diff --git a/nn/runtime/test/generated/all_generated_V1_1_vts_tests.cpp b/nn/runtime/test/generated/all_generated_V1_1_vts_tests.cpp
index 612a79b..02010d1 100644
--- a/nn/runtime/test/generated/all_generated_V1_1_vts_tests.cpp
+++ b/nn/runtime/test/generated/all_generated_V1_1_vts_tests.cpp
@@ -1,6 +1,81 @@
 // DO NOT EDIT;
 // Generated by ml/nn/runtime/test/specs/generate_vts_test.sh
 
+namespace add_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated add_relaxed test
+#include "examples/add_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/add_relaxed.model.cpp"
+} // namespace add_relaxed
+TEST_F(NeuralnetworksHidlTest, add_relaxed) {
+    generated_tests::Execute(device,
+                             add_relaxed::createTestModel,
+                             add_relaxed::is_ignored,
+                             add_relaxed::examples);
+}
+
+namespace avg_pool_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated avg_pool_float_1_relaxed test
+#include "examples/avg_pool_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/avg_pool_float_1_relaxed.model.cpp"
+} // namespace avg_pool_float_1_relaxed
+TEST_F(NeuralnetworksHidlTest, avg_pool_float_1_relaxed) {
+    generated_tests::Execute(device,
+                             avg_pool_float_1_relaxed::createTestModel,
+                             avg_pool_float_1_relaxed::is_ignored,
+                             avg_pool_float_1_relaxed::examples);
+}
+
+namespace avg_pool_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated avg_pool_float_2_relaxed test
+#include "examples/avg_pool_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/avg_pool_float_2_relaxed.model.cpp"
+} // namespace avg_pool_float_2_relaxed
+TEST_F(NeuralnetworksHidlTest, avg_pool_float_2_relaxed) {
+    generated_tests::Execute(device,
+                             avg_pool_float_2_relaxed::createTestModel,
+                             avg_pool_float_2_relaxed::is_ignored,
+                             avg_pool_float_2_relaxed::examples);
+}
+
+namespace avg_pool_float_3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated avg_pool_float_3_relaxed test
+#include "examples/avg_pool_float_3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/avg_pool_float_3_relaxed.model.cpp"
+} // namespace avg_pool_float_3_relaxed
+TEST_F(NeuralnetworksHidlTest, avg_pool_float_3_relaxed) {
+    generated_tests::Execute(device,
+                             avg_pool_float_3_relaxed::createTestModel,
+                             avg_pool_float_3_relaxed::is_ignored,
+                             avg_pool_float_3_relaxed::examples);
+}
+
+namespace avg_pool_float_4_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated avg_pool_float_4_relaxed test
+#include "examples/avg_pool_float_4_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/avg_pool_float_4_relaxed.model.cpp"
+} // namespace avg_pool_float_4_relaxed
+TEST_F(NeuralnetworksHidlTest, avg_pool_float_4_relaxed) {
+    generated_tests::Execute(device,
+                             avg_pool_float_4_relaxed::createTestModel,
+                             avg_pool_float_4_relaxed::is_ignored,
+                             avg_pool_float_4_relaxed::examples);
+}
+
 namespace batch_to_space_float_1 {
 std::vector<MixedTypedExample> examples = {
 // Generated batch_to_space_float_1 test
@@ -46,6 +121,291 @@
                              batch_to_space_quant8_1::examples);
 }
 
+namespace concat_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated concat_float_1_relaxed test
+#include "examples/concat_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/concat_float_1_relaxed.model.cpp"
+} // namespace concat_float_1_relaxed
+TEST_F(NeuralnetworksHidlTest, concat_float_1_relaxed) {
+    generated_tests::Execute(device,
+                             concat_float_1_relaxed::createTestModel,
+                             concat_float_1_relaxed::is_ignored,
+                             concat_float_1_relaxed::examples);
+}
+
+namespace concat_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated concat_float_2_relaxed test
+#include "examples/concat_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/concat_float_2_relaxed.model.cpp"
+} // namespace concat_float_2_relaxed
+TEST_F(NeuralnetworksHidlTest, concat_float_2_relaxed) {
+    generated_tests::Execute(device,
+                             concat_float_2_relaxed::createTestModel,
+                             concat_float_2_relaxed::is_ignored,
+                             concat_float_2_relaxed::examples);
+}
+
+namespace concat_float_3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated concat_float_3_relaxed test
+#include "examples/concat_float_3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/concat_float_3_relaxed.model.cpp"
+} // namespace concat_float_3_relaxed
+TEST_F(NeuralnetworksHidlTest, concat_float_3_relaxed) {
+    generated_tests::Execute(device,
+                             concat_float_3_relaxed::createTestModel,
+                             concat_float_3_relaxed::is_ignored,
+                             concat_float_3_relaxed::examples);
+}
+
+namespace conv_1_h3_w2_SAME_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_1_h3_w2_SAME_relaxed test
+#include "examples/conv_1_h3_w2_SAME_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/conv_1_h3_w2_SAME_relaxed.model.cpp"
+} // namespace conv_1_h3_w2_SAME_relaxed
+TEST_F(NeuralnetworksHidlTest, conv_1_h3_w2_SAME_relaxed) {
+    generated_tests::Execute(device,
+                             conv_1_h3_w2_SAME_relaxed::createTestModel,
+                             conv_1_h3_w2_SAME_relaxed::is_ignored,
+                             conv_1_h3_w2_SAME_relaxed::examples);
+}
+
+namespace conv_1_h3_w2_VALID_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_1_h3_w2_VALID_relaxed test
+#include "examples/conv_1_h3_w2_VALID_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/conv_1_h3_w2_VALID_relaxed.model.cpp"
+} // namespace conv_1_h3_w2_VALID_relaxed
+TEST_F(NeuralnetworksHidlTest, conv_1_h3_w2_VALID_relaxed) {
+    generated_tests::Execute(device,
+                             conv_1_h3_w2_VALID_relaxed::createTestModel,
+                             conv_1_h3_w2_VALID_relaxed::is_ignored,
+                             conv_1_h3_w2_VALID_relaxed::examples);
+}
+
+namespace conv_3_h3_w2_SAME_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_3_h3_w2_SAME_relaxed test
+#include "examples/conv_3_h3_w2_SAME_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/conv_3_h3_w2_SAME_relaxed.model.cpp"
+} // namespace conv_3_h3_w2_SAME_relaxed
+TEST_F(NeuralnetworksHidlTest, conv_3_h3_w2_SAME_relaxed) {
+    generated_tests::Execute(device,
+                             conv_3_h3_w2_SAME_relaxed::createTestModel,
+                             conv_3_h3_w2_SAME_relaxed::is_ignored,
+                             conv_3_h3_w2_SAME_relaxed::examples);
+}
+
+namespace conv_3_h3_w2_VALID_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_3_h3_w2_VALID_relaxed test
+#include "examples/conv_3_h3_w2_VALID_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/conv_3_h3_w2_VALID_relaxed.model.cpp"
+} // namespace conv_3_h3_w2_VALID_relaxed
+TEST_F(NeuralnetworksHidlTest, conv_3_h3_w2_VALID_relaxed) {
+    generated_tests::Execute(device,
+                             conv_3_h3_w2_VALID_relaxed::createTestModel,
+                             conv_3_h3_w2_VALID_relaxed::is_ignored,
+                             conv_3_h3_w2_VALID_relaxed::examples);
+}
+
+namespace conv_float_channels_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_float_channels_relaxed test
+#include "examples/conv_float_channels_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/conv_float_channels_relaxed.model.cpp"
+} // namespace conv_float_channels_relaxed
+TEST_F(NeuralnetworksHidlTest, conv_float_channels_relaxed) {
+    generated_tests::Execute(device,
+                             conv_float_channels_relaxed::createTestModel,
+                             conv_float_channels_relaxed::is_ignored,
+                             conv_float_channels_relaxed::examples);
+}
+
+namespace conv_float_channels_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_float_channels_weights_as_inputs_relaxed test
+#include "examples/conv_float_channels_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/conv_float_channels_weights_as_inputs_relaxed.model.cpp"
+} // namespace conv_float_channels_weights_as_inputs_relaxed
+TEST_F(NeuralnetworksHidlTest, conv_float_channels_weights_as_inputs_relaxed) {
+    generated_tests::Execute(device,
+                             conv_float_channels_weights_as_inputs_relaxed::createTestModel,
+                             conv_float_channels_weights_as_inputs_relaxed::is_ignored,
+                             conv_float_channels_weights_as_inputs_relaxed::examples);
+}
+
+namespace conv_float_large_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_float_large_relaxed test
+#include "examples/conv_float_large_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/conv_float_large_relaxed.model.cpp"
+} // namespace conv_float_large_relaxed
+TEST_F(NeuralnetworksHidlTest, conv_float_large_relaxed) {
+    generated_tests::Execute(device,
+                             conv_float_large_relaxed::createTestModel,
+                             conv_float_large_relaxed::is_ignored,
+                             conv_float_large_relaxed::examples);
+}
+
+namespace conv_float_large_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_float_large_weights_as_inputs_relaxed test
+#include "examples/conv_float_large_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/conv_float_large_weights_as_inputs_relaxed.model.cpp"
+} // namespace conv_float_large_weights_as_inputs_relaxed
+TEST_F(NeuralnetworksHidlTest, conv_float_large_weights_as_inputs_relaxed) {
+    generated_tests::Execute(device,
+                             conv_float_large_weights_as_inputs_relaxed::createTestModel,
+                             conv_float_large_weights_as_inputs_relaxed::is_ignored,
+                             conv_float_large_weights_as_inputs_relaxed::examples);
+}
+
+namespace conv_float_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_float_relaxed test
+#include "examples/conv_float_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/conv_float_relaxed.model.cpp"
+} // namespace conv_float_relaxed
+TEST_F(NeuralnetworksHidlTest, conv_float_relaxed) {
+    generated_tests::Execute(device,
+                             conv_float_relaxed::createTestModel,
+                             conv_float_relaxed::is_ignored,
+                             conv_float_relaxed::examples);
+}
+
+namespace conv_float_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_float_weights_as_inputs_relaxed test
+#include "examples/conv_float_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/conv_float_weights_as_inputs_relaxed.model.cpp"
+} // namespace conv_float_weights_as_inputs_relaxed
+TEST_F(NeuralnetworksHidlTest, conv_float_weights_as_inputs_relaxed) {
+    generated_tests::Execute(device,
+                             conv_float_weights_as_inputs_relaxed::createTestModel,
+                             conv_float_weights_as_inputs_relaxed::is_ignored,
+                             conv_float_weights_as_inputs_relaxed::examples);
+}
+
+namespace depth_to_space_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depth_to_space_float_1_relaxed test
+#include "examples/depth_to_space_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/depth_to_space_float_1_relaxed.model.cpp"
+} // namespace depth_to_space_float_1_relaxed
+TEST_F(NeuralnetworksHidlTest, depth_to_space_float_1_relaxed) {
+    generated_tests::Execute(device,
+                             depth_to_space_float_1_relaxed::createTestModel,
+                             depth_to_space_float_1_relaxed::is_ignored,
+                             depth_to_space_float_1_relaxed::examples);
+}
+
+namespace depth_to_space_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depth_to_space_float_2_relaxed test
+#include "examples/depth_to_space_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/depth_to_space_float_2_relaxed.model.cpp"
+} // namespace depth_to_space_float_2_relaxed
+TEST_F(NeuralnetworksHidlTest, depth_to_space_float_2_relaxed) {
+    generated_tests::Execute(device,
+                             depth_to_space_float_2_relaxed::createTestModel,
+                             depth_to_space_float_2_relaxed::is_ignored,
+                             depth_to_space_float_2_relaxed::examples);
+}
+
+namespace depth_to_space_float_3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depth_to_space_float_3_relaxed test
+#include "examples/depth_to_space_float_3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/depth_to_space_float_3_relaxed.model.cpp"
+} // namespace depth_to_space_float_3_relaxed
+TEST_F(NeuralnetworksHidlTest, depth_to_space_float_3_relaxed) {
+    generated_tests::Execute(device,
+                             depth_to_space_float_3_relaxed::createTestModel,
+                             depth_to_space_float_3_relaxed::is_ignored,
+                             depth_to_space_float_3_relaxed::examples);
+}
+
+namespace depthwise_conv2d_float_large_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depthwise_conv2d_float_large_relaxed test
+#include "examples/depthwise_conv2d_float_large_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/depthwise_conv2d_float_large_relaxed.model.cpp"
+} // namespace depthwise_conv2d_float_large_relaxed
+TEST_F(NeuralnetworksHidlTest, depthwise_conv2d_float_large_relaxed) {
+    generated_tests::Execute(device,
+                             depthwise_conv2d_float_large_relaxed::createTestModel,
+                             depthwise_conv2d_float_large_relaxed::is_ignored,
+                             depthwise_conv2d_float_large_relaxed::examples);
+}
+
+namespace depthwise_conv2d_float_large_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depthwise_conv2d_float_large_weights_as_inputs_relaxed test
+#include "examples/depthwise_conv2d_float_large_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/depthwise_conv2d_float_large_weights_as_inputs_relaxed.model.cpp"
+} // namespace depthwise_conv2d_float_large_weights_as_inputs_relaxed
+TEST_F(NeuralnetworksHidlTest, depthwise_conv2d_float_large_weights_as_inputs_relaxed) {
+    generated_tests::Execute(device,
+                             depthwise_conv2d_float_large_weights_as_inputs_relaxed::createTestModel,
+                             depthwise_conv2d_float_large_weights_as_inputs_relaxed::is_ignored,
+                             depthwise_conv2d_float_large_weights_as_inputs_relaxed::examples);
+}
+
+namespace depthwise_conv_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depthwise_conv_relaxed test
+#include "examples/depthwise_conv_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/depthwise_conv_relaxed.model.cpp"
+} // namespace depthwise_conv_relaxed
+TEST_F(NeuralnetworksHidlTest, depthwise_conv_relaxed) {
+    generated_tests::Execute(device,
+                             depthwise_conv_relaxed::createTestModel,
+                             depthwise_conv_relaxed::is_ignored,
+                             depthwise_conv_relaxed::examples);
+}
+
 namespace div {
 std::vector<MixedTypedExample> examples = {
 // Generated div test
@@ -61,6 +421,456 @@
                              div::examples);
 }
 
+namespace embedding_lookup_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated embedding_lookup_relaxed test
+#include "examples/embedding_lookup_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/embedding_lookup_relaxed.model.cpp"
+} // namespace embedding_lookup_relaxed
+TEST_F(NeuralnetworksHidlTest, embedding_lookup_relaxed) {
+    generated_tests::Execute(device,
+                             embedding_lookup_relaxed::createTestModel,
+                             embedding_lookup_relaxed::is_ignored,
+                             embedding_lookup_relaxed::examples);
+}
+
+namespace floor_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated floor_relaxed test
+#include "examples/floor_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/floor_relaxed.model.cpp"
+} // namespace floor_relaxed
+TEST_F(NeuralnetworksHidlTest, floor_relaxed) {
+    generated_tests::Execute(device,
+                             floor_relaxed::createTestModel,
+                             floor_relaxed::is_ignored,
+                             floor_relaxed::examples);
+}
+
+namespace fully_connected_float_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated fully_connected_float_relaxed test
+#include "examples/fully_connected_float_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/fully_connected_float_relaxed.model.cpp"
+} // namespace fully_connected_float_relaxed
+TEST_F(NeuralnetworksHidlTest, fully_connected_float_relaxed) {
+    generated_tests::Execute(device,
+                             fully_connected_float_relaxed::createTestModel,
+                             fully_connected_float_relaxed::is_ignored,
+                             fully_connected_float_relaxed::examples);
+}
+
+namespace fully_connected_float_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated fully_connected_float_weights_as_inputs_relaxed test
+#include "examples/fully_connected_float_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/fully_connected_float_weights_as_inputs_relaxed.model.cpp"
+} // namespace fully_connected_float_weights_as_inputs_relaxed
+TEST_F(NeuralnetworksHidlTest, fully_connected_float_weights_as_inputs_relaxed) {
+    generated_tests::Execute(device,
+                             fully_connected_float_weights_as_inputs_relaxed::createTestModel,
+                             fully_connected_float_weights_as_inputs_relaxed::is_ignored,
+                             fully_connected_float_weights_as_inputs_relaxed::examples);
+}
+
+namespace hashtable_lookup_float_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated hashtable_lookup_float_relaxed test
+#include "examples/hashtable_lookup_float_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/hashtable_lookup_float_relaxed.model.cpp"
+} // namespace hashtable_lookup_float_relaxed
+TEST_F(NeuralnetworksHidlTest, hashtable_lookup_float_relaxed) {
+    generated_tests::Execute(device,
+                             hashtable_lookup_float_relaxed::createTestModel,
+                             hashtable_lookup_float_relaxed::is_ignored,
+                             hashtable_lookup_float_relaxed::examples);
+}
+
+namespace l2_normalization_large_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated l2_normalization_large_relaxed test
+#include "examples/l2_normalization_large_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/l2_normalization_large_relaxed.model.cpp"
+} // namespace l2_normalization_large_relaxed
+TEST_F(NeuralnetworksHidlTest, l2_normalization_large_relaxed) {
+    generated_tests::Execute(device,
+                             l2_normalization_large_relaxed::createTestModel,
+                             l2_normalization_large_relaxed::is_ignored,
+                             l2_normalization_large_relaxed::examples);
+}
+
+namespace l2_normalization_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated l2_normalization_relaxed test
+#include "examples/l2_normalization_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/l2_normalization_relaxed.model.cpp"
+} // namespace l2_normalization_relaxed
+TEST_F(NeuralnetworksHidlTest, l2_normalization_relaxed) {
+    generated_tests::Execute(device,
+                             l2_normalization_relaxed::createTestModel,
+                             l2_normalization_relaxed::is_ignored,
+                             l2_normalization_relaxed::examples);
+}
+
+namespace l2_pool_float_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated l2_pool_float_relaxed test
+#include "examples/l2_pool_float_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/l2_pool_float_relaxed.model.cpp"
+} // namespace l2_pool_float_relaxed
+TEST_F(NeuralnetworksHidlTest, l2_pool_float_relaxed) {
+    generated_tests::Execute(device,
+                             l2_pool_float_relaxed::createTestModel,
+                             l2_pool_float_relaxed::is_ignored,
+                             l2_pool_float_relaxed::examples);
+}
+
+namespace local_response_norm_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated local_response_norm_float_1_relaxed test
+#include "examples/local_response_norm_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/local_response_norm_float_1_relaxed.model.cpp"
+} // namespace local_response_norm_float_1_relaxed
+TEST_F(NeuralnetworksHidlTest, local_response_norm_float_1_relaxed) {
+    generated_tests::Execute(device,
+                             local_response_norm_float_1_relaxed::createTestModel,
+                             local_response_norm_float_1_relaxed::is_ignored,
+                             local_response_norm_float_1_relaxed::examples);
+}
+
+namespace local_response_norm_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated local_response_norm_float_2_relaxed test
+#include "examples/local_response_norm_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/local_response_norm_float_2_relaxed.model.cpp"
+} // namespace local_response_norm_float_2_relaxed
+TEST_F(NeuralnetworksHidlTest, local_response_norm_float_2_relaxed) {
+    generated_tests::Execute(device,
+                             local_response_norm_float_2_relaxed::createTestModel,
+                             local_response_norm_float_2_relaxed::is_ignored,
+                             local_response_norm_float_2_relaxed::examples);
+}
+
+namespace local_response_norm_float_3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated local_response_norm_float_3_relaxed test
+#include "examples/local_response_norm_float_3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/local_response_norm_float_3_relaxed.model.cpp"
+} // namespace local_response_norm_float_3_relaxed
+TEST_F(NeuralnetworksHidlTest, local_response_norm_float_3_relaxed) {
+    generated_tests::Execute(device,
+                             local_response_norm_float_3_relaxed::createTestModel,
+                             local_response_norm_float_3_relaxed::is_ignored,
+                             local_response_norm_float_3_relaxed::examples);
+}
+
+namespace local_response_norm_float_4_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated local_response_norm_float_4_relaxed test
+#include "examples/local_response_norm_float_4_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/local_response_norm_float_4_relaxed.model.cpp"
+} // namespace local_response_norm_float_4_relaxed
+TEST_F(NeuralnetworksHidlTest, local_response_norm_float_4_relaxed) {
+    generated_tests::Execute(device,
+                             local_response_norm_float_4_relaxed::createTestModel,
+                             local_response_norm_float_4_relaxed::is_ignored,
+                             local_response_norm_float_4_relaxed::examples);
+}
+
+namespace logistic_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated logistic_float_1_relaxed test
+#include "examples/logistic_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/logistic_float_1_relaxed.model.cpp"
+} // namespace logistic_float_1_relaxed
+TEST_F(NeuralnetworksHidlTest, logistic_float_1_relaxed) {
+    generated_tests::Execute(device,
+                             logistic_float_1_relaxed::createTestModel,
+                             logistic_float_1_relaxed::is_ignored,
+                             logistic_float_1_relaxed::examples);
+}
+
+namespace logistic_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated logistic_float_2_relaxed test
+#include "examples/logistic_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/logistic_float_2_relaxed.model.cpp"
+} // namespace logistic_float_2_relaxed
+TEST_F(NeuralnetworksHidlTest, logistic_float_2_relaxed) {
+    generated_tests::Execute(device,
+                             logistic_float_2_relaxed::createTestModel,
+                             logistic_float_2_relaxed::is_ignored,
+                             logistic_float_2_relaxed::examples);
+}
+
+namespace lsh_projection_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lsh_projection_2_relaxed test
+#include "examples/lsh_projection_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/lsh_projection_2_relaxed.model.cpp"
+} // namespace lsh_projection_2_relaxed
+TEST_F(NeuralnetworksHidlTest, lsh_projection_2_relaxed) {
+    generated_tests::Execute(device,
+                             lsh_projection_2_relaxed::createTestModel,
+                             lsh_projection_2_relaxed::is_ignored,
+                             lsh_projection_2_relaxed::examples);
+}
+
+namespace lsh_projection_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lsh_projection_relaxed test
+#include "examples/lsh_projection_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/lsh_projection_relaxed.model.cpp"
+} // namespace lsh_projection_relaxed
+TEST_F(NeuralnetworksHidlTest, lsh_projection_relaxed) {
+    generated_tests::Execute(device,
+                             lsh_projection_relaxed::createTestModel,
+                             lsh_projection_relaxed::is_ignored,
+                             lsh_projection_relaxed::examples);
+}
+
+namespace lsh_projection_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lsh_projection_weights_as_inputs_relaxed test
+#include "examples/lsh_projection_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/lsh_projection_weights_as_inputs_relaxed.model.cpp"
+} // namespace lsh_projection_weights_as_inputs_relaxed
+TEST_F(NeuralnetworksHidlTest, lsh_projection_weights_as_inputs_relaxed) {
+    generated_tests::Execute(device,
+                             lsh_projection_weights_as_inputs_relaxed::createTestModel,
+                             lsh_projection_weights_as_inputs_relaxed::is_ignored,
+                             lsh_projection_weights_as_inputs_relaxed::examples);
+}
+
+namespace lstm2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm2_relaxed test
+#include "examples/lstm2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/lstm2_relaxed.model.cpp"
+} // namespace lstm2_relaxed
+TEST_F(NeuralnetworksHidlTest, lstm2_relaxed) {
+    generated_tests::Execute(device,
+                             lstm2_relaxed::createTestModel,
+                             lstm2_relaxed::is_ignored,
+                             lstm2_relaxed::examples);
+}
+
+namespace lstm2_state2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm2_state2_relaxed test
+#include "examples/lstm2_state2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/lstm2_state2_relaxed.model.cpp"
+} // namespace lstm2_state2_relaxed
+TEST_F(NeuralnetworksHidlTest, lstm2_state2_relaxed) {
+    generated_tests::Execute(device,
+                             lstm2_state2_relaxed::createTestModel,
+                             lstm2_state2_relaxed::is_ignored,
+                             lstm2_state2_relaxed::examples);
+}
+
+namespace lstm2_state_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm2_state_relaxed test
+#include "examples/lstm2_state_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/lstm2_state_relaxed.model.cpp"
+} // namespace lstm2_state_relaxed
+TEST_F(NeuralnetworksHidlTest, lstm2_state_relaxed) {
+    generated_tests::Execute(device,
+                             lstm2_state_relaxed::createTestModel,
+                             lstm2_state_relaxed::is_ignored,
+                             lstm2_state_relaxed::examples);
+}
+
+namespace lstm3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm3_relaxed test
+#include "examples/lstm3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/lstm3_relaxed.model.cpp"
+} // namespace lstm3_relaxed
+TEST_F(NeuralnetworksHidlTest, lstm3_relaxed) {
+    generated_tests::Execute(device,
+                             lstm3_relaxed::createTestModel,
+                             lstm3_relaxed::is_ignored,
+                             lstm3_relaxed::examples);
+}
+
+namespace lstm3_state2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm3_state2_relaxed test
+#include "examples/lstm3_state2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/lstm3_state2_relaxed.model.cpp"
+} // namespace lstm3_state2_relaxed
+TEST_F(NeuralnetworksHidlTest, lstm3_state2_relaxed) {
+    generated_tests::Execute(device,
+                             lstm3_state2_relaxed::createTestModel,
+                             lstm3_state2_relaxed::is_ignored,
+                             lstm3_state2_relaxed::examples);
+}
+
+namespace lstm3_state3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm3_state3_relaxed test
+#include "examples/lstm3_state3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/lstm3_state3_relaxed.model.cpp"
+} // namespace lstm3_state3_relaxed
+TEST_F(NeuralnetworksHidlTest, lstm3_state3_relaxed) {
+    generated_tests::Execute(device,
+                             lstm3_state3_relaxed::createTestModel,
+                             lstm3_state3_relaxed::is_ignored,
+                             lstm3_state3_relaxed::examples);
+}
+
+namespace lstm3_state_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm3_state_relaxed test
+#include "examples/lstm3_state_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/lstm3_state_relaxed.model.cpp"
+} // namespace lstm3_state_relaxed
+TEST_F(NeuralnetworksHidlTest, lstm3_state_relaxed) {
+    generated_tests::Execute(device,
+                             lstm3_state_relaxed::createTestModel,
+                             lstm3_state_relaxed::is_ignored,
+                             lstm3_state_relaxed::examples);
+}
+
+namespace lstm_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm_relaxed test
+#include "examples/lstm_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/lstm_relaxed.model.cpp"
+} // namespace lstm_relaxed
+TEST_F(NeuralnetworksHidlTest, lstm_relaxed) {
+    generated_tests::Execute(device,
+                             lstm_relaxed::createTestModel,
+                             lstm_relaxed::is_ignored,
+                             lstm_relaxed::examples);
+}
+
+namespace lstm_state2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm_state2_relaxed test
+#include "examples/lstm_state2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/lstm_state2_relaxed.model.cpp"
+} // namespace lstm_state2_relaxed
+TEST_F(NeuralnetworksHidlTest, lstm_state2_relaxed) {
+    generated_tests::Execute(device,
+                             lstm_state2_relaxed::createTestModel,
+                             lstm_state2_relaxed::is_ignored,
+                             lstm_state2_relaxed::examples);
+}
+
+namespace lstm_state_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm_state_relaxed test
+#include "examples/lstm_state_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/lstm_state_relaxed.model.cpp"
+} // namespace lstm_state_relaxed
+TEST_F(NeuralnetworksHidlTest, lstm_state_relaxed) {
+    generated_tests::Execute(device,
+                             lstm_state_relaxed::createTestModel,
+                             lstm_state_relaxed::is_ignored,
+                             lstm_state_relaxed::examples);
+}
+
+namespace max_pool_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated max_pool_float_1_relaxed test
+#include "examples/max_pool_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/max_pool_float_1_relaxed.model.cpp"
+} // namespace max_pool_float_1_relaxed
+TEST_F(NeuralnetworksHidlTest, max_pool_float_1_relaxed) {
+    generated_tests::Execute(device,
+                             max_pool_float_1_relaxed::createTestModel,
+                             max_pool_float_1_relaxed::is_ignored,
+                             max_pool_float_1_relaxed::examples);
+}
+
+namespace max_pool_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated max_pool_float_2_relaxed test
+#include "examples/max_pool_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/max_pool_float_2_relaxed.model.cpp"
+} // namespace max_pool_float_2_relaxed
+TEST_F(NeuralnetworksHidlTest, max_pool_float_2_relaxed) {
+    generated_tests::Execute(device,
+                             max_pool_float_2_relaxed::createTestModel,
+                             max_pool_float_2_relaxed::is_ignored,
+                             max_pool_float_2_relaxed::examples);
+}
+
+namespace max_pool_float_3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated max_pool_float_3_relaxed test
+#include "examples/max_pool_float_3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/max_pool_float_3_relaxed.model.cpp"
+} // namespace max_pool_float_3_relaxed
+TEST_F(NeuralnetworksHidlTest, max_pool_float_3_relaxed) {
+    generated_tests::Execute(device,
+                             max_pool_float_3_relaxed::createTestModel,
+                             max_pool_float_3_relaxed::is_ignored,
+                             max_pool_float_3_relaxed::examples);
+}
+
 namespace mean_float_1 {
 std::vector<MixedTypedExample> examples = {
 // Generated mean_float_1 test
@@ -106,6 +916,51 @@
                              mean::examples);
 }
 
+namespace mobilenet_224_gender_basic_fixed_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated mobilenet_224_gender_basic_fixed_relaxed test
+#include "examples/mobilenet_224_gender_basic_fixed_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/mobilenet_224_gender_basic_fixed_relaxed.model.cpp"
+} // namespace mobilenet_224_gender_basic_fixed_relaxed
+TEST_F(NeuralnetworksHidlTest, mobilenet_224_gender_basic_fixed_relaxed) {
+    generated_tests::Execute(device,
+                             mobilenet_224_gender_basic_fixed_relaxed::createTestModel,
+                             mobilenet_224_gender_basic_fixed_relaxed::is_ignored,
+                             mobilenet_224_gender_basic_fixed_relaxed::examples);
+}
+
+namespace mul_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated mul_relaxed test
+#include "examples/mul_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/mul_relaxed.model.cpp"
+} // namespace mul_relaxed
+TEST_F(NeuralnetworksHidlTest, mul_relaxed) {
+    generated_tests::Execute(device,
+                             mul_relaxed::createTestModel,
+                             mul_relaxed::is_ignored,
+                             mul_relaxed::examples);
+}
+
+namespace mul_relu_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated mul_relu_relaxed test
+#include "examples/mul_relu_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/mul_relu_relaxed.model.cpp"
+} // namespace mul_relu_relaxed
+TEST_F(NeuralnetworksHidlTest, mul_relu_relaxed) {
+    generated_tests::Execute(device,
+                             mul_relu_relaxed::createTestModel,
+                             mul_relu_relaxed::is_ignored,
+                             mul_relu_relaxed::examples);
+}
+
 namespace pad_float_1 {
 std::vector<MixedTypedExample> examples = {
 // Generated pad_float_1 test
@@ -136,6 +991,186 @@
                              pad::examples);
 }
 
+namespace relu1_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated relu1_float_1_relaxed test
+#include "examples/relu1_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/relu1_float_1_relaxed.model.cpp"
+} // namespace relu1_float_1_relaxed
+TEST_F(NeuralnetworksHidlTest, relu1_float_1_relaxed) {
+    generated_tests::Execute(device,
+                             relu1_float_1_relaxed::createTestModel,
+                             relu1_float_1_relaxed::is_ignored,
+                             relu1_float_1_relaxed::examples);
+}
+
+namespace relu1_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated relu1_float_2_relaxed test
+#include "examples/relu1_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/relu1_float_2_relaxed.model.cpp"
+} // namespace relu1_float_2_relaxed
+TEST_F(NeuralnetworksHidlTest, relu1_float_2_relaxed) {
+    generated_tests::Execute(device,
+                             relu1_float_2_relaxed::createTestModel,
+                             relu1_float_2_relaxed::is_ignored,
+                             relu1_float_2_relaxed::examples);
+}
+
+namespace relu6_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated relu6_float_1_relaxed test
+#include "examples/relu6_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/relu6_float_1_relaxed.model.cpp"
+} // namespace relu6_float_1_relaxed
+TEST_F(NeuralnetworksHidlTest, relu6_float_1_relaxed) {
+    generated_tests::Execute(device,
+                             relu6_float_1_relaxed::createTestModel,
+                             relu6_float_1_relaxed::is_ignored,
+                             relu6_float_1_relaxed::examples);
+}
+
+namespace relu6_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated relu6_float_2_relaxed test
+#include "examples/relu6_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/relu6_float_2_relaxed.model.cpp"
+} // namespace relu6_float_2_relaxed
+TEST_F(NeuralnetworksHidlTest, relu6_float_2_relaxed) {
+    generated_tests::Execute(device,
+                             relu6_float_2_relaxed::createTestModel,
+                             relu6_float_2_relaxed::is_ignored,
+                             relu6_float_2_relaxed::examples);
+}
+
+namespace relu_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated relu_float_1_relaxed test
+#include "examples/relu_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/relu_float_1_relaxed.model.cpp"
+} // namespace relu_float_1_relaxed
+TEST_F(NeuralnetworksHidlTest, relu_float_1_relaxed) {
+    generated_tests::Execute(device,
+                             relu_float_1_relaxed::createTestModel,
+                             relu_float_1_relaxed::is_ignored,
+                             relu_float_1_relaxed::examples);
+}
+
+namespace reshape_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated reshape_relaxed test
+#include "examples/reshape_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/reshape_relaxed.model.cpp"
+} // namespace reshape_relaxed
+TEST_F(NeuralnetworksHidlTest, reshape_relaxed) {
+    generated_tests::Execute(device,
+                             reshape_relaxed::createTestModel,
+                             reshape_relaxed::is_ignored,
+                             reshape_relaxed::examples);
+}
+
+namespace reshape_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated reshape_weights_as_inputs_relaxed test
+#include "examples/reshape_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/reshape_weights_as_inputs_relaxed.model.cpp"
+} // namespace reshape_weights_as_inputs_relaxed
+TEST_F(NeuralnetworksHidlTest, reshape_weights_as_inputs_relaxed) {
+    generated_tests::Execute(device,
+                             reshape_weights_as_inputs_relaxed::createTestModel,
+                             reshape_weights_as_inputs_relaxed::is_ignored,
+                             reshape_weights_as_inputs_relaxed::examples);
+}
+
+namespace resize_bilinear_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated resize_bilinear_relaxed test
+#include "examples/resize_bilinear_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/resize_bilinear_relaxed.model.cpp"
+} // namespace resize_bilinear_relaxed
+TEST_F(NeuralnetworksHidlTest, resize_bilinear_relaxed) {
+    generated_tests::Execute(device,
+                             resize_bilinear_relaxed::createTestModel,
+                             resize_bilinear_relaxed::is_ignored,
+                             resize_bilinear_relaxed::examples);
+}
+
+namespace rnn_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated rnn_relaxed test
+#include "examples/rnn_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/rnn_relaxed.model.cpp"
+} // namespace rnn_relaxed
+TEST_F(NeuralnetworksHidlTest, rnn_relaxed) {
+    generated_tests::Execute(device,
+                             rnn_relaxed::createTestModel,
+                             rnn_relaxed::is_ignored,
+                             rnn_relaxed::examples);
+}
+
+namespace rnn_state_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated rnn_state_relaxed test
+#include "examples/rnn_state_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/rnn_state_relaxed.model.cpp"
+} // namespace rnn_state_relaxed
+TEST_F(NeuralnetworksHidlTest, rnn_state_relaxed) {
+    generated_tests::Execute(device,
+                             rnn_state_relaxed::createTestModel,
+                             rnn_state_relaxed::is_ignored,
+                             rnn_state_relaxed::examples);
+}
+
+namespace softmax_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated softmax_float_1_relaxed test
+#include "examples/softmax_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/softmax_float_1_relaxed.model.cpp"
+} // namespace softmax_float_1_relaxed
+TEST_F(NeuralnetworksHidlTest, softmax_float_1_relaxed) {
+    generated_tests::Execute(device,
+                             softmax_float_1_relaxed::createTestModel,
+                             softmax_float_1_relaxed::is_ignored,
+                             softmax_float_1_relaxed::examples);
+}
+
+namespace softmax_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated softmax_float_2_relaxed test
+#include "examples/softmax_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/softmax_float_2_relaxed.model.cpp"
+} // namespace softmax_float_2_relaxed
+TEST_F(NeuralnetworksHidlTest, softmax_float_2_relaxed) {
+    generated_tests::Execute(device,
+                             softmax_float_2_relaxed::createTestModel,
+                             softmax_float_2_relaxed::is_ignored,
+                             softmax_float_2_relaxed::examples);
+}
+
 namespace space_to_batch_float_1 {
 std::vector<MixedTypedExample> examples = {
 // Generated space_to_batch_float_1 test
@@ -241,6 +1276,51 @@
                              space_to_batch_quant8_3::examples);
 }
 
+namespace space_to_depth_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated space_to_depth_float_1_relaxed test
+#include "examples/space_to_depth_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/space_to_depth_float_1_relaxed.model.cpp"
+} // namespace space_to_depth_float_1_relaxed
+TEST_F(NeuralnetworksHidlTest, space_to_depth_float_1_relaxed) {
+    generated_tests::Execute(device,
+                             space_to_depth_float_1_relaxed::createTestModel,
+                             space_to_depth_float_1_relaxed::is_ignored,
+                             space_to_depth_float_1_relaxed::examples);
+}
+
+namespace space_to_depth_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated space_to_depth_float_2_relaxed test
+#include "examples/space_to_depth_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/space_to_depth_float_2_relaxed.model.cpp"
+} // namespace space_to_depth_float_2_relaxed
+TEST_F(NeuralnetworksHidlTest, space_to_depth_float_2_relaxed) {
+    generated_tests::Execute(device,
+                             space_to_depth_float_2_relaxed::createTestModel,
+                             space_to_depth_float_2_relaxed::is_ignored,
+                             space_to_depth_float_2_relaxed::examples);
+}
+
+namespace space_to_depth_float_3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated space_to_depth_float_3_relaxed test
+#include "examples/space_to_depth_float_3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/space_to_depth_float_3_relaxed.model.cpp"
+} // namespace space_to_depth_float_3_relaxed
+TEST_F(NeuralnetworksHidlTest, space_to_depth_float_3_relaxed) {
+    generated_tests::Execute(device,
+                             space_to_depth_float_3_relaxed::createTestModel,
+                             space_to_depth_float_3_relaxed::is_ignored,
+                             space_to_depth_float_3_relaxed::examples);
+}
+
 namespace squeeze_float_1 {
 std::vector<MixedTypedExample> examples = {
 // Generated squeeze_float_1 test
@@ -616,6 +1696,66 @@
                              sub::examples);
 }
 
+namespace svdf2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated svdf2_relaxed test
+#include "examples/svdf2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/svdf2_relaxed.model.cpp"
+} // namespace svdf2_relaxed
+TEST_F(NeuralnetworksHidlTest, svdf2_relaxed) {
+    generated_tests::Execute(device,
+                             svdf2_relaxed::createTestModel,
+                             svdf2_relaxed::is_ignored,
+                             svdf2_relaxed::examples);
+}
+
+namespace svdf_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated svdf_relaxed test
+#include "examples/svdf_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/svdf_relaxed.model.cpp"
+} // namespace svdf_relaxed
+TEST_F(NeuralnetworksHidlTest, svdf_relaxed) {
+    generated_tests::Execute(device,
+                             svdf_relaxed::createTestModel,
+                             svdf_relaxed::is_ignored,
+                             svdf_relaxed::examples);
+}
+
+namespace svdf_state_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated svdf_state_relaxed test
+#include "examples/svdf_state_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/svdf_state_relaxed.model.cpp"
+} // namespace svdf_state_relaxed
+TEST_F(NeuralnetworksHidlTest, svdf_state_relaxed) {
+    generated_tests::Execute(device,
+                             svdf_state_relaxed::createTestModel,
+                             svdf_state_relaxed::is_ignored,
+                             svdf_state_relaxed::examples);
+}
+
+namespace tanh_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated tanh_relaxed test
+#include "examples/tanh_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/tanh_relaxed.model.cpp"
+} // namespace tanh_relaxed
+TEST_F(NeuralnetworksHidlTest, tanh_relaxed) {
+    generated_tests::Execute(device,
+                             tanh_relaxed::createTestModel,
+                             tanh_relaxed::is_ignored,
+                             tanh_relaxed::examples);
+}
+
 namespace transpose_float_1 {
 std::vector<MixedTypedExample> examples = {
 // Generated transpose_float_1 test
diff --git a/nn/runtime/test/generated/all_generated_tests.cpp b/nn/runtime/test/generated/all_generated_tests.cpp
index 5b07cb4..f1b794d 100644
--- a/nn/runtime/test/generated/all_generated_tests.cpp
+++ b/nn/runtime/test/generated/all_generated_tests.cpp
@@ -1863,6 +1863,76 @@
             tanh::examples);
 }
 
+namespace add_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated add_relaxed test
+#include "generated/examples/add_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/add_relaxed.model.cpp"
+} // namespace add_relaxed
+TEST_F(GeneratedTests, add_relaxed) {
+    execute(add_relaxed::CreateModel,
+            add_relaxed::is_ignored,
+            add_relaxed::examples);
+}
+
+namespace avg_pool_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated avg_pool_float_1_relaxed test
+#include "generated/examples/avg_pool_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/avg_pool_float_1_relaxed.model.cpp"
+} // namespace avg_pool_float_1_relaxed
+TEST_F(GeneratedTests, avg_pool_float_1_relaxed) {
+    execute(avg_pool_float_1_relaxed::CreateModel,
+            avg_pool_float_1_relaxed::is_ignored,
+            avg_pool_float_1_relaxed::examples);
+}
+
+namespace avg_pool_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated avg_pool_float_2_relaxed test
+#include "generated/examples/avg_pool_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/avg_pool_float_2_relaxed.model.cpp"
+} // namespace avg_pool_float_2_relaxed
+TEST_F(GeneratedTests, avg_pool_float_2_relaxed) {
+    execute(avg_pool_float_2_relaxed::CreateModel,
+            avg_pool_float_2_relaxed::is_ignored,
+            avg_pool_float_2_relaxed::examples);
+}
+
+namespace avg_pool_float_3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated avg_pool_float_3_relaxed test
+#include "generated/examples/avg_pool_float_3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/avg_pool_float_3_relaxed.model.cpp"
+} // namespace avg_pool_float_3_relaxed
+TEST_F(GeneratedTests, avg_pool_float_3_relaxed) {
+    execute(avg_pool_float_3_relaxed::CreateModel,
+            avg_pool_float_3_relaxed::is_ignored,
+            avg_pool_float_3_relaxed::examples);
+}
+
+namespace avg_pool_float_4_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated avg_pool_float_4_relaxed test
+#include "generated/examples/avg_pool_float_4_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/avg_pool_float_4_relaxed.model.cpp"
+} // namespace avg_pool_float_4_relaxed
+TEST_F(GeneratedTests, avg_pool_float_4_relaxed) {
+    execute(avg_pool_float_4_relaxed::CreateModel,
+            avg_pool_float_4_relaxed::is_ignored,
+            avg_pool_float_4_relaxed::examples);
+}
+
 namespace batch_to_space_float_1 {
 std::vector<MixedTypedExample> examples = {
 // Generated batch_to_space_float_1 test
@@ -1905,6 +1975,272 @@
             batch_to_space_quant8_1::examples);
 }
 
+namespace concat_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated concat_float_1_relaxed test
+#include "generated/examples/concat_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/concat_float_1_relaxed.model.cpp"
+} // namespace concat_float_1_relaxed
+TEST_F(GeneratedTests, concat_float_1_relaxed) {
+    execute(concat_float_1_relaxed::CreateModel,
+            concat_float_1_relaxed::is_ignored,
+            concat_float_1_relaxed::examples);
+}
+
+namespace concat_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated concat_float_2_relaxed test
+#include "generated/examples/concat_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/concat_float_2_relaxed.model.cpp"
+} // namespace concat_float_2_relaxed
+TEST_F(GeneratedTests, concat_float_2_relaxed) {
+    execute(concat_float_2_relaxed::CreateModel,
+            concat_float_2_relaxed::is_ignored,
+            concat_float_2_relaxed::examples);
+}
+
+namespace concat_float_3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated concat_float_3_relaxed test
+#include "generated/examples/concat_float_3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/concat_float_3_relaxed.model.cpp"
+} // namespace concat_float_3_relaxed
+TEST_F(GeneratedTests, concat_float_3_relaxed) {
+    execute(concat_float_3_relaxed::CreateModel,
+            concat_float_3_relaxed::is_ignored,
+            concat_float_3_relaxed::examples);
+}
+
+namespace conv_1_h3_w2_SAME_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_1_h3_w2_SAME_relaxed test
+#include "generated/examples/conv_1_h3_w2_SAME_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/conv_1_h3_w2_SAME_relaxed.model.cpp"
+} // namespace conv_1_h3_w2_SAME_relaxed
+TEST_F(GeneratedTests, conv_1_h3_w2_SAME_relaxed) {
+    execute(conv_1_h3_w2_SAME_relaxed::CreateModel,
+            conv_1_h3_w2_SAME_relaxed::is_ignored,
+            conv_1_h3_w2_SAME_relaxed::examples);
+}
+
+namespace conv_1_h3_w2_VALID_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_1_h3_w2_VALID_relaxed test
+#include "generated/examples/conv_1_h3_w2_VALID_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/conv_1_h3_w2_VALID_relaxed.model.cpp"
+} // namespace conv_1_h3_w2_VALID_relaxed
+TEST_F(GeneratedTests, conv_1_h3_w2_VALID_relaxed) {
+    execute(conv_1_h3_w2_VALID_relaxed::CreateModel,
+            conv_1_h3_w2_VALID_relaxed::is_ignored,
+            conv_1_h3_w2_VALID_relaxed::examples);
+}
+
+namespace conv_3_h3_w2_SAME_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_3_h3_w2_SAME_relaxed test
+#include "generated/examples/conv_3_h3_w2_SAME_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/conv_3_h3_w2_SAME_relaxed.model.cpp"
+} // namespace conv_3_h3_w2_SAME_relaxed
+TEST_F(GeneratedTests, conv_3_h3_w2_SAME_relaxed) {
+    execute(conv_3_h3_w2_SAME_relaxed::CreateModel,
+            conv_3_h3_w2_SAME_relaxed::is_ignored,
+            conv_3_h3_w2_SAME_relaxed::examples);
+}
+
+namespace conv_3_h3_w2_VALID_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_3_h3_w2_VALID_relaxed test
+#include "generated/examples/conv_3_h3_w2_VALID_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/conv_3_h3_w2_VALID_relaxed.model.cpp"
+} // namespace conv_3_h3_w2_VALID_relaxed
+TEST_F(GeneratedTests, conv_3_h3_w2_VALID_relaxed) {
+    execute(conv_3_h3_w2_VALID_relaxed::CreateModel,
+            conv_3_h3_w2_VALID_relaxed::is_ignored,
+            conv_3_h3_w2_VALID_relaxed::examples);
+}
+
+namespace conv_float_channels_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_float_channels_relaxed test
+#include "generated/examples/conv_float_channels_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/conv_float_channels_relaxed.model.cpp"
+} // namespace conv_float_channels_relaxed
+TEST_F(GeneratedTests, conv_float_channels_relaxed) {
+    execute(conv_float_channels_relaxed::CreateModel,
+            conv_float_channels_relaxed::is_ignored,
+            conv_float_channels_relaxed::examples);
+}
+
+namespace conv_float_channels_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_float_channels_weights_as_inputs_relaxed test
+#include "generated/examples/conv_float_channels_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/conv_float_channels_weights_as_inputs_relaxed.model.cpp"
+} // namespace conv_float_channels_weights_as_inputs_relaxed
+TEST_F(GeneratedTests, conv_float_channels_weights_as_inputs_relaxed) {
+    execute(conv_float_channels_weights_as_inputs_relaxed::CreateModel,
+            conv_float_channels_weights_as_inputs_relaxed::is_ignored,
+            conv_float_channels_weights_as_inputs_relaxed::examples);
+}
+
+namespace conv_float_large_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_float_large_relaxed test
+#include "generated/examples/conv_float_large_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/conv_float_large_relaxed.model.cpp"
+} // namespace conv_float_large_relaxed
+TEST_F(GeneratedTests, conv_float_large_relaxed) {
+    execute(conv_float_large_relaxed::CreateModel,
+            conv_float_large_relaxed::is_ignored,
+            conv_float_large_relaxed::examples);
+}
+
+namespace conv_float_large_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_float_large_weights_as_inputs_relaxed test
+#include "generated/examples/conv_float_large_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/conv_float_large_weights_as_inputs_relaxed.model.cpp"
+} // namespace conv_float_large_weights_as_inputs_relaxed
+TEST_F(GeneratedTests, conv_float_large_weights_as_inputs_relaxed) {
+    execute(conv_float_large_weights_as_inputs_relaxed::CreateModel,
+            conv_float_large_weights_as_inputs_relaxed::is_ignored,
+            conv_float_large_weights_as_inputs_relaxed::examples);
+}
+
+namespace conv_float_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_float_relaxed test
+#include "generated/examples/conv_float_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/conv_float_relaxed.model.cpp"
+} // namespace conv_float_relaxed
+TEST_F(GeneratedTests, conv_float_relaxed) {
+    execute(conv_float_relaxed::CreateModel,
+            conv_float_relaxed::is_ignored,
+            conv_float_relaxed::examples);
+}
+
+namespace conv_float_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_float_weights_as_inputs_relaxed test
+#include "generated/examples/conv_float_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/conv_float_weights_as_inputs_relaxed.model.cpp"
+} // namespace conv_float_weights_as_inputs_relaxed
+TEST_F(GeneratedTests, conv_float_weights_as_inputs_relaxed) {
+    execute(conv_float_weights_as_inputs_relaxed::CreateModel,
+            conv_float_weights_as_inputs_relaxed::is_ignored,
+            conv_float_weights_as_inputs_relaxed::examples);
+}
+
+namespace depth_to_space_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depth_to_space_float_1_relaxed test
+#include "generated/examples/depth_to_space_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/depth_to_space_float_1_relaxed.model.cpp"
+} // namespace depth_to_space_float_1_relaxed
+TEST_F(GeneratedTests, depth_to_space_float_1_relaxed) {
+    execute(depth_to_space_float_1_relaxed::CreateModel,
+            depth_to_space_float_1_relaxed::is_ignored,
+            depth_to_space_float_1_relaxed::examples);
+}
+
+namespace depth_to_space_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depth_to_space_float_2_relaxed test
+#include "generated/examples/depth_to_space_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/depth_to_space_float_2_relaxed.model.cpp"
+} // namespace depth_to_space_float_2_relaxed
+TEST_F(GeneratedTests, depth_to_space_float_2_relaxed) {
+    execute(depth_to_space_float_2_relaxed::CreateModel,
+            depth_to_space_float_2_relaxed::is_ignored,
+            depth_to_space_float_2_relaxed::examples);
+}
+
+namespace depth_to_space_float_3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depth_to_space_float_3_relaxed test
+#include "generated/examples/depth_to_space_float_3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/depth_to_space_float_3_relaxed.model.cpp"
+} // namespace depth_to_space_float_3_relaxed
+TEST_F(GeneratedTests, depth_to_space_float_3_relaxed) {
+    execute(depth_to_space_float_3_relaxed::CreateModel,
+            depth_to_space_float_3_relaxed::is_ignored,
+            depth_to_space_float_3_relaxed::examples);
+}
+
+namespace depthwise_conv2d_float_large_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depthwise_conv2d_float_large_relaxed test
+#include "generated/examples/depthwise_conv2d_float_large_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/depthwise_conv2d_float_large_relaxed.model.cpp"
+} // namespace depthwise_conv2d_float_large_relaxed
+TEST_F(GeneratedTests, depthwise_conv2d_float_large_relaxed) {
+    execute(depthwise_conv2d_float_large_relaxed::CreateModel,
+            depthwise_conv2d_float_large_relaxed::is_ignored,
+            depthwise_conv2d_float_large_relaxed::examples);
+}
+
+namespace depthwise_conv2d_float_large_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depthwise_conv2d_float_large_weights_as_inputs_relaxed test
+#include "generated/examples/depthwise_conv2d_float_large_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/depthwise_conv2d_float_large_weights_as_inputs_relaxed.model.cpp"
+} // namespace depthwise_conv2d_float_large_weights_as_inputs_relaxed
+TEST_F(GeneratedTests, depthwise_conv2d_float_large_weights_as_inputs_relaxed) {
+    execute(depthwise_conv2d_float_large_weights_as_inputs_relaxed::CreateModel,
+            depthwise_conv2d_float_large_weights_as_inputs_relaxed::is_ignored,
+            depthwise_conv2d_float_large_weights_as_inputs_relaxed::examples);
+}
+
+namespace depthwise_conv_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depthwise_conv_relaxed test
+#include "generated/examples/depthwise_conv_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/depthwise_conv_relaxed.model.cpp"
+} // namespace depthwise_conv_relaxed
+TEST_F(GeneratedTests, depthwise_conv_relaxed) {
+    execute(depthwise_conv_relaxed::CreateModel,
+            depthwise_conv_relaxed::is_ignored,
+            depthwise_conv_relaxed::examples);
+}
+
 namespace div {
 std::vector<MixedTypedExample> examples = {
 // Generated div test
@@ -1919,6 +2255,426 @@
             div::examples);
 }
 
+namespace embedding_lookup_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated embedding_lookup_relaxed test
+#include "generated/examples/embedding_lookup_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/embedding_lookup_relaxed.model.cpp"
+} // namespace embedding_lookup_relaxed
+TEST_F(GeneratedTests, embedding_lookup_relaxed) {
+    execute(embedding_lookup_relaxed::CreateModel,
+            embedding_lookup_relaxed::is_ignored,
+            embedding_lookup_relaxed::examples);
+}
+
+namespace floor_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated floor_relaxed test
+#include "generated/examples/floor_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/floor_relaxed.model.cpp"
+} // namespace floor_relaxed
+TEST_F(GeneratedTests, floor_relaxed) {
+    execute(floor_relaxed::CreateModel,
+            floor_relaxed::is_ignored,
+            floor_relaxed::examples);
+}
+
+namespace fully_connected_float_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated fully_connected_float_relaxed test
+#include "generated/examples/fully_connected_float_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/fully_connected_float_relaxed.model.cpp"
+} // namespace fully_connected_float_relaxed
+TEST_F(GeneratedTests, fully_connected_float_relaxed) {
+    execute(fully_connected_float_relaxed::CreateModel,
+            fully_connected_float_relaxed::is_ignored,
+            fully_connected_float_relaxed::examples);
+}
+
+namespace fully_connected_float_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated fully_connected_float_weights_as_inputs_relaxed test
+#include "generated/examples/fully_connected_float_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/fully_connected_float_weights_as_inputs_relaxed.model.cpp"
+} // namespace fully_connected_float_weights_as_inputs_relaxed
+TEST_F(GeneratedTests, fully_connected_float_weights_as_inputs_relaxed) {
+    execute(fully_connected_float_weights_as_inputs_relaxed::CreateModel,
+            fully_connected_float_weights_as_inputs_relaxed::is_ignored,
+            fully_connected_float_weights_as_inputs_relaxed::examples);
+}
+
+namespace hashtable_lookup_float_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated hashtable_lookup_float_relaxed test
+#include "generated/examples/hashtable_lookup_float_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/hashtable_lookup_float_relaxed.model.cpp"
+} // namespace hashtable_lookup_float_relaxed
+TEST_F(GeneratedTests, hashtable_lookup_float_relaxed) {
+    execute(hashtable_lookup_float_relaxed::CreateModel,
+            hashtable_lookup_float_relaxed::is_ignored,
+            hashtable_lookup_float_relaxed::examples);
+}
+
+namespace l2_normalization_large_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated l2_normalization_large_relaxed test
+#include "generated/examples/l2_normalization_large_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/l2_normalization_large_relaxed.model.cpp"
+} // namespace l2_normalization_large_relaxed
+TEST_F(GeneratedTests, l2_normalization_large_relaxed) {
+    execute(l2_normalization_large_relaxed::CreateModel,
+            l2_normalization_large_relaxed::is_ignored,
+            l2_normalization_large_relaxed::examples);
+}
+
+namespace l2_normalization_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated l2_normalization_relaxed test
+#include "generated/examples/l2_normalization_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/l2_normalization_relaxed.model.cpp"
+} // namespace l2_normalization_relaxed
+TEST_F(GeneratedTests, l2_normalization_relaxed) {
+    execute(l2_normalization_relaxed::CreateModel,
+            l2_normalization_relaxed::is_ignored,
+            l2_normalization_relaxed::examples);
+}
+
+namespace l2_pool_float_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated l2_pool_float_relaxed test
+#include "generated/examples/l2_pool_float_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/l2_pool_float_relaxed.model.cpp"
+} // namespace l2_pool_float_relaxed
+TEST_F(GeneratedTests, l2_pool_float_relaxed) {
+    execute(l2_pool_float_relaxed::CreateModel,
+            l2_pool_float_relaxed::is_ignored,
+            l2_pool_float_relaxed::examples);
+}
+
+namespace local_response_norm_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated local_response_norm_float_1_relaxed test
+#include "generated/examples/local_response_norm_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/local_response_norm_float_1_relaxed.model.cpp"
+} // namespace local_response_norm_float_1_relaxed
+TEST_F(GeneratedTests, local_response_norm_float_1_relaxed) {
+    execute(local_response_norm_float_1_relaxed::CreateModel,
+            local_response_norm_float_1_relaxed::is_ignored,
+            local_response_norm_float_1_relaxed::examples);
+}
+
+namespace local_response_norm_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated local_response_norm_float_2_relaxed test
+#include "generated/examples/local_response_norm_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/local_response_norm_float_2_relaxed.model.cpp"
+} // namespace local_response_norm_float_2_relaxed
+TEST_F(GeneratedTests, local_response_norm_float_2_relaxed) {
+    execute(local_response_norm_float_2_relaxed::CreateModel,
+            local_response_norm_float_2_relaxed::is_ignored,
+            local_response_norm_float_2_relaxed::examples);
+}
+
+namespace local_response_norm_float_3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated local_response_norm_float_3_relaxed test
+#include "generated/examples/local_response_norm_float_3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/local_response_norm_float_3_relaxed.model.cpp"
+} // namespace local_response_norm_float_3_relaxed
+TEST_F(GeneratedTests, local_response_norm_float_3_relaxed) {
+    execute(local_response_norm_float_3_relaxed::CreateModel,
+            local_response_norm_float_3_relaxed::is_ignored,
+            local_response_norm_float_3_relaxed::examples);
+}
+
+namespace local_response_norm_float_4_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated local_response_norm_float_4_relaxed test
+#include "generated/examples/local_response_norm_float_4_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/local_response_norm_float_4_relaxed.model.cpp"
+} // namespace local_response_norm_float_4_relaxed
+TEST_F(GeneratedTests, local_response_norm_float_4_relaxed) {
+    execute(local_response_norm_float_4_relaxed::CreateModel,
+            local_response_norm_float_4_relaxed::is_ignored,
+            local_response_norm_float_4_relaxed::examples);
+}
+
+namespace logistic_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated logistic_float_1_relaxed test
+#include "generated/examples/logistic_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/logistic_float_1_relaxed.model.cpp"
+} // namespace logistic_float_1_relaxed
+TEST_F(GeneratedTests, logistic_float_1_relaxed) {
+    execute(logistic_float_1_relaxed::CreateModel,
+            logistic_float_1_relaxed::is_ignored,
+            logistic_float_1_relaxed::examples);
+}
+
+namespace logistic_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated logistic_float_2_relaxed test
+#include "generated/examples/logistic_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/logistic_float_2_relaxed.model.cpp"
+} // namespace logistic_float_2_relaxed
+TEST_F(GeneratedTests, logistic_float_2_relaxed) {
+    execute(logistic_float_2_relaxed::CreateModel,
+            logistic_float_2_relaxed::is_ignored,
+            logistic_float_2_relaxed::examples);
+}
+
+namespace lsh_projection_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lsh_projection_2_relaxed test
+#include "generated/examples/lsh_projection_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/lsh_projection_2_relaxed.model.cpp"
+} // namespace lsh_projection_2_relaxed
+TEST_F(GeneratedTests, lsh_projection_2_relaxed) {
+    execute(lsh_projection_2_relaxed::CreateModel,
+            lsh_projection_2_relaxed::is_ignored,
+            lsh_projection_2_relaxed::examples);
+}
+
+namespace lsh_projection_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lsh_projection_relaxed test
+#include "generated/examples/lsh_projection_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/lsh_projection_relaxed.model.cpp"
+} // namespace lsh_projection_relaxed
+TEST_F(GeneratedTests, lsh_projection_relaxed) {
+    execute(lsh_projection_relaxed::CreateModel,
+            lsh_projection_relaxed::is_ignored,
+            lsh_projection_relaxed::examples);
+}
+
+namespace lsh_projection_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lsh_projection_weights_as_inputs_relaxed test
+#include "generated/examples/lsh_projection_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/lsh_projection_weights_as_inputs_relaxed.model.cpp"
+} // namespace lsh_projection_weights_as_inputs_relaxed
+TEST_F(GeneratedTests, lsh_projection_weights_as_inputs_relaxed) {
+    execute(lsh_projection_weights_as_inputs_relaxed::CreateModel,
+            lsh_projection_weights_as_inputs_relaxed::is_ignored,
+            lsh_projection_weights_as_inputs_relaxed::examples);
+}
+
+namespace lstm2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm2_relaxed test
+#include "generated/examples/lstm2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/lstm2_relaxed.model.cpp"
+} // namespace lstm2_relaxed
+TEST_F(GeneratedTests, lstm2_relaxed) {
+    execute(lstm2_relaxed::CreateModel,
+            lstm2_relaxed::is_ignored,
+            lstm2_relaxed::examples);
+}
+
+namespace lstm2_state2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm2_state2_relaxed test
+#include "generated/examples/lstm2_state2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/lstm2_state2_relaxed.model.cpp"
+} // namespace lstm2_state2_relaxed
+TEST_F(GeneratedTests, lstm2_state2_relaxed) {
+    execute(lstm2_state2_relaxed::CreateModel,
+            lstm2_state2_relaxed::is_ignored,
+            lstm2_state2_relaxed::examples);
+}
+
+namespace lstm2_state_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm2_state_relaxed test
+#include "generated/examples/lstm2_state_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/lstm2_state_relaxed.model.cpp"
+} // namespace lstm2_state_relaxed
+TEST_F(GeneratedTests, lstm2_state_relaxed) {
+    execute(lstm2_state_relaxed::CreateModel,
+            lstm2_state_relaxed::is_ignored,
+            lstm2_state_relaxed::examples);
+}
+
+namespace lstm3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm3_relaxed test
+#include "generated/examples/lstm3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/lstm3_relaxed.model.cpp"
+} // namespace lstm3_relaxed
+TEST_F(GeneratedTests, lstm3_relaxed) {
+    execute(lstm3_relaxed::CreateModel,
+            lstm3_relaxed::is_ignored,
+            lstm3_relaxed::examples);
+}
+
+namespace lstm3_state2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm3_state2_relaxed test
+#include "generated/examples/lstm3_state2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/lstm3_state2_relaxed.model.cpp"
+} // namespace lstm3_state2_relaxed
+TEST_F(GeneratedTests, lstm3_state2_relaxed) {
+    execute(lstm3_state2_relaxed::CreateModel,
+            lstm3_state2_relaxed::is_ignored,
+            lstm3_state2_relaxed::examples);
+}
+
+namespace lstm3_state3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm3_state3_relaxed test
+#include "generated/examples/lstm3_state3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/lstm3_state3_relaxed.model.cpp"
+} // namespace lstm3_state3_relaxed
+TEST_F(GeneratedTests, lstm3_state3_relaxed) {
+    execute(lstm3_state3_relaxed::CreateModel,
+            lstm3_state3_relaxed::is_ignored,
+            lstm3_state3_relaxed::examples);
+}
+
+namespace lstm3_state_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm3_state_relaxed test
+#include "generated/examples/lstm3_state_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/lstm3_state_relaxed.model.cpp"
+} // namespace lstm3_state_relaxed
+TEST_F(GeneratedTests, lstm3_state_relaxed) {
+    execute(lstm3_state_relaxed::CreateModel,
+            lstm3_state_relaxed::is_ignored,
+            lstm3_state_relaxed::examples);
+}
+
+namespace lstm_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm_relaxed test
+#include "generated/examples/lstm_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/lstm_relaxed.model.cpp"
+} // namespace lstm_relaxed
+TEST_F(GeneratedTests, lstm_relaxed) {
+    execute(lstm_relaxed::CreateModel,
+            lstm_relaxed::is_ignored,
+            lstm_relaxed::examples);
+}
+
+namespace lstm_state2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm_state2_relaxed test
+#include "generated/examples/lstm_state2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/lstm_state2_relaxed.model.cpp"
+} // namespace lstm_state2_relaxed
+TEST_F(GeneratedTests, lstm_state2_relaxed) {
+    execute(lstm_state2_relaxed::CreateModel,
+            lstm_state2_relaxed::is_ignored,
+            lstm_state2_relaxed::examples);
+}
+
+namespace lstm_state_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated lstm_state_relaxed test
+#include "generated/examples/lstm_state_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/lstm_state_relaxed.model.cpp"
+} // namespace lstm_state_relaxed
+TEST_F(GeneratedTests, lstm_state_relaxed) {
+    execute(lstm_state_relaxed::CreateModel,
+            lstm_state_relaxed::is_ignored,
+            lstm_state_relaxed::examples);
+}
+
+namespace max_pool_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated max_pool_float_1_relaxed test
+#include "generated/examples/max_pool_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/max_pool_float_1_relaxed.model.cpp"
+} // namespace max_pool_float_1_relaxed
+TEST_F(GeneratedTests, max_pool_float_1_relaxed) {
+    execute(max_pool_float_1_relaxed::CreateModel,
+            max_pool_float_1_relaxed::is_ignored,
+            max_pool_float_1_relaxed::examples);
+}
+
+namespace max_pool_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated max_pool_float_2_relaxed test
+#include "generated/examples/max_pool_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/max_pool_float_2_relaxed.model.cpp"
+} // namespace max_pool_float_2_relaxed
+TEST_F(GeneratedTests, max_pool_float_2_relaxed) {
+    execute(max_pool_float_2_relaxed::CreateModel,
+            max_pool_float_2_relaxed::is_ignored,
+            max_pool_float_2_relaxed::examples);
+}
+
+namespace max_pool_float_3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated max_pool_float_3_relaxed test
+#include "generated/examples/max_pool_float_3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/max_pool_float_3_relaxed.model.cpp"
+} // namespace max_pool_float_3_relaxed
+TEST_F(GeneratedTests, max_pool_float_3_relaxed) {
+    execute(max_pool_float_3_relaxed::CreateModel,
+            max_pool_float_3_relaxed::is_ignored,
+            max_pool_float_3_relaxed::examples);
+}
+
 namespace mean_float_1 {
 std::vector<MixedTypedExample> examples = {
 // Generated mean_float_1 test
@@ -1961,6 +2717,48 @@
             mean::examples);
 }
 
+namespace mobilenet_224_gender_basic_fixed_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated mobilenet_224_gender_basic_fixed_relaxed test
+#include "generated/examples/mobilenet_224_gender_basic_fixed_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/mobilenet_224_gender_basic_fixed_relaxed.model.cpp"
+} // namespace mobilenet_224_gender_basic_fixed_relaxed
+TEST_F(GeneratedTests, mobilenet_224_gender_basic_fixed_relaxed) {
+    execute(mobilenet_224_gender_basic_fixed_relaxed::CreateModel,
+            mobilenet_224_gender_basic_fixed_relaxed::is_ignored,
+            mobilenet_224_gender_basic_fixed_relaxed::examples);
+}
+
+namespace mul_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated mul_relaxed test
+#include "generated/examples/mul_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/mul_relaxed.model.cpp"
+} // namespace mul_relaxed
+TEST_F(GeneratedTests, mul_relaxed) {
+    execute(mul_relaxed::CreateModel,
+            mul_relaxed::is_ignored,
+            mul_relaxed::examples);
+}
+
+namespace mul_relu_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated mul_relu_relaxed test
+#include "generated/examples/mul_relu_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/mul_relu_relaxed.model.cpp"
+} // namespace mul_relu_relaxed
+TEST_F(GeneratedTests, mul_relu_relaxed) {
+    execute(mul_relu_relaxed::CreateModel,
+            mul_relu_relaxed::is_ignored,
+            mul_relu_relaxed::examples);
+}
+
 namespace pad_float_1 {
 std::vector<MixedTypedExample> examples = {
 // Generated pad_float_1 test
@@ -1989,6 +2787,174 @@
             pad::examples);
 }
 
+namespace relu1_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated relu1_float_1_relaxed test
+#include "generated/examples/relu1_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/relu1_float_1_relaxed.model.cpp"
+} // namespace relu1_float_1_relaxed
+TEST_F(GeneratedTests, relu1_float_1_relaxed) {
+    execute(relu1_float_1_relaxed::CreateModel,
+            relu1_float_1_relaxed::is_ignored,
+            relu1_float_1_relaxed::examples);
+}
+
+namespace relu1_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated relu1_float_2_relaxed test
+#include "generated/examples/relu1_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/relu1_float_2_relaxed.model.cpp"
+} // namespace relu1_float_2_relaxed
+TEST_F(GeneratedTests, relu1_float_2_relaxed) {
+    execute(relu1_float_2_relaxed::CreateModel,
+            relu1_float_2_relaxed::is_ignored,
+            relu1_float_2_relaxed::examples);
+}
+
+namespace relu6_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated relu6_float_1_relaxed test
+#include "generated/examples/relu6_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/relu6_float_1_relaxed.model.cpp"
+} // namespace relu6_float_1_relaxed
+TEST_F(GeneratedTests, relu6_float_1_relaxed) {
+    execute(relu6_float_1_relaxed::CreateModel,
+            relu6_float_1_relaxed::is_ignored,
+            relu6_float_1_relaxed::examples);
+}
+
+namespace relu6_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated relu6_float_2_relaxed test
+#include "generated/examples/relu6_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/relu6_float_2_relaxed.model.cpp"
+} // namespace relu6_float_2_relaxed
+TEST_F(GeneratedTests, relu6_float_2_relaxed) {
+    execute(relu6_float_2_relaxed::CreateModel,
+            relu6_float_2_relaxed::is_ignored,
+            relu6_float_2_relaxed::examples);
+}
+
+namespace relu_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated relu_float_1_relaxed test
+#include "generated/examples/relu_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/relu_float_1_relaxed.model.cpp"
+} // namespace relu_float_1_relaxed
+TEST_F(GeneratedTests, relu_float_1_relaxed) {
+    execute(relu_float_1_relaxed::CreateModel,
+            relu_float_1_relaxed::is_ignored,
+            relu_float_1_relaxed::examples);
+}
+
+namespace reshape_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated reshape_relaxed test
+#include "generated/examples/reshape_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/reshape_relaxed.model.cpp"
+} // namespace reshape_relaxed
+TEST_F(GeneratedTests, reshape_relaxed) {
+    execute(reshape_relaxed::CreateModel,
+            reshape_relaxed::is_ignored,
+            reshape_relaxed::examples);
+}
+
+namespace reshape_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated reshape_weights_as_inputs_relaxed test
+#include "generated/examples/reshape_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/reshape_weights_as_inputs_relaxed.model.cpp"
+} // namespace reshape_weights_as_inputs_relaxed
+TEST_F(GeneratedTests, reshape_weights_as_inputs_relaxed) {
+    execute(reshape_weights_as_inputs_relaxed::CreateModel,
+            reshape_weights_as_inputs_relaxed::is_ignored,
+            reshape_weights_as_inputs_relaxed::examples);
+}
+
+namespace resize_bilinear_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated resize_bilinear_relaxed test
+#include "generated/examples/resize_bilinear_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/resize_bilinear_relaxed.model.cpp"
+} // namespace resize_bilinear_relaxed
+TEST_F(GeneratedTests, resize_bilinear_relaxed) {
+    execute(resize_bilinear_relaxed::CreateModel,
+            resize_bilinear_relaxed::is_ignored,
+            resize_bilinear_relaxed::examples);
+}
+
+namespace rnn_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated rnn_relaxed test
+#include "generated/examples/rnn_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/rnn_relaxed.model.cpp"
+} // namespace rnn_relaxed
+TEST_F(GeneratedTests, rnn_relaxed) {
+    execute(rnn_relaxed::CreateModel,
+            rnn_relaxed::is_ignored,
+            rnn_relaxed::examples);
+}
+
+namespace rnn_state_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated rnn_state_relaxed test
+#include "generated/examples/rnn_state_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/rnn_state_relaxed.model.cpp"
+} // namespace rnn_state_relaxed
+TEST_F(GeneratedTests, rnn_state_relaxed) {
+    execute(rnn_state_relaxed::CreateModel,
+            rnn_state_relaxed::is_ignored,
+            rnn_state_relaxed::examples);
+}
+
+namespace softmax_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated softmax_float_1_relaxed test
+#include "generated/examples/softmax_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/softmax_float_1_relaxed.model.cpp"
+} // namespace softmax_float_1_relaxed
+TEST_F(GeneratedTests, softmax_float_1_relaxed) {
+    execute(softmax_float_1_relaxed::CreateModel,
+            softmax_float_1_relaxed::is_ignored,
+            softmax_float_1_relaxed::examples);
+}
+
+namespace softmax_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated softmax_float_2_relaxed test
+#include "generated/examples/softmax_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/softmax_float_2_relaxed.model.cpp"
+} // namespace softmax_float_2_relaxed
+TEST_F(GeneratedTests, softmax_float_2_relaxed) {
+    execute(softmax_float_2_relaxed::CreateModel,
+            softmax_float_2_relaxed::is_ignored,
+            softmax_float_2_relaxed::examples);
+}
+
 namespace space_to_batch_float_1 {
 std::vector<MixedTypedExample> examples = {
 // Generated space_to_batch_float_1 test
@@ -2087,6 +3053,48 @@
             space_to_batch_quant8_3::examples);
 }
 
+namespace space_to_depth_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated space_to_depth_float_1_relaxed test
+#include "generated/examples/space_to_depth_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/space_to_depth_float_1_relaxed.model.cpp"
+} // namespace space_to_depth_float_1_relaxed
+TEST_F(GeneratedTests, space_to_depth_float_1_relaxed) {
+    execute(space_to_depth_float_1_relaxed::CreateModel,
+            space_to_depth_float_1_relaxed::is_ignored,
+            space_to_depth_float_1_relaxed::examples);
+}
+
+namespace space_to_depth_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated space_to_depth_float_2_relaxed test
+#include "generated/examples/space_to_depth_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/space_to_depth_float_2_relaxed.model.cpp"
+} // namespace space_to_depth_float_2_relaxed
+TEST_F(GeneratedTests, space_to_depth_float_2_relaxed) {
+    execute(space_to_depth_float_2_relaxed::CreateModel,
+            space_to_depth_float_2_relaxed::is_ignored,
+            space_to_depth_float_2_relaxed::examples);
+}
+
+namespace space_to_depth_float_3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated space_to_depth_float_3_relaxed test
+#include "generated/examples/space_to_depth_float_3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/space_to_depth_float_3_relaxed.model.cpp"
+} // namespace space_to_depth_float_3_relaxed
+TEST_F(GeneratedTests, space_to_depth_float_3_relaxed) {
+    execute(space_to_depth_float_3_relaxed::CreateModel,
+            space_to_depth_float_3_relaxed::is_ignored,
+            space_to_depth_float_3_relaxed::examples);
+}
+
 namespace squeeze_float_1 {
 std::vector<MixedTypedExample> examples = {
 // Generated squeeze_float_1 test
@@ -2437,6 +3445,62 @@
             sub::examples);
 }
 
+namespace svdf2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated svdf2_relaxed test
+#include "generated/examples/svdf2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/svdf2_relaxed.model.cpp"
+} // namespace svdf2_relaxed
+TEST_F(GeneratedTests, svdf2_relaxed) {
+    execute(svdf2_relaxed::CreateModel,
+            svdf2_relaxed::is_ignored,
+            svdf2_relaxed::examples);
+}
+
+namespace svdf_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated svdf_relaxed test
+#include "generated/examples/svdf_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/svdf_relaxed.model.cpp"
+} // namespace svdf_relaxed
+TEST_F(GeneratedTests, svdf_relaxed) {
+    execute(svdf_relaxed::CreateModel,
+            svdf_relaxed::is_ignored,
+            svdf_relaxed::examples);
+}
+
+namespace svdf_state_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated svdf_state_relaxed test
+#include "generated/examples/svdf_state_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/svdf_state_relaxed.model.cpp"
+} // namespace svdf_state_relaxed
+TEST_F(GeneratedTests, svdf_state_relaxed) {
+    execute(svdf_state_relaxed::CreateModel,
+            svdf_state_relaxed::is_ignored,
+            svdf_state_relaxed::examples);
+}
+
+namespace tanh_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated tanh_relaxed test
+#include "generated/examples/tanh_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/tanh_relaxed.model.cpp"
+} // namespace tanh_relaxed
+TEST_F(GeneratedTests, tanh_relaxed) {
+    execute(tanh_relaxed::CreateModel,
+            tanh_relaxed::is_ignored,
+            tanh_relaxed::examples);
+}
+
 namespace transpose_float_1 {
 std::vector<MixedTypedExample> examples = {
 // Generated transpose_float_1 test
diff --git a/nn/runtime/test/generated/examples/add_relaxed.example.cpp b/nn/runtime/test/generated/examples/add_relaxed.example.cpp
new file mode 100644
index 0000000..ad63c3b
--- /dev/null
+++ b/nn/runtime/test/generated/examples/add_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: add_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f}}, {1, {3.0f, 4.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {4.0f, 6.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/avg_pool_float_1_relaxed.example.cpp b/nn/runtime/test/generated/examples/avg_pool_float_1_relaxed.example.cpp
new file mode 100644
index 0000000..13418a9
--- /dev/null
+++ b/nn/runtime/test/generated/examples/avg_pool_float_1_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: avg_pool_float_1_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/avg_pool_float_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/avg_pool_float_2_relaxed.example.cpp
new file mode 100644
index 0000000..9e6ede3
--- /dev/null
+++ b/nn/runtime/test/generated/examples/avg_pool_float_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: avg_pool_float_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 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+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 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+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/avg_pool_float_3_relaxed.example.cpp b/nn/runtime/test/generated/examples/avg_pool_float_3_relaxed.example.cpp
new file mode 100644
index 0000000..851e5d0
--- /dev/null
+++ b/nn/runtime/test/generated/examples/avg_pool_float_3_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: avg_pool_float_3_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 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+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 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+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/avg_pool_float_4_relaxed.example.cpp b/nn/runtime/test/generated/examples/avg_pool_float_4_relaxed.example.cpp
new file mode 100644
index 0000000..ae179c4
--- /dev/null
+++ b/nn/runtime/test/generated/examples/avg_pool_float_4_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: avg_pool_float_4_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
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10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/concat_float_1_relaxed.example.cpp b/nn/runtime/test/generated/examples/concat_float_1_relaxed.example.cpp
new file mode 100644
index 0000000..82e046b
--- /dev/null
+++ b/nn/runtime/test/generated/examples/concat_float_1_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: concat_float_1_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}}, {1, {7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/concat_float_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/concat_float_2_relaxed.example.cpp
new file mode 100644
index 0000000..c4acbcb
--- /dev/null
+++ b/nn/runtime/test/generated/examples/concat_float_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: concat_float_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519, 520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532, 533, 534, 535, 536, 537, 538, 539, 540, 541, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558, 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 578, 579, 580, 581, 582, 583, 584, 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 757, 758, 759, 760, 761, 762, 763, 764, 765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 778, 779, 780, 781, 782, 783, 784, 785, 786, 787, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 884, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959, 960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019, 1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039, 1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055, 1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1093, 1094, 1095, 1096, 1097, 1098, 1099, 1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1112, 1113, 1114, 1115, 1116, 1117, 1118, 1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1148, 1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1159, 1160, 1161, 1162, 1163, 1164, 1165, 1166, 1167, 1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1177, 1178, 1179, 1180, 1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255, 1256, 1257, 1258, 1259, 1260, 1261, 1262, 1263, 1264, 1265, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275, 1276, 1277, 1278, 1279, 1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291, 1292, 1293, 1294, 1295, 1296, 1297, 1298, 1299, 1300, 1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1313, 1314, 1315, 1316, 1317, 1318, 1319, 1320, 1321, 1322, 1323, 1324, 1325, 1326, 1327, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1341, 1342, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1350, 1351, 1352, 1353, 1354, 1355, 1356, 1357, 1358, 1359, 1360, 1361, 1362, 1363, 1364, 1365, 1366, 1367, 1368, 1369, 1370, 1371, 1372, 1373, 1374, 1375, 1376, 1377, 1378, 1379, 1380, 1381, 1382, 1383, 1384, 1385, 1386, 1387, 1388, 1389, 1390, 1391, 1392, 1393, 1394, 1395, 1396, 1397, 1398, 1399, 1400, 1401, 1402, 1403, 1404, 1405, 1406, 1407, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1415, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426, 1427, 1428, 1429, 1430, 1431, 1432, 1433, 1434, 1435, 1436, 1437, 1438, 1439, 1440, 1441, 1442, 1443, 1444, 1445, 1446, 1447, 1448, 1449, 1450, 1451, 1452, 1453, 1454, 1455, 1456, 1457, 1458, 1459, 1460, 1461, 1462, 1463, 1464, 1465, 1466, 1467, 1468, 1469, 1470, 1471, 1472, 1473, 1474, 1475, 1476, 1477, 1478, 1479, 1480, 1481, 1482, 1483, 1484, 1485, 1486, 1487, 1488, 1489, 1490, 1491, 1492, 1493, 1494, 1495, 1496, 1497, 1498, 1499, 1500, 1501, 1502, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510, 1511, 1512, 1513, 1514, 1515, 1516, 1517, 1518, 1519, 1520, 1521, 1522, 1523, 1524, 1525, 1526, 1527, 1528, 1529, 1530, 1531, 1532, 1533, 1534, 1535, 1536, 1537, 1538, 1539, 1540, 1541, 1542, 1543, 1544, 1545, 1546, 1547, 1548, 1549, 1550, 1551, 1552, 1553, 1554, 1555, 1556, 1557, 1558, 1559, 1560, 1561, 1562, 1563, 1564, 1565, 1566, 1567, 1568, 1569, 1570, 1571, 1572, 1573, 1574, 1575, 1576, 1577, 1578, 1579, 1580, 1581, 1582, 1583, 1584, 1585, 1586, 1587, 1588, 1589, 1590, 1591, 1592, 1593, 1594, 1595, 1596, 1597, 1598, 1599, 1600, 1601, 1602, 1603, 1604, 1605, 1606, 1607, 1608, 1609, 1610, 1611, 1612, 1613, 1614, 1615, 1616, 1617, 1618, 1619, 1620, 1621, 1622, 1623, 1624, 1625, 1626, 1627, 1628, 1629, 1630, 1631, 1632, 1633, 1634, 1635, 1636, 1637, 1638, 1639, 1640, 1641, 1642, 1643, 1644, 1645, 1646, 1647, 1648, 1649, 1650, 1651, 1652, 1653, 1654, 1655, 1656, 1657, 1658, 1659, 1660, 1661, 1662, 1663, 1664, 1665, 1666, 1667, 1668, 1669, 1670, 1671, 1672, 1673, 1674, 1675, 1676, 1677, 1678, 1679, 1680, 1681, 1682, 1683, 1684, 1685, 1686, 1687, 1688, 1689, 1690, 1691, 1692, 1693, 1694, 1695, 1696, 1697, 1698, 1699, 1700, 1701, 1702, 1703, 1704, 1705, 1706, 1707, 1708, 1709, 1710, 1711, 1712, 1713, 1714, 1715, 1716, 1717, 1718, 1719, 1720, 1721, 1722, 1723, 1724, 1725, 1726, 1727, 1728, 1729, 1730, 1731, 1732, 1733, 1734, 1735, 1736, 1737, 1738, 1739, 1740, 1741, 1742, 1743, 1744, 1745, 1746, 1747, 1748, 1749, 1750, 1751, 1752, 1753, 1754, 1755, 1756, 1757, 1758, 1759, 1760, 1761, 1762, 1763, 1764, 1765, 1766, 1767, 1768, 1769, 1770, 1771, 1772, 1773, 1774, 1775, 1776, 1777, 1778, 1779, 1780, 1781, 1782, 1783, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1792, 1793, 1794, 1795, 1796, 1797, 1798, 1799, 1800, 1801, 1802, 1803, 1804, 1805, 1806, 1807, 1808, 1809, 1810, 1811, 1812, 1813, 1814, 1815, 1816, 1817, 1818, 1819, 1820, 1821, 1822, 1823, 1824, 1825, 1826, 1827, 1828, 1829, 1830, 1831, 1832, 1833, 1834, 1835, 1836, 1837, 1838, 1839, 1840, 1841, 1842, 1843, 1844, 1845, 1846, 1847, 1848, 1849, 1850, 1851, 1852, 1853, 1854, 1855, 1856, 1857, 1858, 1859, 1860, 1861, 1862, 1863, 1864, 1865, 1866, 1867, 1868, 1869, 1870, 1871, 1872, 1873, 1874, 1875, 1876, 1877, 1878, 1879, 1880, 1881, 1882, 1883, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 1895, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024, 2025, 2026, 2027, 2028, 2029, 2030, 2031, 2032, 2033, 2034, 2035, 2036, 2037, 2038, 2039, 2040, 2041, 2042, 2043, 2044, 2045, 2046, 2047, 2048, 2049, 2050, 2051, 2052, 2053, 2054, 2055, 2056, 2057, 2058, 2059, 2060, 2061, 2062, 2063, 2064, 2065, 2066, 2067, 2068, 2069, 2070, 2071, 2072, 2073, 2074, 2075, 2076, 2077, 2078, 2079, 2080, 2081, 2082, 2083, 2084, 2085, 2086, 2087, 2088, 2089, 2090, 2091, 2092, 2093, 2094, 2095, 2096, 2097, 2098, 2099, 2100, 2101, 2102, 2103, 2104, 2105, 2106, 2107, 2108, 2109, 2110, 2111, 2112, 2113, 2114, 2115, 2116, 2117, 2118, 2119, 2120, 2121, 2122, 2123, 2124, 2125, 2126, 2127, 2128, 2129, 2130, 2131, 2132, 2133, 2134, 2135, 2136, 2137, 2138, 2139, 2140, 2141, 2142, 2143, 2144, 2145, 2146, 2147, 2148, 2149, 2150, 2151, 2152, 2153, 2154, 2155, 2156, 2157, 2158, 2159, 2160, 2161, 2162, 2163, 2164, 2165, 2166, 2167, 2168, 2169, 2170, 2171, 2172, 2173, 2174, 2175, 2176, 2177, 2178, 2179, 2180, 2181, 2182, 2183, 2184, 2185, 2186, 2187, 2188, 2189, 2190, 2191, 2192, 2193, 2194, 2195, 2196, 2197, 2198, 2199, 2200, 2201, 2202, 2203, 2204, 2205, 2206, 2207, 2208, 2209, 2210, 2211, 2212, 2213, 2214, 2215, 2216, 2217, 2218, 2219, 2220, 2221, 2222, 2223, 2224, 2225, 2226, 2227, 2228, 2229, 2230, 2231, 2232, 2233, 2234, 2235, 2236, 2237, 2238, 2239, 2240, 2241, 2242, 2243, 2244, 2245, 2246, 2247, 2248, 2249, 2250, 2251, 2252, 2253, 2254, 2255, 2256, 2257, 2258, 2259, 2260, 2261, 2262, 2263, 2264, 2265, 2266, 2267, 2268, 2269, 2270, 2271, 2272, 2273, 2274, 2275, 2276, 2277, 2278, 2279, 2280, 2281, 2282, 2283, 2284, 2285, 2286, 2287, 2288, 2289, 2290, 2291, 2292, 2293, 2294, 2295, 2296, 2297, 2298, 2299, 2300, 2301, 2302, 2303, 2304, 2305, 2306, 2307, 2308, 2309, 2310, 2311, 2312, 2313, 2314, 2315, 2316, 2317, 2318, 2319, 2320, 2321, 2322, 2323, 2324, 2325, 2326, 2327, 2328, 2329, 2330, 2331, 2332, 2333, 2334, 2335, 2336, 2337, 2338, 2339, 2340, 2341, 2342, 2343, 2344, 2345, 2346, 2347, 2348, 2349, 2350, 2351, 2352, 2353, 2354, 2355, 2356, 2357, 2358, 2359, 2360, 2361, 2362, 2363, 2364, 2365, 2366, 2367, 2368, 2369, 2370, 2371, 2372, 2373, 2374, 2375, 2376, 2377, 2378, 2379, 2380, 2381, 2382, 2383, 2384, 2385, 2386, 2387, 2388, 2389, 2390, 2391, 2392, 2393, 2394, 2395, 2396, 2397, 2398, 2399, 2400, 2401, 2402, 2403, 2404, 2405, 2406, 2407, 2408, 2409, 2410, 2411, 2412, 2413, 2414, 2415, 2416, 2417, 2418, 2419, 2420, 2421, 2422, 2423, 2424, 2425, 2426, 2427, 2428, 2429, 2430, 2431, 2432, 2433, 2434, 2435, 2436, 2437, 2438, 2439, 2440, 2441, 2442, 2443, 2444, 2445, 2446, 2447, 2448, 2449, 2450, 2451, 2452, 2453, 2454, 2455, 2456, 2457, 2458, 2459, 2460, 2461, 2462, 2463, 2464, 2465, 2466, 2467, 2468, 2469, 2470, 2471, 2472, 2473, 2474, 2475, 2476, 2477, 2478, 2479, 2480, 2481, 2482, 2483, 2484, 2485, 2486, 2487, 2488, 2489, 2490, 2491, 2492, 2493, 2494, 2495, 2496, 2497, 2498, 2499, 2500, 2501, 2502, 2503, 2504, 2505, 2506, 2507, 2508, 2509, 2510, 2511, 2512, 2513, 2514, 2515, 2516, 2517, 2518, 2519, 2520, 2521, 2522, 2523, 2524, 2525, 2526, 2527, 2528, 2529, 2530, 2531, 2532, 2533, 2534, 2535, 2536, 2537, 2538, 2539, 2540, 2541, 2542, 2543, 2544, 2545, 2546, 2547, 2548, 2549, 2550, 2551, 2552, 2553, 2554, 2555, 2556, 2557, 2558, 2559, 2560, 2561, 2562, 2563, 2564, 2565, 2566, 2567, 2568, 2569, 2570, 2571, 2572, 2573, 2574, 2575, 2576, 2577, 2578, 2579, 2580, 2581, 2582, 2583, 2584, 2585, 2586, 2587, 2588, 2589, 2590, 2591, 2592, 2593, 2594, 2595, 2596, 2597, 2598, 2599, 2600, 2601, 2602, 2603, 2604, 2605, 2606, 2607, 2608, 2609, 2610, 2611, 2612, 2613, 2614, 2615, 2616, 2617, 2618, 2619, 2620, 2621, 2622, 2623, 2624, 2625, 2626, 2627, 2628, 2629, 2630, 2631, 2632, 2633, 2634, 2635, 2636, 2637, 2638, 2639, 2640, 2641, 2642, 2643, 2644, 2645, 2646, 2647, 2648, 2649, 2650, 2651, 2652, 2653, 2654, 2655, 2656, 2657, 2658, 2659, 2660, 2661, 2662, 2663, 2664, 2665, 2666, 2667, 2668, 2669, 2670, 2671, 2672, 2673, 2674, 2675, 2676, 2677, 2678, 2679, 2680, 2681, 2682, 2683, 2684, 2685, 2686, 2687, 2688, 2689, 2690, 2691, 2692, 2693, 2694, 2695, 2696, 2697, 2698, 2699, 2700, 2701, 2702, 2703, 2704, 2705, 2706, 2707, 2708, 2709, 2710, 2711, 2712, 2713, 2714, 2715, 2716, 2717, 2718, 2719, 2720, 2721, 2722, 2723, 2724, 2725, 2726, 2727, 2728, 2729, 2730, 2731, 2732, 2733, 2734, 2735, 2736, 2737, 2738, 2739, 2740, 2741, 2742, 2743, 2744, 2745, 2746, 2747, 2748, 2749, 2750, 2751, 2752, 2753, 2754, 2755, 2756, 2757, 2758, 2759, 2760, 2761, 2762, 2763, 2764, 2765, 2766, 2767, 2768, 2769, 2770, 2771, 2772, 2773, 2774, 2775, 2776, 2777, 2778, 2779, 2780, 2781, 2782, 2783, 2784, 2785, 2786, 2787, 2788, 2789, 2790, 2791, 2792, 2793, 2794, 2795, 2796, 2797, 2798, 2799, 2800, 2801, 2802, 2803, 2804, 2805, 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820, 2821, 2822, 2823, 2824, 2825, 2826, 2827, 2828, 2829, 2830, 2831, 2832, 2833, 2834, 2835, 2836, 2837, 2838, 2839, 2840, 2841, 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19419, 19420, 19421, 19422, 19423, 19424, 19425, 19426, 19427, 19428, 19429, 19430, 19431, 19432, 19433, 19434, 19435, 19436, 19437, 19438, 19439, 19440, 19441, 19442, 19443, 19444, 19445, 19446, 19447, 19448, 19449, 19450, 19451, 19452, 19453, 19454, 19455, 19456, 19457, 19458, 19459, 19460, 19461, 19462, 19463, 19464, 19465, 19466, 19467, 19468, 19469, 19470, 19471, 19472, 19473, 19474, 19475, 19476, 19477, 19478, 19479, 19480, 19481, 19482, 19483, 19484, 19485, 19486, 19487, 19488, 19489, 19490, 19491, 19492, 19493, 19494, 19495, 19496, 19497, 19498, 19499, 19500, 19501, 19502, 19503, 19504, 19505, 19506, 19507, 19508, 19509, 19510, 19511, 19512, 19513, 19514, 19515, 19516, 19517, 19518, 19519, 19520, 19521, 19522, 19523, 19524, 19525, 19526, 19527, 19528, 19529, 19530, 19531, 19532, 19533, 19534, 19535, 19536, 19537, 19538, 19539, 19540, 19541, 19542, 19543, 19544, 19545, 19546, 19547, 19548, 19549, 19550, 19551, 19552, 19553, 19554, 19555, 19556, 19557, 19558, 19559, 19560, 19561, 19562, 19563, 19564, 19565, 19566, 19567, 19568, 19569, 19570, 19571, 19572, 19573, 19574, 19575, 19576, 19577, 19578, 19579, 19580, 19581, 19582, 19583, 19584, 19585, 19586, 19587, 19588, 19589, 19590, 19591, 19592, 19593, 19594, 19595, 19596, 19597, 19598, 19599, 19600, 19601, 19602, 19603, 19604, 19605, 19606, 19607, 19608, 19609, 19610, 19611, 19612, 19613, 19614, 19615, 19616, 19617, 19618, 19619, 19620, 19621, 19622, 19623, 19624, 19625, 19626, 19627, 19628, 19629, 19630, 19631, 19632, 19633, 19634, 19635, 19636, 19637, 19638, 19639, 19640, 19641, 19642, 19643, 19644, 19645, 19646, 19647, 19648, 19649, 19650, 19651, 19652, 19653, 19654, 19655, 19656, 19657, 19658, 19659, 19660, 19661, 19662, 19663, 19664, 19665, 19666, 19667, 19668, 19669, 19670, 19671, 19672, 19673, 19674, 19675, 19676, 19677, 19678, 19679, 19680, 19681, 19682, 19683, 19684, 19685, 19686, 19687, 19688, 19689, 19690, 19691, 19692, 19693, 19694, 19695, 19696, 19697, 19698, 19699, 19700, 19701, 19702, 19703, 19704, 19705, 19706, 19707, 19708, 19709, 19710, 19711, 19712, 19713, 19714, 19715, 19716, 19717, 19718, 19719, 19720, 19721, 19722, 19723, 19724, 19725, 19726, 19727, 19728, 19729, 19730, 19731, 19732, 19733, 19734, 19735, 19736, 19737, 19738, 19739, 19740, 19741, 19742, 19743, 19744, 19745, 19746, 19747, 19748, 19749, 19750, 19751, 19752, 19753, 19754, 19755, 19756, 19757, 19758, 19759, 19760, 19761, 19762, 19763, 19764, 19765, 19766, 19767, 19768, 19769, 19770, 19771, 19772, 19773, 19774, 19775, 19776, 19777, 19778, 19779, 19780, 19781, 19782, 19783, 19784, 19785, 19786, 19787, 19788, 19789, 19790, 19791, 19792, 19793, 19794, 19795, 19796, 19797, 19798, 19799, 19800, 19801, 19802, 19803, 19804, 19805, 19806, 19807, 19808, 19809, 19810, 19811, 19812, 19813, 19814, 19815, 19816, 19817, 19818, 19819, 19820, 19821, 19822, 19823, 19824, 19825, 19826, 19827, 19828, 19829, 19830, 19831, 19832, 19833, 19834, 19835, 19836, 19837, 19838, 19839, 19840, 19841, 19842, 19843, 19844, 19845, 19846, 19847, 19848, 19849, 19850, 19851, 19852, 19853, 19854, 19855, 19856, 19857, 19858, 19859, 19860, 19861, 19862, 19863, 19864, 19865, 19866, 19867, 19868, 19869, 19870, 19871, 19872, 19873, 19874, 19875, 19876, 19877, 19878, 19879, 19880, 19881, 19882, 19883, 19884, 19885, 19886, 19887, 19888, 19889, 19890, 19891, 19892, 19893, 19894, 19895, 19896, 19897, 19898, 19899, 19900, 19901, 19902, 19903, 19904, 19905, 19906, 19907, 19908, 19909, 19910, 19911, 19912, 19913, 19914, 19915, 19916, 19917, 19918, 19919, 19920, 19921, 19922, 19923, 19924, 19925, 19926, 19927, 19928, 19929, 19930, 19931, 19932, 19933, 19934, 19935, 19936, 19937, 19938, 19939, 19940, 19941, 19942, 19943, 19944, 19945, 19946, 19947, 19948, 19949, 19950, 19951, 19952, 19953, 19954, 19955, 19956, 19957, 19958, 19959, 19960, 19961, 19962, 19963, 19964, 19965, 19966, 19967, 19968, 19969, 19970, 19971, 19972, 19973, 19974, 19975, 19976, 19977, 19978, 19979, 19980, 19981, 19982, 19983, 19984, 19985, 19986, 19987, 19988, 19989, 19990, 19991, 19992, 19993, 19994, 19995, 19996, 19997, 19998, 19999, 20000, 20001, 20002, 20003, 20004, 20005, 20006, 20007, 20008, 20009, 20010, 20011, 20012, 20013, 20014, 20015, 20016, 20017, 20018, 20019, 20020, 20021, 20022, 20023, 20024, 20025, 20026, 20027, 20028, 20029, 20030, 20031, 20032, 20033, 20034, 20035, 20036, 20037, 20038, 20039, 20040, 20041, 20042, 20043, 20044, 20045, 20046, 20047, 20048, 20049, 20050, 20051, 20052, 20053, 20054, 20055, 20056, 20057, 20058, 20059, 20060, 20061, 20062, 20063, 20064, 20065, 20066, 20067, 20068, 20069, 20070, 20071, 20072, 20073, 20074, 20075, 20076, 20077, 20078, 20079, 20080, 20081, 20082, 20083, 20084, 20085, 20086, 20087, 20088, 20089, 20090, 20091, 20092, 20093, 20094, 20095, 20096, 20097, 20098, 20099, 20100, 20101, 20102, 20103, 20104, 20105, 20106, 20107, 20108, 20109, 20110, 20111, 20112, 20113, 20114, 20115, 20116, 20117, 20118, 20119, 20120, 20121, 20122, 20123, 20124, 20125, 20126, 20127, 20128, 20129, 20130, 20131, 20132, 20133, 20134, 20135, 20136, 20137, 20138, 20139, 20140, 20141, 20142, 20143, 20144, 20145, 20146, 20147, 20148, 20149, 20150, 20151, 20152, 20153, 20154, 20155, 20156, 20157, 20158, 20159, 20160, 20161, 20162, 20163, 20164, 20165, 20166, 20167, 20168, 20169, 20170, 20171, 20172, 20173, 20174, 20175, 20176, 20177, 20178, 20179, 20180, 20181, 20182, 20183, 20184, 20185, 20186, 20187, 20188, 20189, 20190, 20191, 20192, 20193, 20194, 20195, 20196, 20197, 20198, 20199, 20200, 20201, 20202, 20203, 20204, 20205, 20206, 20207, 20208, 20209, 20210, 20211, 20212, 20213, 20214, 20215, 20216, 20217, 20218, 20219, 20220, 20221, 20222, 20223, 20224, 20225, 20226, 20227, 20228, 20229, 20230, 20231, 20232, 20233, 20234, 20235, 20236, 20237, 20238, 20239, 20240, 20241, 20242, 20243, 20244, 20245, 20246, 20247, 20248, 20249, 20250, 20251, 20252, 20253, 20254, 20255, 20256, 20257, 20258, 20259, 20260, 20261, 20262, 20263, 20264, 20265, 20266, 20267, 20268, 20269, 20270, 20271, 20272, 20273, 20274, 20275, 20276, 20277, 20278, 20279, 20280, 20281, 20282, 20283, 20284, 20285, 20286, 20287, 20288, 20289, 20290, 20291, 20292, 20293, 20294, 20295, 20296, 20297, 20298, 20299, 20300, 20301, 20302, 20303, 20304, 20305, 20306, 20307, 20308, 20309, 20310, 20311, 20312, 20313, 20314, 20315, 20316, 20317, 20318, 20319, 20320, 20321, 20322, 20323, 20324, 20325, 20326, 20327, 20328, 20329, 20330, 20331, 20332, 20333, 20334, 20335, 20336, 20337, 20338, 20339, 20340, 20341, 20342, 20343, 20344, 20345, 20346, 20347, 20348, 20349, 20350, 20351, 20352, 20353, 20354, 20355, 20356, 20357, 20358, 20359, 20360, 20361, 20362, 20363, 20364, 20365, 20366, 20367, 20368, 20369, 20370, 20371, 20372, 20373, 20374, 20375, 20376, 20377, 20378, 20379, 20380, 20381, 20382, 20383, 20384, 20385, 20386, 20387, 20388, 20389, 20390, 20391, 20392, 20393, 20394, 20395, 20396, 20397, 20398, 20399, 20400, 20401, 20402, 20403, 20404, 20405, 20406, 20407, 20408, 20409, 20410, 20411, 20412, 20413, 20414, 20415, 20416, 20417, 20418, 20419, 20420, 20421, 20422, 20423, 20424, 20425, 20426, 20427, 20428, 20429, 20430, 20431, 20432, 20433, 20434, 20435, 20436, 20437, 20438, 20439, 20440, 20441, 20442, 20443, 20444, 20445, 20446, 20447, 20448, 20449, 20450, 20451, 20452, 20453, 20454, 20455, 20456, 20457, 20458, 20459, 20460, 20461, 20462, 20463, 20464, 20465, 20466, 20467, 20468, 20469, 20470, 20471, 20472, 20473, 20474, 20475, 20476, 20477, 20478, 20479, 20480, 20481, 20482, 20483, 20484, 20485, 20486, 20487, 20488, 20489, 20490, 20491, 20492, 20493, 20494, 20495, 20496, 20497, 20498, 20499, 20500, 20501, 20502, 20503, 20504, 20505, 20506, 20507, 20508, 20509, 20510, 20511, 20512, 20513, 20514, 20515, 20516, 20517, 20518, 20519, 20520, 20521, 20522, 20523, 20524, 20525, 20526, 20527, 20528, 20529, 20530, 20531, 20532, 20533, 20534, 20535, 20536, 20537, 20538, 20539, 20540, 20541, 20542, 20543, 20544, 20545, 20546, 20547, 20548, 20549, 20550, 20551, 20552, 20553, 20554, 20555, 20556, 20557, 20558, 20559, 20560, 20561, 20562, 20563, 20564, 20565, 20566, 20567, 20568, 20569, 20570, 20571, 20572, 20573, 20574, 20575, 20576, 20577, 20578, 20579, 20580, 20581, 20582, 20583, 20584, 20585, 20586, 20587, 20588, 20589, 20590, 20591, 20592, 20593, 20594, 20595, 20596, 20597, 20598, 20599, 20600, 20601, 20602, 20603, 20604, 20605, 20606, 20607, 20608, 20609, 20610, 20611, 20612, 20613, 20614, 20615, 20616, 20617, 20618, 20619, 20620, 20621, 20622, 20623, 20624, 20625, 20626, 20627, 20628, 20629, 20630, 20631, 20632, 20633, 20634, 20635, 20636, 20637, 20638, 20639, 20640, 20641, 20642, 20643, 20644, 20645, 20646, 20647, 20648, 20649, 20650, 20651, 20652, 20653, 20654, 20655, 20656, 20657, 20658, 20659, 20660, 20661, 20662, 20663, 20664, 20665, 20666, 20667, 20668, 20669, 20670, 20671, 20672, 20673, 20674, 20675, 20676, 20677, 20678, 20679, 20680, 20681, 20682, 20683, 20684, 20685, 20686, 20687, 20688, 20689, 20690, 20691, 20692, 20693, 20694, 20695, 20696, 20697, 20698, 20699, 20700, 20701, 20702, 20703, 20704, 20705, 20706, 20707, 20708, 20709, 20710, 20711, 20712, 20713, 20714, 20715, 20716, 20717, 20718, 20719, 20720, 20721, 20722, 20723, 20724, 20725, 20726, 20727, 20728, 20729, 20730, 20731, 20732, 20733, 20734, 20735, 20736, 20737, 20738, 20739, 20740, 20741, 20742, 20743, 20744, 20745, 20746, 20747, 20748, 20749, 20750, 20751, 20752, 20753, 20754, 20755, 20756, 20757, 20758, 20759, 20760, 20761, 20762, 20763, 20764, 20765, 20766, 20767, 20768, 20769, 20770, 20771, 20772, 20773, 20774, 20775, 20776, 20777, 20778, 20779, 20780, 20781, 20782, 20783, 20784, 20785, 20786, 20787, 20788, 20789, 20790, 20791, 20792, 20793, 20794, 20795, 20796, 20797, 20798, 20799, 20800, 20801, 20802, 20803, 20804, 20805, 20806, 20807, 20808, 20809, 20810, 20811, 20812, 20813, 20814, 20815, 20816, 20817, 20818, 20819, 20820, 20821, 20822, 20823, 20824, 20825, 20826, 20827, 20828, 20829, 20830, 20831, 20832, 20833, 20834, 20835, 20836, 20837, 20838, 20839, 20840, 20841, 20842, 20843, 20844, 20845, 20846, 20847, 20848, 20849, 20850, 20851, 20852, 20853, 20854, 20855, 20856, 20857, 20858, 20859, 20860, 20861, 20862, 20863, 20864, 20865, 20866, 20867, 20868, 20869, 20870, 20871, 20872, 20873, 20874, 20875, 20876, 20877, 20878, 20879, 20880, 20881, 20882, 20883, 20884, 20885, 20886, 20887, 20888, 20889, 20890, 20891, 20892, 20893, 20894, 20895, 20896, 20897, 20898, 20899, 20900, 20901, 20902, 20903, 20904, 20905, 20906, 20907, 20908, 20909, 20910, 20911, 20912, 20913, 20914, 20915, 20916, 20917, 20918, 20919, 20920, 20921, 20922, 20923, 20924, 20925, 20926, 20927, 20928, 20929, 20930, 20931, 20932, 20933, 20934, 20935, 20936, 20937, 20938, 20939, 20940, 20941, 20942, 20943, 20944, 20945, 20946, 20947, 20948, 20949, 20950, 20951, 20952, 20953, 20954, 20955, 20956, 20957, 20958, 20959, 20960, 20961, 20962, 20963, 20964, 20965, 20966, 20967, 20968, 20969, 20970, 20971, 20972, 20973, 20974, 20975, 20976, 20977, 20978, 20979, 20980, 20981, 20982, 20983, 20984, 20985, 20986, 20987, 20988, 20989, 20990, 20991, 20992, 20993, 20994, 20995, 20996, 20997, 20998, 20999, 21000, 21001, 21002, 21003, 21004, 21005, 21006, 21007, 21008, 21009, 21010, 21011, 21012, 21013, 21014, 21015, 21016, 21017, 21018, 21019, 21020, 21021, 21022, 21023, 21024, 21025, 21026, 21027, 21028, 21029, 21030, 21031, 21032, 21033, 21034, 21035, 21036, 21037, 21038, 21039, 21040, 21041, 21042, 21043, 21044, 21045, 21046, 21047, 21048, 21049, 21050, 21051, 21052, 21053, 21054, 21055, 21056, 21057, 21058, 21059, 21060, 21061, 21062, 21063, 21064, 21065, 21066, 21067, 21068, 21069, 21070, 21071, 21072, 21073, 21074, 21075, 21076, 21077, 21078, 21079, 21080, 21081, 21082, 21083, 21084, 21085, 21086, 21087, 21088, 21089, 21090, 21091, 21092, 21093, 21094, 21095, 21096, 21097, 21098, 21099, 21100, 21101, 21102, 21103, 21104, 21105, 21106, 21107, 21108, 21109, 21110, 21111, 21112, 21113, 21114, 21115, 21116, 21117, 21118, 21119, 21120, 21121, 21122, 21123, 21124, 21125, 21126, 21127, 21128, 21129, 21130, 21131, 21132, 21133, 21134, 21135, 21136, 21137, 21138, 21139, 21140, 21141, 21142, 21143, 21144, 21145, 21146, 21147, 21148, 21149, 21150, 21151, 21152, 21153, 21154, 21155, 21156, 21157, 21158, 21159}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519, 520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532, 533, 534, 535, 536, 537, 538, 539, 540, 541, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558, 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 578, 579, 580, 581, 582, 583, 584, 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 757, 758, 759, 760, 761, 762, 763, 764, 765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 778, 779, 780, 781, 782, 783, 784, 785, 786, 787, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 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19706, 19707, 19708, 19709, 19710, 19711, 19712, 19713, 19714, 19715, 19716, 19717, 19718, 19719, 19720, 19721, 19722, 19723, 19724, 19725, 19726, 19727, 19728, 19729, 19730, 19731, 19732, 19733, 19734, 19735, 19736, 19737, 19738, 19739, 19740, 19741, 19742, 19743, 19744, 19745, 19746, 19747, 19748, 19749, 19750, 19751, 19752, 19753, 19754, 19755, 19756, 19757, 19758, 19759, 19760, 19761, 19762, 19763, 19764, 19765, 19766, 19767, 19768, 19769, 19770, 19771, 19772, 19773, 19774, 19775, 19776, 19777, 19778, 19779, 19780, 19781, 19782, 19783, 19784, 19785, 19786, 19787, 19788, 19789, 19790, 19791, 19792, 19793, 19794, 19795, 19796, 19797, 19798, 19799, 19800, 19801, 19802, 19803, 19804, 19805, 19806, 19807, 19808, 19809, 19810, 19811, 19812, 19813, 19814, 19815, 19816, 19817, 19818, 19819, 19820, 19821, 19822, 19823, 19824, 19825, 19826, 19827, 19828, 19829, 19830, 19831, 19832, 19833, 19834, 19835, 19836, 19837, 19838, 19839, 19840, 19841, 19842, 19843, 19844, 19845, 19846, 19847, 19848, 19849, 19850, 19851, 19852, 19853, 19854, 19855, 19856, 19857, 19858, 19859, 19860, 19861, 19862, 19863, 19864, 19865, 19866, 19867, 19868, 19869, 19870, 19871, 19872, 19873, 19874, 19875, 19876, 19877, 19878, 19879, 19880, 19881, 19882, 19883, 19884, 19885, 19886, 19887, 19888, 19889, 19890, 19891, 19892, 19893, 19894, 19895, 19896, 19897, 19898, 19899, 19900, 19901, 19902, 19903, 19904, 19905, 19906, 19907, 19908, 19909, 19910, 19911, 19912, 19913, 19914, 19915, 19916, 19917, 19918, 19919, 19920, 19921, 19922, 19923, 19924, 19925, 19926, 19927, 19928, 19929, 19930, 19931, 19932, 19933, 19934, 19935, 19936, 19937, 19938, 19939, 19940, 19941, 19942, 19943, 19944, 19945, 19946, 19947, 19948, 19949, 19950, 19951, 19952, 19953, 19954, 19955, 19956, 19957, 19958, 19959, 19960, 19961, 19962, 19963, 19964, 19965, 19966, 19967, 19968, 19969, 19970, 19971, 19972, 19973, 19974, 19975, 19976, 19977, 19978, 19979, 19980, 19981, 19982, 19983, 19984, 19985, 19986, 19987, 19988, 19989, 19990, 19991, 19992, 19993, 19994, 19995, 19996, 19997, 19998, 19999, 20000, 20001, 20002, 20003, 20004, 20005, 20006, 20007, 20008, 20009, 20010, 20011, 20012, 20013, 20014, 20015, 20016, 20017, 20018, 20019, 20020, 20021, 20022, 20023, 20024, 20025, 20026, 20027, 20028, 20029, 20030, 20031, 20032, 20033, 20034, 20035, 20036, 20037, 20038, 20039, 20040, 20041, 20042, 20043, 20044, 20045, 20046, 20047, 20048, 20049, 20050, 20051, 20052, 20053, 20054, 20055, 20056, 20057, 20058, 20059, 20060, 20061, 20062, 20063, 20064, 20065, 20066, 20067, 20068, 20069, 20070, 20071, 20072, 20073, 20074, 20075, 20076, 20077, 20078, 20079, 20080, 20081, 20082, 20083, 20084, 20085, 20086, 20087, 20088, 20089, 20090, 20091, 20092, 20093, 20094, 20095, 20096, 20097, 20098, 20099, 20100, 20101, 20102, 20103, 20104, 20105, 20106, 20107, 20108, 20109, 20110, 20111, 20112, 20113, 20114, 20115, 20116, 20117, 20118, 20119, 20120, 20121, 20122, 20123, 20124, 20125, 20126, 20127, 20128, 20129, 20130, 20131, 20132, 20133, 20134, 20135, 20136, 20137, 20138, 20139, 20140, 20141, 20142, 20143, 20144, 20145, 20146, 20147, 20148, 20149, 20150, 20151, 20152, 20153, 20154, 20155, 20156, 20157, 20158, 20159, 20160, 20161, 20162, 20163, 20164, 20165, 20166, 20167, 20168, 20169, 20170, 20171, 20172, 20173, 20174, 20175, 20176, 20177, 20178, 20179, 20180, 20181, 20182, 20183, 20184, 20185, 20186, 20187, 20188, 20189, 20190, 20191, 20192, 20193, 20194, 20195, 20196, 20197, 20198, 20199, 20200, 20201, 20202, 20203, 20204, 20205, 20206, 20207, 20208, 20209, 20210, 20211, 20212, 20213, 20214, 20215, 20216, 20217, 20218, 20219, 20220, 20221, 20222, 20223, 20224, 20225, 20226, 20227, 20228, 20229, 20230, 20231, 20232, 20233, 20234, 20235, 20236, 20237, 20238, 20239, 20240, 20241, 20242, 20243, 20244, 20245, 20246, 20247, 20248, 20249, 20250, 20251, 20252, 20253, 20254, 20255, 20256, 20257, 20258, 20259, 20260, 20261, 20262, 20263, 20264, 20265, 20266, 20267, 20268, 20269, 20270, 20271, 20272, 20273, 20274, 20275, 20276, 20277, 20278, 20279, 20280, 20281, 20282, 20283, 20284, 20285, 20286, 20287, 20288, 20289, 20290, 20291, 20292, 20293, 20294, 20295, 20296, 20297, 20298, 20299, 20300, 20301, 20302, 20303, 20304, 20305, 20306, 20307, 20308, 20309, 20310, 20311, 20312, 20313, 20314, 20315, 20316, 20317, 20318, 20319, 20320, 20321, 20322, 20323, 20324, 20325, 20326, 20327, 20328, 20329, 20330, 20331, 20332, 20333, 20334, 20335, 20336, 20337, 20338, 20339, 20340, 20341, 20342, 20343, 20344, 20345, 20346, 20347, 20348, 20349, 20350, 20351, 20352, 20353, 20354, 20355, 20356, 20357, 20358, 20359, 20360, 20361, 20362, 20363, 20364, 20365, 20366, 20367, 20368, 20369, 20370, 20371, 20372, 20373, 20374, 20375, 20376, 20377, 20378, 20379, 20380, 20381, 20382, 20383, 20384, 20385, 20386, 20387, 20388, 20389, 20390, 20391, 20392, 20393, 20394, 20395, 20396, 20397, 20398, 20399, 20400, 20401, 20402, 20403, 20404, 20405, 20406, 20407, 20408, 20409, 20410, 20411, 20412, 20413, 20414, 20415, 20416, 20417, 20418, 20419, 20420, 20421, 20422, 20423, 20424, 20425, 20426, 20427, 20428, 20429, 20430, 20431, 20432, 20433, 20434, 20435, 20436, 20437, 20438, 20439, 20440, 20441, 20442, 20443, 20444, 20445, 20446, 20447, 20448, 20449, 20450, 20451, 20452, 20453, 20454, 20455, 20456, 20457, 20458, 20459, 20460, 20461, 20462, 20463, 20464, 20465, 20466, 20467, 20468, 20469, 20470, 20471, 20472, 20473, 20474, 20475, 20476, 20477, 20478, 20479, 20480, 20481, 20482, 20483, 20484, 20485, 20486, 20487, 20488, 20489, 20490, 20491, 20492, 20493, 20494, 20495, 20496, 20497, 20498, 20499, 20500, 20501, 20502, 20503, 20504, 20505, 20506, 20507, 20508, 20509, 20510, 20511, 20512, 20513, 20514, 20515, 20516, 20517, 20518, 20519, 20520, 20521, 20522, 20523, 20524, 20525, 20526, 20527, 20528, 20529, 20530, 20531, 20532, 20533, 20534, 20535, 20536, 20537, 20538, 20539, 20540, 20541, 20542, 20543, 20544, 20545, 20546, 20547, 20548, 20549, 20550, 20551, 20552, 20553, 20554, 20555, 20556, 20557, 20558, 20559, 20560, 20561, 20562, 20563, 20564, 20565, 20566, 20567, 20568, 20569, 20570, 20571, 20572, 20573, 20574, 20575, 20576, 20577, 20578, 20579, 20580, 20581, 20582, 20583, 20584, 20585, 20586, 20587, 20588, 20589, 20590, 20591, 20592, 20593, 20594, 20595, 20596, 20597, 20598, 20599, 20600, 20601, 20602, 20603, 20604, 20605, 20606, 20607, 20608, 20609, 20610, 20611, 20612, 20613, 20614, 20615, 20616, 20617, 20618, 20619, 20620, 20621, 20622, 20623, 20624, 20625, 20626, 20627, 20628, 20629, 20630, 20631, 20632, 20633, 20634, 20635, 20636, 20637, 20638, 20639, 20640, 20641, 20642, 20643, 20644, 20645, 20646, 20647, 20648, 20649, 20650, 20651, 20652, 20653, 20654, 20655, 20656, 20657, 20658, 20659, 20660, 20661, 20662, 20663, 20664, 20665, 20666, 20667, 20668, 20669, 20670, 20671, 20672, 20673, 20674, 20675, 20676, 20677, 20678, 20679, 20680, 20681, 20682, 20683, 20684, 20685, 20686, 20687, 20688, 20689, 20690, 20691, 20692, 20693, 20694, 20695, 20696, 20697, 20698, 20699, 20700, 20701, 20702, 20703, 20704, 20705, 20706, 20707, 20708, 20709, 20710, 20711, 20712, 20713, 20714, 20715, 20716, 20717, 20718, 20719, 20720, 20721, 20722, 20723, 20724, 20725, 20726, 20727, 20728, 20729, 20730, 20731, 20732, 20733, 20734, 20735, 20736, 20737, 20738, 20739, 20740, 20741, 20742, 20743, 20744, 20745, 20746, 20747, 20748, 20749, 20750, 20751, 20752, 20753, 20754, 20755, 20756, 20757, 20758, 20759, 20760, 20761, 20762, 20763, 20764, 20765, 20766, 20767, 20768, 20769, 20770, 20771, 20772, 20773, 20774, 20775, 20776, 20777, 20778, 20779, 20780, 20781, 20782, 20783, 20784, 20785, 20786, 20787, 20788, 20789, 20790, 20791, 20792, 20793, 20794, 20795, 20796, 20797, 20798, 20799, 20800, 20801, 20802, 20803, 20804, 20805, 20806, 20807, 20808, 20809, 20810, 20811, 20812, 20813, 20814, 20815, 20816, 20817, 20818, 20819, 20820, 20821, 20822, 20823, 20824, 20825, 20826, 20827, 20828, 20829, 20830, 20831, 20832, 20833, 20834, 20835, 20836, 20837, 20838, 20839, 20840, 20841, 20842, 20843, 20844, 20845, 20846, 20847, 20848, 20849, 20850, 20851, 20852, 20853, 20854, 20855, 20856, 20857, 20858, 20859, 20860, 20861, 20862, 20863, 20864, 20865, 20866, 20867, 20868, 20869, 20870, 20871, 20872, 20873, 20874, 20875, 20876, 20877, 20878, 20879, 20880, 20881, 20882, 20883, 20884, 20885, 20886, 20887, 20888, 20889, 20890, 20891, 20892, 20893, 20894, 20895, 20896, 20897, 20898, 20899, 20900, 20901, 20902, 20903, 20904, 20905, 20906, 20907, 20908, 20909, 20910, 20911, 20912, 20913, 20914, 20915, 20916, 20917, 20918, 20919, 20920, 20921, 20922, 20923, 20924, 20925, 20926, 20927, 20928, 20929, 20930, 20931, 20932, 20933, 20934, 20935, 20936, 20937, 20938, 20939, 20940, 20941, 20942, 20943, 20944, 20945, 20946, 20947, 20948, 20949, 20950, 20951, 20952, 20953, 20954, 20955, 20956, 20957, 20958, 20959, 20960, 20961, 20962, 20963, 20964, 20965, 20966, 20967, 20968, 20969, 20970, 20971, 20972, 20973, 20974, 20975, 20976, 20977, 20978, 20979, 20980, 20981, 20982, 20983, 20984, 20985, 20986, 20987, 20988, 20989, 20990, 20991, 20992, 20993, 20994, 20995, 20996, 20997, 20998, 20999, 21000, 21001, 21002, 21003, 21004, 21005, 21006, 21007, 21008, 21009, 21010, 21011, 21012, 21013, 21014, 21015, 21016, 21017, 21018, 21019, 21020, 21021, 21022, 21023, 21024, 21025, 21026, 21027, 21028, 21029, 21030, 21031, 21032, 21033, 21034, 21035, 21036, 21037, 21038, 21039, 21040, 21041, 21042, 21043, 21044, 21045, 21046, 21047, 21048, 21049, 21050, 21051, 21052, 21053, 21054, 21055, 21056, 21057, 21058, 21059, 21060, 21061, 21062, 21063, 21064, 21065, 21066, 21067, 21068, 21069, 21070, 21071, 21072, 21073, 21074, 21075, 21076, 21077, 21078, 21079, 21080, 21081, 21082, 21083, 21084, 21085, 21086, 21087, 21088, 21089, 21090, 21091, 21092, 21093, 21094, 21095, 21096, 21097, 21098, 21099, 21100, 21101, 21102, 21103, 21104, 21105, 21106, 21107, 21108, 21109, 21110, 21111, 21112, 21113, 21114, 21115, 21116, 21117, 21118, 21119, 21120, 21121, 21122, 21123, 21124, 21125, 21126, 21127, 21128, 21129, 21130, 21131, 21132, 21133, 21134, 21135, 21136, 21137, 21138, 21139, 21140, 21141, 21142, 21143, 21144, 21145, 21146, 21147, 21148, 21149, 21150, 21151, 21152, 21153, 21154, 21155, 21156, 21157, 21158, 21159}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/concat_float_3_relaxed.example.cpp b/nn/runtime/test/generated/examples/concat_float_3_relaxed.example.cpp
new file mode 100644
index 0000000..b755d4e
--- /dev/null
+++ b/nn/runtime/test/generated/examples/concat_float_3_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: concat_float_3_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519, 520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532, 533, 534, 535, 536, 537, 538, 539, 540, 541, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558, 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 578, 579, 580, 581, 582, 583, 584, 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 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-5280, -5281, -5282, -5283, -5284, -5285, -5286, -5287, -5288, -5289, -5290, -5291, -5292, -5293, -5294, -5295, -5296, -5297, -5298, -5299, -5300, -5301, -5302, -5303, -5304, -5305, -5306, -5307, -5308, -5309, -5310, -5311, -5312, -5313, -5314, -5315, -5316, -5317, -5318, -5319, -5320, -5321, -5322, -5323, -5324, -5325, -5326, -5327, -5328, -5329, -5330, -5331, -5332, -5333, -5334, -5335, -5336, -5337, -5338, -5339, -5340, -5341, -5342, -5343, -5344, -5345, -5346, -5347, -5348, -5349, -5350, -5351, -5352, -5353, -5354, -5355, -5356, -5357, -5358, -5359, -5360, -5361, -5362, -5363, -5364, -5365, -5366, -5367, -5368, -5369, -5370, -5371, -5372, -5373, -5374, -5375, -5376, -5377, -5378, -5379, -5380, -5381, -5382, -5383, -5384, -5385, -5386, -5387, -5388, -5389, -5390, -5391, -5392, -5393, -5394, -5395, -5396, -5397, -5398, -5399, -5400, -5401, -5402, -5403, -5404, -5405, -5406, -5407, -5408, -5409, -5410, -5411, -5412, -5413, -5414, -5415, -5416, -5417, -5418, -5419, -5420, -5421, -5422, -5423, -5424, -5425, -5426, -5427, -5428, -5429, -5430, -5431, -5432, -5433, -5434, -5435, -5436, -5437, -5438, -5439, -5440, -5441, -5442, -5443, -5444, -5445, -5446, -5447, -5448, -5449, -5450, -5451, -5452, -5453, -5454, -5455, -5456, -5457, -5458, -5459, -5460, -5461, -5462, -5463, -5464, -5465, -5466, -5467, -5468, -5469, -5470, -5471, -5472, -5473, -5474, -5475, -5476, -5477, -5478, -5479, -5480, -5481, -5482, -5483, -5484, -5485, -5486, -5487, -5488, -5489, -5490, -5491, -5492, -5493, -5494, -5495, -5496, -5497, -5498, -5499, -5500, -5501, -5502, -5503, -5504, -5505, -5506, -5507, -5508, -5509, -5510, -5511, -5512, -5513, -5514, -5515, -5516, -5517, -5518, -5519, -5520, -5521, -5522, -5523, -5524, -5525, -5526, -5527, -5528, -5529, -5530, -5531, -5532, -5533, -5534, -5535, -5536, -5537, -5538, -5539, -5540, -5541, -5542, -5543, -5544, -5545, -5546, -5547, -5548, -5549, -5550, -5551, -5552, -5553, -5554, -5555, -5556, -5557, -5558, -5559, -5560, -5561, -5562, -5563, -5564, -5565, -5566, -5567, -5568, -5569, -5570, -5571, -5572, -5573, -5574, -5575, -5576, -5577, -5578, -5579, -5580, -5581, -5582, -5583, -5584, -5585, -5586, -5587, -5588, -5589, -5590, -5591, -5592, -5593, -5594, -5595, -5596, -5597, -5598, -5599, -5600, -5601, -5602, -5603, -5604, -5605, -5606, -5607, -5608, -5609, -5610, -5611, -5612, -5613, -5614, -5615, -5616, -5617, -5618, -5619, -5620, -5621, -5622, -5623, -5624, -5625, -5626, -5627, -5628, -5629, -5630, -5631, -5632, -5633, -5634, -5635, -5636, -5637, -5638, -5639, -5640, -5641, -5642, -5643, -5644, -5645, -5646, -5647, -5648, -5649, -5650, -5651, -5652, -5653, -5654, -5655, -5656, -5657, -5658, -5659, -5660, -5661, -5662, -5663, -5664, -5665, -5666, -5667, -5668, -5669, -5670, -5671, -5672, -5673, -5674, -5675, -5676, -5677, -5678, -5679, -5680, -5681, -5682, -5683, -5684, -5685, -5686, -5687, -5688, -5689, -5690, -5691, -5692, -5693, -5694, -5695, -5696, -5697, -5698, -5699, -5700, -5701, -5702, -5703, -5704, -5705, -5706, -5707, -5708, -5709, -5710, -5711, -5712, -5713, -5714, -5715, -5716, -5717, -5718, -5719, -5720, -5721, -5722, -5723, -5724, -5725, -5726, -5727, -5728, -5729, -5730, -5731, -5732, -5733, -5734, -5735, -5736, -5737, -5738, -5739, -5740, -5741, -5742, -5743, -5744, -5745, -5746, -5747, -5748, -5749, -5750, -5751, -5752, -5753, -5754, -5755, -5756, -5757, -5758, -5759, -5760, -5761, -5762, -5763, -5764, -5765, -5766, -5767, -5768, -5769, -5770, -5771, -5772, -5773, -5774, -5775, -5776, -5777, -5778, -5779, -5780, -5781, -5782, -5783, -5784, -5785, -5786, -5787, -5788, -5789, -5790, -5791, -5792, -5793, -5794, -5795, -5796, -5797, -5798, -5799, -5800, -5801, -5802, -5803, -5804, -5805, -5806, -5807, -5808, -5809, -5810, -5811, -5812, -5813, -5814, -5815, -5816, -5817, -5818, -5819, -5820, -5821, -5822, -5823, -5824, -5825, -5826, -5827, -5828, -5829, -5830, -5831, -5832, -5833, -5834, -5835, -5836, -5837, -5838, -5839, -5840, -5841, -5842, -5843, -5844, -5845, -5846, -5847, -5848, -5849, -5850, -5851, -5852, -5853, -5854, -5855, -5856, -5857, -5858, -5859, -5860, -5861, -5862, -5863, -5864, -5865, -5866, -5867, -5868, -5869, -5870, -5871, -5872, -5873, -5874, -5875, -5876, -5877, -5878, -5879, -5880, -5881, -5882, -5883, -5884, -5885, -5886, -5887, -5888, -5889, -5890, -5891, -5892, -5893, -5894, -5895, -5896, -5897, -5898, -5899, -5900, -5901, -5902, -5903, -5904, -5905, -5906, -5907, -5908, -5909, -5910, -5911, -5912, -5913, -5914, -5915, -5916, -5917, -5918, -5919, -5920, -5921, -5922, -5923, -5924, -5925, -5926, -5927, -5928, -5929, -5930, -5931, -5932, -5933, -5934, -5935, -5936, -5937, -5938, -5939, -5940, -5941, -5942, -5943, -5944, -5945, -5946, -5947, -5948, -5949, -5950, -5951, -5952, -5953, -5954, -5955, -5956, -5957, -5958, -5959, -5960, -5961, -5962, -5963, -5964, -5965, -5966, -5967, -5968, -5969, -5970, -5971, -5972, -5973, -5974, -5975, -5976, -5977, -5978, -5979, -5980, -5981, -5982, -5983, -5984, -5985, -5986, -5987, -5988, -5989, -5990, -5991, -5992, -5993, -5994, -5995, -5996, -5997, -5998, -5999, -6000, -6001, -6002, -6003, -6004, -6005, -6006, -6007, -6008, -6009, -6010, -6011, -6012, -6013, -6014, -6015, -6016, -6017, -6018, -6019, -6020, -6021, -6022, -6023, -6024, -6025, -6026, -6027, -6028, -6029, -6030, -6031, -6032, -6033, -6034, -6035, -6036, -6037, -6038, -6039, -6040, -6041, -6042, -6043, -6044, -6045, -6046, -6047, -6048, -6049, -6050, -6051, -6052, -6053, -6054, -6055, -6056, -6057, -6058, -6059, -6060, -6061, -6062, -6063, -6064, -6065, -6066, -6067, -6068, -6069, -6070, -6071, -6072, -6073, -6074, -6075, -6076, -6077, -6078, -6079, -6080, -6081, -6082, -6083, -6084, -6085, -6086, -6087, -6088, -6089, -6090, -6091, -6092, -6093, -6094, -6095, -6096, -6097, -6098, -6099, -6100, -6101, -6102, -6103, -6104, -6105, -6106, -6107, -6108, -6109, -6110, -6111, -6112, -6113, -6114, -6115, -6116, -6117, -6118, -6119, -6120, -6121, -6122, -6123, -6124, -6125, -6126, -6127, -6128, -6129, -6130, -6131, -6132, -6133, -6134, -6135, -6136, -6137, -6138, -6139, -6140, -6141, -6142, -6143, -6144, -6145, -6146, -6147, -6148, -6149, -6150, -6151, -6152, -6153, -6154, -6155, -6156, -6157, -6158, -6159, -6160, -6161, -6162, -6163, -6164, -6165, -6166, -6167, -6168, -6169, -6170, -6171, -6172, -6173, -6174, -6175, -6176, -6177, -6178, -6179, -6180, -6181, -6182, -6183, -6184, -6185, -6186, -6187, -6188, -6189, -6190, -6191, -6192, -6193, -6194, -6195, -6196, -6197, -6198, -6199, -6200, -6201, -6202, -6203, -6204, -6205, -6206, -6207, -6208, -6209, -6210, -6211, -6212, -6213, -6214, -6215, -6216, -6217, -6218, -6219, -6220, -6221, -6222, -6223, -6224, -6225, -6226, -6227, -6228, -6229, -6230, -6231, -6232, -6233, -6234, -6235, -6236, -6237, -6238, -6239, -6240, -6241, -6242, -6243, -6244, -6245, -6246, -6247, -6248, -6249, -6250, -6251, -6252, -6253, -6254, -6255, -6256, -6257, -6258, -6259, -6260, -6261, -6262, -6263, -6264, -6265, -6266, -6267, -6268, -6269, -6270, -6271, -6272, -6273, -6274, -6275, -6276, -6277, -6278, -6279, -6280, -6281, -6282, -6283, -6284, -6285, -6286, -6287, -6288, -6289, -6290, -6291, -6292, -6293, -6294, -6295, -6296, -6297, -6298, -6299, -6300, -6301, -6302, -6303, -6304, -6305, -6306, -6307, -6308, -6309, -6310, -6311, -6312, -6313, -6314, -6315, -6316, -6317, -6318, -6319, -6320, -6321, -6322, -6323, -6324, -6325, -6326, -6327, -6328, -6329, -6330, -6331, -6332, -6333, -6334, -6335, -6336, -6337, -6338, -6339, -6340, -6341, -6342, -6343, -6344, -6345, -6346, -6347, -6348, -6349, -6350, -6351, -6352, -6353, -6354, -6355, -6356, -6357, -6358, -6359}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 0, -1, -2, -3, -4, -5, -6, -7, -8, -9, -10, -11, -12, -13, -14, -15, -16, -17, -18, -19, -20, -21, -22, -23, -24, -25, -26, -27, -28, -29, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, -30, -31, -32, -33, -34, -35, -36, -37, -38, -39, -40, -41, -42, -43, -44, -45, -46, -47, -48, -49, -50, -51, -52, -53, -54, -55, -56, -57, -58, -59, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, -60, -61, -62, -63, -64, -65, -66, -67, -68, -69, -70, -71, -72, -73, -74, -75, -76, -77, -78, -79, -80, -81, -82, -83, -84, -85, -86, -87, -88, -89, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, -90, -91, -92, -93, -94, -95, -96, -97, -98, -99, -100, -101, -102, -103, -104, -105, -106, -107, -108, -109, -110, -111, -112, -113, -114, -115, -116, -117, -118, -119, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, -120, -121, -122, -123, -124, -125, -126, -127, -128, -129, -130, -131, -132, -133, -134, -135, -136, -137, -138, -139, -140, -141, -142, -143, -144, -145, -146, -147, -148, -149, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, -150, -151, -152, -153, -154, -155, -156, -157, -158, -159, -160, -161, -162, -163, -164, -165, -166, -167, -168, -169, -170, -171, -172, -173, -174, -175, -176, -177, -178, -179, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, -180, -181, -182, -183, -184, 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11914, 11915, 11916, 11917, 11918, 11919, 11920, 11921, 11922, 11923, 11924, 11925, 11926, 11927, 11928, 11929, 11930, 11931, 11932, 11933, 11934, 11935, 11936, 11937, 11938, 11939, -5940, -5941, -5942, -5943, -5944, -5945, -5946, -5947, -5948, -5949, -5950, -5951, -5952, -5953, -5954, -5955, -5956, -5957, -5958, -5959, -5960, -5961, -5962, -5963, -5964, -5965, -5966, -5967, -5968, -5969, 11940, 11941, 11942, 11943, 11944, 11945, 11946, 11947, 11948, 11949, 11950, 11951, 11952, 11953, 11954, 11955, 11956, 11957, 11958, 11959, 11960, 11961, 11962, 11963, 11964, 11965, 11966, 11967, 11968, 11969, 11970, 11971, 11972, 11973, 11974, 11975, 11976, 11977, 11978, 11979, 11980, 11981, 11982, 11983, 11984, 11985, 11986, 11987, 11988, 11989, 11990, 11991, 11992, 11993, 11994, 11995, 11996, 11997, 11998, 11999, -5970, -5971, -5972, -5973, -5974, -5975, -5976, -5977, -5978, -5979, -5980, -5981, -5982, -5983, -5984, -5985, -5986, -5987, -5988, -5989, -5990, -5991, -5992, -5993, -5994, -5995, -5996, -5997, -5998, -5999, 12000, 12001, 12002, 12003, 12004, 12005, 12006, 12007, 12008, 12009, 12010, 12011, 12012, 12013, 12014, 12015, 12016, 12017, 12018, 12019, 12020, 12021, 12022, 12023, 12024, 12025, 12026, 12027, 12028, 12029, 12030, 12031, 12032, 12033, 12034, 12035, 12036, 12037, 12038, 12039, 12040, 12041, 12042, 12043, 12044, 12045, 12046, 12047, 12048, 12049, 12050, 12051, 12052, 12053, 12054, 12055, 12056, 12057, 12058, 12059, -6000, -6001, -6002, -6003, -6004, -6005, -6006, -6007, -6008, -6009, -6010, -6011, -6012, -6013, -6014, -6015, -6016, -6017, -6018, -6019, -6020, -6021, -6022, -6023, -6024, -6025, -6026, -6027, -6028, -6029, 12060, 12061, 12062, 12063, 12064, 12065, 12066, 12067, 12068, 12069, 12070, 12071, 12072, 12073, 12074, 12075, 12076, 12077, 12078, 12079, 12080, 12081, 12082, 12083, 12084, 12085, 12086, 12087, 12088, 12089, 12090, 12091, 12092, 12093, 12094, 12095, 12096, 12097, 12098, 12099, 12100, 12101, 12102, 12103, 12104, 12105, 12106, 12107, 12108, 12109, 12110, 12111, 12112, 12113, 12114, 12115, 12116, 12117, 12118, 12119, -6030, -6031, -6032, -6033, -6034, -6035, -6036, -6037, -6038, -6039, -6040, -6041, -6042, -6043, -6044, -6045, -6046, -6047, -6048, -6049, -6050, -6051, -6052, -6053, -6054, -6055, -6056, -6057, -6058, -6059, 12120, 12121, 12122, 12123, 12124, 12125, 12126, 12127, 12128, 12129, 12130, 12131, 12132, 12133, 12134, 12135, 12136, 12137, 12138, 12139, 12140, 12141, 12142, 12143, 12144, 12145, 12146, 12147, 12148, 12149, 12150, 12151, 12152, 12153, 12154, 12155, 12156, 12157, 12158, 12159, 12160, 12161, 12162, 12163, 12164, 12165, 12166, 12167, 12168, 12169, 12170, 12171, 12172, 12173, 12174, 12175, 12176, 12177, 12178, 12179, -6060, -6061, -6062, -6063, -6064, -6065, -6066, -6067, -6068, -6069, -6070, -6071, -6072, -6073, -6074, -6075, -6076, -6077, -6078, -6079, -6080, -6081, -6082, -6083, -6084, -6085, -6086, -6087, -6088, -6089, 12180, 12181, 12182, 12183, 12184, 12185, 12186, 12187, 12188, 12189, 12190, 12191, 12192, 12193, 12194, 12195, 12196, 12197, 12198, 12199, 12200, 12201, 12202, 12203, 12204, 12205, 12206, 12207, 12208, 12209, 12210, 12211, 12212, 12213, 12214, 12215, 12216, 12217, 12218, 12219, 12220, 12221, 12222, 12223, 12224, 12225, 12226, 12227, 12228, 12229, 12230, 12231, 12232, 12233, 12234, 12235, 12236, 12237, 12238, 12239, -6090, -6091, -6092, -6093, -6094, -6095, -6096, -6097, -6098, -6099, -6100, -6101, -6102, -6103, -6104, -6105, -6106, -6107, -6108, -6109, -6110, -6111, -6112, -6113, -6114, -6115, -6116, -6117, -6118, -6119, 12240, 12241, 12242, 12243, 12244, 12245, 12246, 12247, 12248, 12249, 12250, 12251, 12252, 12253, 12254, 12255, 12256, 12257, 12258, 12259, 12260, 12261, 12262, 12263, 12264, 12265, 12266, 12267, 12268, 12269, 12270, 12271, 12272, 12273, 12274, 12275, 12276, 12277, 12278, 12279, 12280, 12281, 12282, 12283, 12284, 12285, 12286, 12287, 12288, 12289, 12290, 12291, 12292, 12293, 12294, 12295, 12296, 12297, 12298, 12299, -6120, -6121, -6122, -6123, -6124, -6125, -6126, -6127, -6128, -6129, -6130, -6131, -6132, -6133, -6134, -6135, -6136, -6137, -6138, -6139, -6140, -6141, -6142, -6143, -6144, -6145, -6146, -6147, -6148, -6149, 12300, 12301, 12302, 12303, 12304, 12305, 12306, 12307, 12308, 12309, 12310, 12311, 12312, 12313, 12314, 12315, 12316, 12317, 12318, 12319, 12320, 12321, 12322, 12323, 12324, 12325, 12326, 12327, 12328, 12329, 12330, 12331, 12332, 12333, 12334, 12335, 12336, 12337, 12338, 12339, 12340, 12341, 12342, 12343, 12344, 12345, 12346, 12347, 12348, 12349, 12350, 12351, 12352, 12353, 12354, 12355, 12356, 12357, 12358, 12359, -6150, -6151, -6152, -6153, -6154, -6155, -6156, -6157, -6158, -6159, -6160, -6161, -6162, -6163, -6164, -6165, -6166, -6167, -6168, -6169, -6170, -6171, -6172, -6173, -6174, -6175, -6176, -6177, -6178, -6179, 12360, 12361, 12362, 12363, 12364, 12365, 12366, 12367, 12368, 12369, 12370, 12371, 12372, 12373, 12374, 12375, 12376, 12377, 12378, 12379, 12380, 12381, 12382, 12383, 12384, 12385, 12386, 12387, 12388, 12389, 12390, 12391, 12392, 12393, 12394, 12395, 12396, 12397, 12398, 12399, 12400, 12401, 12402, 12403, 12404, 12405, 12406, 12407, 12408, 12409, 12410, 12411, 12412, 12413, 12414, 12415, 12416, 12417, 12418, 12419, -6180, -6181, -6182, -6183, -6184, -6185, -6186, -6187, -6188, -6189, -6190, -6191, -6192, -6193, -6194, -6195, -6196, -6197, -6198, -6199, -6200, -6201, -6202, -6203, -6204, -6205, -6206, -6207, -6208, -6209, 12420, 12421, 12422, 12423, 12424, 12425, 12426, 12427, 12428, 12429, 12430, 12431, 12432, 12433, 12434, 12435, 12436, 12437, 12438, 12439, 12440, 12441, 12442, 12443, 12444, 12445, 12446, 12447, 12448, 12449, 12450, 12451, 12452, 12453, 12454, 12455, 12456, 12457, 12458, 12459, 12460, 12461, 12462, 12463, 12464, 12465, 12466, 12467, 12468, 12469, 12470, 12471, 12472, 12473, 12474, 12475, 12476, 12477, 12478, 12479, -6210, -6211, -6212, -6213, -6214, -6215, -6216, -6217, -6218, -6219, -6220, -6221, -6222, -6223, -6224, -6225, -6226, -6227, -6228, -6229, -6230, -6231, -6232, -6233, -6234, -6235, -6236, -6237, -6238, -6239, 12480, 12481, 12482, 12483, 12484, 12485, 12486, 12487, 12488, 12489, 12490, 12491, 12492, 12493, 12494, 12495, 12496, 12497, 12498, 12499, 12500, 12501, 12502, 12503, 12504, 12505, 12506, 12507, 12508, 12509, 12510, 12511, 12512, 12513, 12514, 12515, 12516, 12517, 12518, 12519, 12520, 12521, 12522, 12523, 12524, 12525, 12526, 12527, 12528, 12529, 12530, 12531, 12532, 12533, 12534, 12535, 12536, 12537, 12538, 12539, -6240, -6241, -6242, -6243, -6244, -6245, -6246, -6247, -6248, -6249, -6250, -6251, -6252, -6253, -6254, -6255, -6256, -6257, -6258, -6259, -6260, -6261, -6262, -6263, -6264, -6265, -6266, -6267, -6268, -6269, 12540, 12541, 12542, 12543, 12544, 12545, 12546, 12547, 12548, 12549, 12550, 12551, 12552, 12553, 12554, 12555, 12556, 12557, 12558, 12559, 12560, 12561, 12562, 12563, 12564, 12565, 12566, 12567, 12568, 12569, 12570, 12571, 12572, 12573, 12574, 12575, 12576, 12577, 12578, 12579, 12580, 12581, 12582, 12583, 12584, 12585, 12586, 12587, 12588, 12589, 12590, 12591, 12592, 12593, 12594, 12595, 12596, 12597, 12598, 12599, -6270, -6271, -6272, -6273, -6274, -6275, -6276, -6277, -6278, -6279, -6280, -6281, -6282, -6283, -6284, -6285, -6286, -6287, -6288, -6289, -6290, -6291, -6292, -6293, -6294, -6295, -6296, -6297, -6298, -6299, 12600, 12601, 12602, 12603, 12604, 12605, 12606, 12607, 12608, 12609, 12610, 12611, 12612, 12613, 12614, 12615, 12616, 12617, 12618, 12619, 12620, 12621, 12622, 12623, 12624, 12625, 12626, 12627, 12628, 12629, 12630, 12631, 12632, 12633, 12634, 12635, 12636, 12637, 12638, 12639, 12640, 12641, 12642, 12643, 12644, 12645, 12646, 12647, 12648, 12649, 12650, 12651, 12652, 12653, 12654, 12655, 12656, 12657, 12658, 12659, -6300, -6301, -6302, -6303, -6304, -6305, -6306, -6307, -6308, -6309, -6310, -6311, -6312, -6313, -6314, -6315, -6316, -6317, -6318, -6319, -6320, -6321, -6322, -6323, -6324, -6325, -6326, -6327, -6328, -6329, 12660, 12661, 12662, 12663, 12664, 12665, 12666, 12667, 12668, 12669, 12670, 12671, 12672, 12673, 12674, 12675, 12676, 12677, 12678, 12679, 12680, 12681, 12682, 12683, 12684, 12685, 12686, 12687, 12688, 12689, 12690, 12691, 12692, 12693, 12694, 12695, 12696, 12697, 12698, 12699, 12700, 12701, 12702, 12703, 12704, 12705, 12706, 12707, 12708, 12709, 12710, 12711, 12712, 12713, 12714, 12715, 12716, 12717, 12718, 12719, -6330, -6331, -6332, -6333, -6334, -6335, -6336, -6337, -6338, -6339, -6340, -6341, -6342, -6343, -6344, -6345, -6346, -6347, -6348, -6349, -6350, -6351, -6352, -6353, -6354, -6355, -6356, -6357, -6358, -6359}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/conv_1_h3_w2_SAME_relaxed.example.cpp b/nn/runtime/test/generated/examples/conv_1_h3_w2_SAME_relaxed.example.cpp
new file mode 100644
index 0000000..90b680a
--- /dev/null
+++ b/nn/runtime/test/generated/examples/conv_1_h3_w2_SAME_relaxed.example.cpp
@@ -0,0 +1,43 @@
+// Generated file (from: conv_1_h3_w2_SAME_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.869931f, 0.644628f, -0.918393f, 0.153672f, 0.868562f, -0.358177f, -0.134931f, -0.247565f, 0.22174f, -0.259157f, -0.284296f, -0.538065f, 0.765559f, 0.41986f, -0.556241f, 0.658494f, 0.214355f, -0.850169f, -0.252893f, -0.478935f, 0.530526f, -0.0700663f, -0.988729f, -0.303061f, 0.150845f, 0.829915f, 0.476349f, 0.406537f, -0.355343f, 0.757145f, -0.356362f, 0.800482f, -0.713861f, 0.210483f, -0.634303f, 0.718236f, -0.752038f, 0.457547f, -0.550769f, -0.551178f, 0.446766f, -0.227462f, 0.216348f, -0.852806f, -0.351486f, 0.55906f, -0.668493f, -0.303493f, -0.363763f, -0.162837f, 0.0701012f, 0.756097f, -0.142269f, 0.329724f, -0.656317f, -0.998086f, -0.652949f, -0.40316f, -0.893682f, 0.432744f, 0.612362f, -0.869588f, -0.71327f, -0.398092f, -0.0423559f, 0.436576f, -0.925272f, 0.176549f, 0.822904f, 0.096833f, -0.296802f, -0.427195f, 0.031654f, -0.254479f, 0.244905f, 0.0948254f, 0.643769f, -0.90391f, 0.352665f, -0.901179f, 0.266159f, -0.968068f, -0.615401f, -0.388975f, 0.939052f, -0.116289f, 0.107523f, -0.0582711f, 0.435172f, 0.334675f, 0.459711f, 0.717436f, 0.496627f, -0.680175f, -0.415066f, 0.339848f, 0.506004f, -0.337808f, -0.107218f, -0.172496f, 0.870638f, 0.931872f, -0.953884f, 0.903042f, 0.760078f, 0.209727f, -0.285384f, -0.45514f, 0.113194f, 0.0756611f, 0.0924435f, -0.472863f, 0.960609f, -0.160385f, -0.839445f, 0.457097f, 0.163348f, 0.344867f, -0.131619f, 0.688715f, -0.540827f, 0.571259f, -0.95587f, 0.506164f, -0.155839f, 0.0789621f, 0.756772f, -0.662069f, 0.242908f, 0.460821f, 0.177872f, -0.289839f, -0.640603f, 0.702598f, -0.506406f, -0.568262f, -0.0713716f, 0.413792f, 0.159673f, -0.305208f, 0.133816f, -0.160254f, 0.787323f, -0.753244f, 0.600721f, 0.263186f, -0.162387f, 0.477962f, -0.702951f, -0.731036f, -0.939481f, -0.524519f, 0.934072f, -0.511637f, -0.503499f, 0.106236f, -0.323684f, 0.534444f, -0.843745f, 0.364171f, 0.0370358f, -0.168801f, -0.404559f, -0.814178f, 0.91745f, -0.334276f, 0.66925f, -0.801201f, 0.156511f, -0.427949f, 0.379153f, 0.818597f, -0.649902f, 0.427087f, -0.586015f, -0.559789f, -0.833923f, 0.0892409f, -0.621251f, 0.213826f, 0.465509f, 0.4704f, 0.380261f, 0.413067f, 0.180822f, 0.172866f, 0.59614f, 0.825575f, 0.662916f, -0.704381f, -0.297631f, 0.697778f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.85284f, -0.0393656f, -0.127353f, 1.43115f, -0.302294f, -1.0402f, 0.655023f, -0.587614f, 1.72003f, 1.55816f, 0.667546f, 2.23663f, 0.0661516f, 0.290254f, 0.770222f, -0.346357f, -1.58197f, -0.850595f, -0.484224f, 0.949967f, -0.577263f, -0.871949f, 2.34132f, -0.104506f, -0.135965f, -0.985713f, 0.815147f, 1.03114f, -1.41915f, -0.515534f, -0.373639f, 1.42026f, -1.50604f, 0.673113f, 3.06139f, -0.388578f, -1.76707f, -0.315667f, -1.03815f, -0.343435f, 0.432787f, -1.41643f, 1.12944f, -0.175806f, -0.846415f, 1.40095f, 0.70832f, -1.46717f, 2.19562f, -2.61266f, -0.705383f, 1.26124f, 1.46545f, -2.35761f, 2.04494f, 1.23741f, -0.527402f, -0.39954f, -0.0128623f, 1.3644f, 0.985755f, -0.718118f, -0.1008f, 1.24327f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.295335f, -0.00387601f, -0.552251f, 0.166084f, -0.28482f, -0.152143f, -0.719885f, -0.869386f, -0.745598f, 0.823947f, 0.473183f, -0.331337f, 0.187631f, 0.0426571f, -0.826897f, -0.755085f, -0.472453f, -0.0233656f, 0.0483436f, 0.933418f, -0.961974f, 0.0125783f, 0.219742f, 0.342604f, -0.15166f, 0.0934905f, 0.783221f, 0.129664f, 0.838844f, -0.271388f, 0.924519f, 0.342843f, 0.274418f, 0.350817f, 0.841638f, -0.543993f, -0.00283395f, -0.128467f, -0.682943f, -0.319117f, 0.84634f, 0.283003f, 0.32865f, 0.0293755f, -0.0335696f, 0.591266f, -0.0743476f, -0.741271f, 0.462056f, -0.583625f, -0.590183f, 0.6234f, 0.535269f, -0.670818f, -0.955642f, -0.770173f, 0.479986f, 0.664377f, 0.399445f, -0.968874f, -0.276263f, -0.901951f, 0.544104f, -0.958981f, 0.482658f, -0.807284f, 0.305369f, -0.947818f, 0.827498f, -0.382887f, -0.805741f, -0.796678f, -0.299804f, -0.229828f, 0.818783f, -0.103055f, -0.45568f, -0.227827f, 0.543743f, -0.96073f, 0.946747f, -0.857182f, -0.96426f, -0.292411f, -0.715614f, 0.765278f, -0.475043f, -0.590142f, -0.238507f, 0.673002f, -0.473357f, -0.319626f, 0.936014f, 0.486607f, 0.580844f, 0.425352f, -0.800994f, 0.290763f, -0.494953f, -0.441162f, 0.718677f, -0.828427f, 0.96965f, 7.53637e-05f, -0.699973f, -0.526886f, -0.352682f, 0.799466f, 0.332789f, 0.723389f, 0.407659f, -0.934084f, -0.284705f, 0.961484f, -0.700395f, -0.985808f, -0.595342f, -0.691721f, 0.49448f, -0.0842649f, 0.0390966f, 0.298938f, -0.128094f, -0.97158f, 0.86393f, 0.270606f, -0.468986f, -0.256605f, 0.47215f, -0.273117f, -0.590343f, -0.826529f, -0.725381f, -0.194821f, -0.259661f, -0.0949207f, -0.180302f, 0.0446834f, -0.222133f, -0.40393f, 0.295772f, -0.92949f, 0.580079f, -0.169856f, 0.330311f, 0.0173551f, -0.635823f, 0.475942f, 0.907175f, 0.242777f, -0.512208f, 0.362463f, 0.0496289f, 0.65171f, 0.990057f, 0.690733f, -0.469013f, -0.101311f, -0.68372f, -0.157841f, -0.677711f, -0.708224f, -0.659437f, -0.407607f, 0.677033f, 0.89032f, 0.228307f, -0.749514f, 0.772958f, 0.054701f, 0.551705f, 0.917052f, -0.895022f, -0.702397f, 0.484142f, 0.108648f, 0.833347f, 0.478872f, -0.984112f, 0.387176f, -0.73299f, 0.7526f, 0.443312f, -0.0987856f, 0.125415f, 0.10876f, -0.498108f, 0.43209f, 0.344609f, 0.928941f, -0.130732f, -0.0569167f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.000614278f, -1.21221f, 0.443861f, 0.102117f, -2.52714f, 1.47489f, 0.173474f, -0.237577f, 1.28735f, 1.91315f, 2.51734f, 0.375841f, 0.637563f, 2.653f, 2.72959f, -1.6271f, 1.17389f, -2.12119f, 2.91417f, -2.24246f, 0.0497045f, -0.127107f, -0.144473f, -0.133762f, -0.393284f, -2.02346f, -0.239178f, -0.246508f, 1.29277f, 1.32963f, 0.117521f, 1.22372f, 0.0665713f, 1.09438f, -1.31426f, 2.52594f, -0.969211f, 0.515478f, -1.60926f, -0.838905f, 0.135211f, 0.786415f, -1.14382f, -0.739102f, -1.01731f, 0.281615f, 2.36311f, 0.891823f, 1.93872f, -0.150491f, 3.45217f, 2.28219f, 1.18282f, -2.25086f, 3.05468f, 0.166228f, 0.434554f, -2.57529f, -0.958662f, -2.23978f, 2.66776f, 0.542601f, 1.76107f, -1.08134f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/conv_1_h3_w2_VALID_relaxed.example.cpp b/nn/runtime/test/generated/examples/conv_1_h3_w2_VALID_relaxed.example.cpp
new file mode 100644
index 0000000..3f21cd1
--- /dev/null
+++ b/nn/runtime/test/generated/examples/conv_1_h3_w2_VALID_relaxed.example.cpp
@@ -0,0 +1,43 @@
+// Generated file (from: conv_1_h3_w2_VALID_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.869931f, 0.644628f, -0.918393f, 0.153672f, 0.868562f, -0.358177f, -0.134931f, -0.247565f, 0.22174f, -0.259157f, -0.284296f, -0.538065f, 0.765559f, 0.41986f, -0.556241f, 0.658494f, 0.214355f, -0.850169f, -0.252893f, -0.478935f, 0.530526f, -0.0700663f, -0.988729f, -0.303061f, 0.150845f, 0.829915f, 0.476349f, 0.406537f, -0.355343f, 0.757145f, -0.356362f, 0.800482f, -0.713861f, 0.210483f, -0.634303f, 0.718236f, -0.752038f, 0.457547f, -0.550769f, -0.551178f, 0.446766f, -0.227462f, 0.216348f, -0.852806f, -0.351486f, 0.55906f, -0.668493f, -0.303493f, -0.363763f, -0.162837f, 0.0701012f, 0.756097f, -0.142269f, 0.329724f, -0.656317f, -0.998086f, -0.652949f, -0.40316f, -0.893682f, 0.432744f, 0.612362f, -0.869588f, -0.71327f, -0.398092f, -0.0423559f, 0.436576f, -0.925272f, 0.176549f, 0.822904f, 0.096833f, -0.296802f, -0.427195f, 0.031654f, -0.254479f, 0.244905f, 0.0948254f, 0.643769f, -0.90391f, 0.352665f, -0.901179f, 0.266159f, -0.968068f, -0.615401f, -0.388975f, 0.939052f, -0.116289f, 0.107523f, -0.0582711f, 0.435172f, 0.334675f, 0.459711f, 0.717436f, 0.496627f, -0.680175f, -0.415066f, 0.339848f, 0.506004f, -0.337808f, -0.107218f, -0.172496f, 0.870638f, 0.931872f, -0.953884f, 0.903042f, 0.760078f, 0.209727f, -0.285384f, -0.45514f, 0.113194f, 0.0756611f, 0.0924435f, -0.472863f, 0.960609f, -0.160385f, -0.839445f, 0.457097f, 0.163348f, 0.344867f, -0.131619f, 0.688715f, -0.540827f, 0.571259f, -0.95587f, 0.506164f, -0.155839f, 0.0789621f, 0.756772f, -0.662069f, 0.242908f, 0.460821f, 0.177872f, -0.289839f, -0.640603f, 0.702598f, -0.506406f, -0.568262f, -0.0713716f, 0.413792f, 0.159673f, -0.305208f, 0.133816f, -0.160254f, 0.787323f, -0.753244f, 0.600721f, 0.263186f, -0.162387f, 0.477962f, -0.702951f, -0.731036f, -0.939481f, -0.524519f, 0.934072f, -0.511637f, -0.503499f, 0.106236f, -0.323684f, 0.534444f, -0.843745f, 0.364171f, 0.0370358f, -0.168801f, -0.404559f, -0.814178f, 0.91745f, -0.334276f, 0.66925f, -0.801201f, 0.156511f, -0.427949f, 0.379153f, 0.818597f, -0.649902f, 0.427087f, -0.586015f, -0.559789f, -0.833923f, 0.0892409f, -0.621251f, 0.213826f, 0.465509f, 0.4704f, 0.380261f, 0.413067f, 0.180822f, 0.172866f, 0.59614f, 0.825575f, 0.662916f, -0.704381f, -0.297631f, 0.697778f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.72003f, 1.55816f, 0.667546f, 2.23663f, 0.0661516f, 0.290254f, 0.770222f, -1.58197f, -0.850595f, -0.484224f, 0.949967f, -0.577263f, -0.871949f, 2.34132f, -0.135965f, -0.985713f, 0.815147f, 1.03114f, -1.41915f, -0.515534f, -0.373639f, -1.50604f, 0.673113f, 3.06139f, -0.388578f, -1.76707f, -0.315667f, -1.03815f, 0.432787f, -1.41643f, 1.12944f, -0.175806f, -0.846415f, 1.40095f, 0.70832f, 2.19562f, -2.61266f, -0.705383f, 1.26124f, 1.46545f, -2.35761f, 2.04494f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.295335f, -0.00387601f, -0.552251f, 0.166084f, -0.28482f, -0.152143f, -0.719885f, -0.869386f, -0.745598f, 0.823947f, 0.473183f, -0.331337f, 0.187631f, 0.0426571f, -0.826897f, -0.755085f, -0.472453f, -0.0233656f, 0.0483436f, 0.933418f, -0.961974f, 0.0125783f, 0.219742f, 0.342604f, -0.15166f, 0.0934905f, 0.783221f, 0.129664f, 0.838844f, -0.271388f, 0.924519f, 0.342843f, 0.274418f, 0.350817f, 0.841638f, -0.543993f, -0.00283395f, -0.128467f, -0.682943f, -0.319117f, 0.84634f, 0.283003f, 0.32865f, 0.0293755f, -0.0335696f, 0.591266f, -0.0743476f, -0.741271f, 0.462056f, -0.583625f, -0.590183f, 0.6234f, 0.535269f, -0.670818f, -0.955642f, -0.770173f, 0.479986f, 0.664377f, 0.399445f, -0.968874f, -0.276263f, -0.901951f, 0.544104f, -0.958981f, 0.482658f, -0.807284f, 0.305369f, -0.947818f, 0.827498f, -0.382887f, -0.805741f, -0.796678f, -0.299804f, -0.229828f, 0.818783f, -0.103055f, -0.45568f, -0.227827f, 0.543743f, -0.96073f, 0.946747f, -0.857182f, -0.96426f, -0.292411f, -0.715614f, 0.765278f, -0.475043f, -0.590142f, -0.238507f, 0.673002f, -0.473357f, -0.319626f, 0.936014f, 0.486607f, 0.580844f, 0.425352f, -0.800994f, 0.290763f, -0.494953f, -0.441162f, 0.718677f, -0.828427f, 0.96965f, 7.53637e-05f, -0.699973f, -0.526886f, -0.352682f, 0.799466f, 0.332789f, 0.723389f, 0.407659f, -0.934084f, -0.284705f, 0.961484f, -0.700395f, -0.985808f, -0.595342f, -0.691721f, 0.49448f, -0.0842649f, 0.0390966f, 0.298938f, -0.128094f, -0.97158f, 0.86393f, 0.270606f, -0.468986f, -0.256605f, 0.47215f, -0.273117f, -0.590343f, -0.826529f, -0.725381f, -0.194821f, -0.259661f, -0.0949207f, -0.180302f, 0.0446834f, -0.222133f, -0.40393f, 0.295772f, -0.92949f, 0.580079f, -0.169856f, 0.330311f, 0.0173551f, -0.635823f, 0.475942f, 0.907175f, 0.242777f, -0.512208f, 0.362463f, 0.0496289f, 0.65171f, 0.990057f, 0.690733f, -0.469013f, -0.101311f, -0.68372f, -0.157841f, -0.677711f, -0.708224f, -0.659437f, -0.407607f, 0.677033f, 0.89032f, 0.228307f, -0.749514f, 0.772958f, 0.054701f, 0.551705f, 0.917052f, -0.895022f, -0.702397f, 0.484142f, 0.108648f, 0.833347f, 0.478872f, -0.984112f, 0.387176f, -0.73299f, 0.7526f, 0.443312f, -0.0987856f, 0.125415f, 0.10876f, -0.498108f, 0.43209f, 0.344609f, 0.928941f, -0.130732f, -0.0569167f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.28735f, 1.91315f, 2.51734f, 0.375841f, 0.637563f, 2.653f, 2.72959f, 1.17389f, -2.12119f, 2.91417f, -2.24246f, 0.0497045f, -0.127107f, -0.144473f, -0.393284f, -2.02346f, -0.239178f, -0.246508f, 1.29277f, 1.32963f, 0.117521f, 0.0665713f, 1.09438f, -1.31426f, 2.52594f, -0.969211f, 0.515478f, -1.60926f, 0.135211f, 0.786415f, -1.14382f, -0.739102f, -1.01731f, 0.281615f, 2.36311f, 1.93872f, -0.150491f, 3.45217f, 2.28219f, 1.18282f, -2.25086f, 3.05468f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/conv_3_h3_w2_SAME_relaxed.example.cpp b/nn/runtime/test/generated/examples/conv_3_h3_w2_SAME_relaxed.example.cpp
new file mode 100644
index 0000000..3b5f4e7
--- /dev/null
+++ b/nn/runtime/test/generated/examples/conv_3_h3_w2_SAME_relaxed.example.cpp
@@ -0,0 +1,43 @@
+// Generated file (from: conv_3_h3_w2_SAME_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.869931f, 0.644628f, -0.918393f, 0.153672f, 0.868562f, -0.358177f, -0.134931f, -0.247565f, 0.22174f, -0.259157f, -0.284296f, -0.538065f, 0.765559f, 0.41986f, -0.556241f, 0.658494f, 0.214355f, -0.850169f, -0.252893f, -0.478935f, 0.530526f, -0.0700663f, -0.988729f, -0.303061f, 0.150845f, 0.829915f, 0.476349f, 0.406537f, -0.355343f, 0.757145f, -0.356362f, 0.800482f, -0.713861f, 0.210483f, -0.634303f, 0.718236f, -0.752038f, 0.457547f, -0.550769f, -0.551178f, 0.446766f, -0.227462f, 0.216348f, -0.852806f, -0.351486f, 0.55906f, -0.668493f, -0.303493f, -0.363763f, -0.162837f, 0.0701012f, 0.756097f, -0.142269f, 0.329724f, -0.656317f, -0.998086f, -0.652949f, -0.40316f, -0.893682f, 0.432744f, 0.612362f, -0.869588f, -0.71327f, -0.398092f, -0.0423559f, 0.436576f, -0.925272f, 0.176549f, 0.822904f, 0.096833f, -0.296802f, -0.427195f, 0.031654f, -0.254479f, 0.244905f, 0.0948254f, 0.643769f, -0.90391f, 0.352665f, -0.901179f, 0.266159f, -0.968068f, -0.615401f, -0.388975f, 0.939052f, -0.116289f, 0.107523f, -0.0582711f, 0.435172f, 0.334675f, 0.459711f, 0.717436f, 0.496627f, -0.680175f, -0.415066f, 0.339848f, 0.506004f, -0.337808f, -0.107218f, -0.172496f, 0.870638f, 0.931872f, -0.953884f, 0.903042f, 0.760078f, 0.209727f, -0.285384f, -0.45514f, 0.113194f, 0.0756611f, 0.0924435f, -0.472863f, 0.960609f, -0.160385f, -0.839445f, 0.457097f, 0.163348f, 0.344867f, -0.131619f, 0.688715f, -0.540827f, 0.571259f, -0.95587f, 0.506164f, -0.155839f, 0.0789621f, 0.756772f, -0.662069f, 0.242908f, 0.460821f, 0.177872f, -0.289839f, -0.640603f, 0.702598f, -0.506406f, -0.568262f, -0.0713716f, 0.413792f, 0.159673f, -0.305208f, 0.133816f, -0.160254f, 0.787323f, -0.753244f, 0.600721f, 0.263186f, -0.162387f, 0.477962f, -0.702951f, -0.731036f, -0.939481f, -0.524519f, 0.934072f, -0.511637f, -0.503499f, 0.106236f, -0.323684f, 0.534444f, -0.843745f, 0.364171f, 0.0370358f, -0.168801f, -0.404559f, -0.814178f, 0.91745f, -0.334276f, 0.66925f, -0.801201f, 0.156511f, -0.427949f, 0.379153f, 0.818597f, -0.649902f, 0.427087f, -0.586015f, -0.559789f, -0.833923f, 0.0892409f, -0.621251f, 0.213826f, 0.465509f, 0.4704f, 0.380261f, 0.413067f, 0.180822f, 0.172866f, 0.59614f, 0.825575f, 0.662916f, -0.704381f, -0.297631f, 0.697778f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-1.27853f, 1.74987f, -0.876718f, 0.989692f, 0.298548f, 0.522103f, -0.536896f, -0.179382f, -0.966914f, 1.33708f, 1.37042f, -0.495494f, 1.43859f, -1.548f, -0.430026f, -0.662793f, -0.0867897f, -0.900658f, -0.524396f, 0.255731f, -0.779081f, 0.12666f, 0.915651f, -0.444765f, -0.186842f, -1.87308f, 1.21135f, -0.385009f, 1.72032f, -1.56036f, -1.23059f, 1.23694f, 0.00200015f, 0.359522f, 1.60084f, 0.434006f, -0.282945f, 2.37292f, -1.28653f, 0.0847837f, -0.352093f, -2.39659f, 0.149246f, 0.920351f, -1.34346f, 0.952311f, -0.35811f, 0.403449f, 0.484796f, -1.19989f, -0.684298f, -1.41301f, 0.103177f, -0.307039f, 1.17741f, 2.58936f, -2.76237f, -1.21565f, -1.09619f, 1.17432f, 0.512143f, 0.771379f, 0.399879f, -0.0533093f, 0.290864f, 0.95563f, 1.16328f, 1.80768f, -1.52564f, -0.126476f, -0.185224f, -0.114779f, 1.2248f, 0.237127f, -0.213297f, -0.619941f, 0.497944f, -1.68688f, 1.59314f, -0.127337f, 0.111419f, 1.13719f, 1.68537f, -0.479644f, 1.18608f, -2.52744f, 1.34136f, 0.548297f, -2.0838f, 2.64585f, -0.993354f, 0.128238f, 1.26092f, 0.318668f, 0.893795f, -0.0600559f, -0.629126f, -0.949229f, 2.25828f, -1.961f, 0.00589599f, -0.187854f, -1.02403f, 0.396121f, 1.3704f, 3.99355f, 0.434221f, 0.274464f, -0.562438f, -0.914871f, 0.539129f, -0.928687f, 0.834954f, 0.844178f, -0.566053f, -0.957341f, 0.933336f, 1.13613f, -1.22109f, 1.4649f, -0.414666f, -0.452821f, -0.706006f, -1.72657f, -0.726574f, -0.0979362f, -0.478669f, 1.78703f, -0.639288f, 1.48565f, -0.179904f, 1.01003f, -0.317118f, -0.675387f, 1.90969f, -1.38343f, 0.697255f, -0.292255f, 1.81634f, 0.717801f, 0.862479f, -0.407478f, -0.343106f, -0.0353232f, -0.481893f, -0.135565f, -2.95941f, 0.247846f, 2.67757f, -2.23999f, -0.519673f, 0.254447f, 0.415283f, -1.01065f, 0.507911f, 0.979926f, -0.184304f, -0.000950437f, -0.734348f, -0.196685f, -0.713241f, 0.594972f, 0.0845042f, 2.48496f, 0.385019f, -0.201145f, 0.533332f, -0.904872f, -0.333518f, -0.581063f, -2.07065f, 0.118687f, -1.86708f, -0.601987f, 0.432037f, 1.73923f, 0.590007f, 0.419788f, 0.314198f, 2.12817f, 0.570793f, -1.15998f, -0.348587f, -1.10231f, -2.13091f, 0.134467f, -0.460382f, 0.138338f, 3.455f, 0.679068f, -0.190282f, -0.0307461f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.295335f, -0.00387601f, -0.552251f, 0.166084f, -0.28482f, -0.152143f, -0.719885f, -0.869386f, -0.745598f, 0.823947f, 0.473183f, -0.331337f, 0.187631f, 0.0426571f, -0.826897f, -0.755085f, -0.472453f, -0.0233656f, 0.0483436f, 0.933418f, -0.961974f, 0.0125783f, 0.219742f, 0.342604f, -0.15166f, 0.0934905f, 0.783221f, 0.129664f, 0.838844f, -0.271388f, 0.924519f, 0.342843f, 0.274418f, 0.350817f, 0.841638f, -0.543993f, -0.00283395f, -0.128467f, -0.682943f, -0.319117f, 0.84634f, 0.283003f, 0.32865f, 0.0293755f, -0.0335696f, 0.591266f, -0.0743476f, -0.741271f, 0.462056f, -0.583625f, -0.590183f, 0.6234f, 0.535269f, -0.670818f, -0.955642f, -0.770173f, 0.479986f, 0.664377f, 0.399445f, -0.968874f, -0.276263f, -0.901951f, 0.544104f, -0.958981f, 0.482658f, -0.807284f, 0.305369f, -0.947818f, 0.827498f, -0.382887f, -0.805741f, -0.796678f, -0.299804f, -0.229828f, 0.818783f, -0.103055f, -0.45568f, -0.227827f, 0.543743f, -0.96073f, 0.946747f, -0.857182f, -0.96426f, -0.292411f, -0.715614f, 0.765278f, -0.475043f, -0.590142f, -0.238507f, 0.673002f, -0.473357f, -0.319626f, 0.936014f, 0.486607f, 0.580844f, 0.425352f, -0.800994f, 0.290763f, -0.494953f, -0.441162f, 0.718677f, -0.828427f, 0.96965f, 7.53637e-05f, -0.699973f, -0.526886f, -0.352682f, 0.799466f, 0.332789f, 0.723389f, 0.407659f, -0.934084f, -0.284705f, 0.961484f, -0.700395f, -0.985808f, -0.595342f, -0.691721f, 0.49448f, -0.0842649f, 0.0390966f, 0.298938f, -0.128094f, -0.97158f, 0.86393f, 0.270606f, -0.468986f, -0.256605f, 0.47215f, -0.273117f, -0.590343f, -0.826529f, -0.725381f, -0.194821f, -0.259661f, -0.0949207f, -0.180302f, 0.0446834f, -0.222133f, -0.40393f, 0.295772f, -0.92949f, 0.580079f, -0.169856f, 0.330311f, 0.0173551f, -0.635823f, 0.475942f, 0.907175f, 0.242777f, -0.512208f, 0.362463f, 0.0496289f, 0.65171f, 0.990057f, 0.690733f, -0.469013f, -0.101311f, -0.68372f, -0.157841f, -0.677711f, -0.708224f, -0.659437f, -0.407607f, 0.677033f, 0.89032f, 0.228307f, -0.749514f, 0.772958f, 0.054701f, 0.551705f, 0.917052f, -0.895022f, -0.702397f, 0.484142f, 0.108648f, 0.833347f, 0.478872f, -0.984112f, 0.387176f, -0.73299f, 0.7526f, 0.443312f, -0.0987856f, 0.125415f, 0.10876f, -0.498108f, 0.43209f, 0.344609f, 0.928941f, -0.130732f, -0.0569167f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.78574f, 0.0700466f, -0.110245f, 0.0141003f, -0.621007f, -0.979104f, 1.24104f, 0.580398f, -0.512997f, 0.900559f, -0.683229f, -1.0162f, 1.0089f, -0.0752488f, 0.110969f, 0.270558f, 0.756819f, -0.10753f, -0.371484f, 0.149005f, 0.0973829f, 0.155766f, -0.476502f, 0.259481f, 1.06709f, -1.16534f, 1.52694f, -0.797245f, 0.802736f, -0.997109f, 2.2661f, -1.45548f, 2.15506f, -1.33682f, 1.15225f, -3.09324f, 0.943457f, 0.885211f, 0.987944f, -0.345875f, -0.114708f, 1.7107f, 0.104745f, 0.828324f, -2.49964f, -0.453742f, -0.288829f, -0.0948694f, -0.489415f, 1.74889f, -0.378257f, -2.10237f, 0.613022f, -2.5225f, -0.746785f, 3.63816f, -1.9287f, 0.774279f, -0.613917f, -0.650011f, 1.03753f, -0.177923f, 0.891815f, -1.00373f, 1.83859f, -1.59239f, -0.0662623f, 0.218806f, -1.088f, 0.280837f, 0.902901f, -1.90127f, 3.04734f, -1.57302f, 1.10881f, -0.980369f, -3.85305f, -0.955859f, 1.64909f, 2.33573f, 0.31144f, -0.594375f, 0.325747f, -0.952566f, -0.613449f, 2.85073f, 1.94692f, 1.12977f, 1.1351f, -0.449652f, 0.118765f, -0.199547f, 2.873f, 1.35182f, -1.85457f, 1.22364f, 1.38049f, 2.38342f, 0.882321f, 1.03795f, -0.321571f, -2.60202f, -1.6372f, 1.09302f, 0.461768f, 1.8485f, -0.158928f, 4.28871f, -0.437375f, -1.5794f, 1.59869f, 0.0811864f, 0.912054f, 0.452176f, 2.01812f, 2.62907f, 1.50304f, -0.840276f, -0.455854f, -0.224913f, 0.609824f, -0.11105f, 3.35635f, 2.02386f, 1.4687f, -0.708365f, -0.508992f, -3.02602f, -0.75725f, 1.85277f, 2.92817f, -0.172997f, -1.13279f, -0.355636f, -0.337669f, -0.588752f, 2.05759f, 1.0651f, 0.884758f, -0.0712112f, 3.81319f, 0.771629f, 0.949634f, 0.0838967f, -2.19264f, 0.114521f, 0.543556f, -1.63197f, -0.267442f, 1.15701f, -2.37862f, 2.57646f, 0.531208f, 0.9499f, -0.231441f, 1.51461f, 1.58888f, 0.895931f, -0.753084f, 0.545251f, 0.746903f, 0.012994f, -0.790398f, -1.1055f, 1.77789f, 0.430923f, 0.818241f, -0.731412f, 0.979546f, -2.48707f, -1.53658f, -1.66798f, -1.04585f, -0.667911f, 1.00299f, -2.20339f, 0.137826f, -2.31281f, 0.755535f, 0.495396f, 0.549629f, 0.713128f, 0.751369f, 0.283996f, -0.814532f, 1.4866f, 1.12105f, 0.927998f, 0.517938f, -0.612661f, -1.47756f, -1.42422f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/conv_3_h3_w2_VALID_relaxed.example.cpp b/nn/runtime/test/generated/examples/conv_3_h3_w2_VALID_relaxed.example.cpp
new file mode 100644
index 0000000..1b3ca05
--- /dev/null
+++ b/nn/runtime/test/generated/examples/conv_3_h3_w2_VALID_relaxed.example.cpp
@@ -0,0 +1,43 @@
+// Generated file (from: conv_3_h3_w2_VALID_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.869931f, 0.644628f, -0.918393f, 0.153672f, 0.868562f, -0.358177f, -0.134931f, -0.247565f, 0.22174f, -0.259157f, -0.284296f, -0.538065f, 0.765559f, 0.41986f, -0.556241f, 0.658494f, 0.214355f, -0.850169f, -0.252893f, -0.478935f, 0.530526f, -0.0700663f, -0.988729f, -0.303061f, 0.150845f, 0.829915f, 0.476349f, 0.406537f, -0.355343f, 0.757145f, -0.356362f, 0.800482f, -0.713861f, 0.210483f, -0.634303f, 0.718236f, -0.752038f, 0.457547f, -0.550769f, -0.551178f, 0.446766f, -0.227462f, 0.216348f, -0.852806f, -0.351486f, 0.55906f, -0.668493f, -0.303493f, -0.363763f, -0.162837f, 0.0701012f, 0.756097f, -0.142269f, 0.329724f, -0.656317f, -0.998086f, -0.652949f, -0.40316f, -0.893682f, 0.432744f, 0.612362f, -0.869588f, -0.71327f, -0.398092f, -0.0423559f, 0.436576f, -0.925272f, 0.176549f, 0.822904f, 0.096833f, -0.296802f, -0.427195f, 0.031654f, -0.254479f, 0.244905f, 0.0948254f, 0.643769f, -0.90391f, 0.352665f, -0.901179f, 0.266159f, -0.968068f, -0.615401f, -0.388975f, 0.939052f, -0.116289f, 0.107523f, -0.0582711f, 0.435172f, 0.334675f, 0.459711f, 0.717436f, 0.496627f, -0.680175f, -0.415066f, 0.339848f, 0.506004f, -0.337808f, -0.107218f, -0.172496f, 0.870638f, 0.931872f, -0.953884f, 0.903042f, 0.760078f, 0.209727f, -0.285384f, -0.45514f, 0.113194f, 0.0756611f, 0.0924435f, -0.472863f, 0.960609f, -0.160385f, -0.839445f, 0.457097f, 0.163348f, 0.344867f, -0.131619f, 0.688715f, -0.540827f, 0.571259f, -0.95587f, 0.506164f, -0.155839f, 0.0789621f, 0.756772f, -0.662069f, 0.242908f, 0.460821f, 0.177872f, -0.289839f, -0.640603f, 0.702598f, -0.506406f, -0.568262f, -0.0713716f, 0.413792f, 0.159673f, -0.305208f, 0.133816f, -0.160254f, 0.787323f, -0.753244f, 0.600721f, 0.263186f, -0.162387f, 0.477962f, -0.702951f, -0.731036f, -0.939481f, -0.524519f, 0.934072f, -0.511637f, -0.503499f, 0.106236f, -0.323684f, 0.534444f, -0.843745f, 0.364171f, 0.0370358f, -0.168801f, -0.404559f, -0.814178f, 0.91745f, -0.334276f, 0.66925f, -0.801201f, 0.156511f, -0.427949f, 0.379153f, 0.818597f, -0.649902f, 0.427087f, -0.586015f, -0.559789f, -0.833923f, 0.0892409f, -0.621251f, 0.213826f, 0.465509f, 0.4704f, 0.380261f, 0.413067f, 0.180822f, 0.172866f, 0.59614f, 0.825575f, 0.662916f, -0.704381f, -0.297631f, 0.697778f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.186842f, -1.87308f, 1.21135f, -0.385009f, 1.72032f, -1.56036f, -1.23059f, 1.23694f, 0.00200015f, 0.359522f, 1.60084f, 0.434006f, -0.282945f, 2.37292f, -1.28653f, 0.0847837f, -0.352093f, -2.39659f, 0.149246f, 0.920351f, -1.34346f, 0.484796f, -1.19989f, -0.684298f, -1.41301f, 0.103177f, -0.307039f, 1.17741f, 2.58936f, -2.76237f, -1.21565f, -1.09619f, 1.17432f, 0.512143f, 0.771379f, 0.399879f, -0.0533093f, 0.290864f, 0.95563f, 1.16328f, 1.80768f, -1.52564f, 1.2248f, 0.237127f, -0.213297f, -0.619941f, 0.497944f, -1.68688f, 1.59314f, -0.127337f, 0.111419f, 1.13719f, 1.68537f, -0.479644f, 1.18608f, -2.52744f, 1.34136f, 0.548297f, -2.0838f, 2.64585f, -0.993354f, 0.128238f, 1.26092f, -0.629126f, -0.949229f, 2.25828f, -1.961f, 0.00589599f, -0.187854f, -1.02403f, 0.396121f, 1.3704f, 3.99355f, 0.434221f, 0.274464f, -0.562438f, -0.914871f, 0.539129f, -0.928687f, 0.834954f, 0.844178f, -0.566053f, -0.957341f, 0.933336f, -0.414666f, -0.452821f, -0.706006f, -1.72657f, -0.726574f, -0.0979362f, -0.478669f, 1.78703f, -0.639288f, 1.48565f, -0.179904f, 1.01003f, -0.317118f, -0.675387f, 1.90969f, -1.38343f, 0.697255f, -0.292255f, 1.81634f, 0.717801f, 0.862479f, -0.481893f, -0.135565f, -2.95941f, 0.247846f, 2.67757f, -2.23999f, -0.519673f, 0.254447f, 0.415283f, -1.01065f, 0.507911f, 0.979926f, -0.184304f, -0.000950437f, -0.734348f, -0.196685f, -0.713241f, 0.594972f, 0.0845044f, 2.48496f, 0.385019f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.295335f, -0.00387601f, -0.552251f, 0.166084f, -0.28482f, -0.152143f, -0.719885f, -0.869386f, -0.745598f, 0.823947f, 0.473183f, -0.331337f, 0.187631f, 0.0426571f, -0.826897f, -0.755085f, -0.472453f, -0.0233656f, 0.0483436f, 0.933418f, -0.961974f, 0.0125783f, 0.219742f, 0.342604f, -0.15166f, 0.0934905f, 0.783221f, 0.129664f, 0.838844f, -0.271388f, 0.924519f, 0.342843f, 0.274418f, 0.350817f, 0.841638f, -0.543993f, -0.00283395f, -0.128467f, -0.682943f, -0.319117f, 0.84634f, 0.283003f, 0.32865f, 0.0293755f, -0.0335696f, 0.591266f, -0.0743476f, -0.741271f, 0.462056f, -0.583625f, -0.590183f, 0.6234f, 0.535269f, -0.670818f, -0.955642f, -0.770173f, 0.479986f, 0.664377f, 0.399445f, -0.968874f, -0.276263f, -0.901951f, 0.544104f, -0.958981f, 0.482658f, -0.807284f, 0.305369f, -0.947818f, 0.827498f, -0.382887f, -0.805741f, -0.796678f, -0.299804f, -0.229828f, 0.818783f, -0.103055f, -0.45568f, -0.227827f, 0.543743f, -0.96073f, 0.946747f, -0.857182f, -0.96426f, -0.292411f, -0.715614f, 0.765278f, -0.475043f, -0.590142f, -0.238507f, 0.673002f, -0.473357f, -0.319626f, 0.936014f, 0.486607f, 0.580844f, 0.425352f, -0.800994f, 0.290763f, -0.494953f, -0.441162f, 0.718677f, -0.828427f, 0.96965f, 7.53637e-05f, -0.699973f, -0.526886f, -0.352682f, 0.799466f, 0.332789f, 0.723389f, 0.407659f, -0.934084f, -0.284705f, 0.961484f, -0.700395f, -0.985808f, -0.595342f, -0.691721f, 0.49448f, -0.0842649f, 0.0390966f, 0.298938f, -0.128094f, -0.97158f, 0.86393f, 0.270606f, -0.468986f, -0.256605f, 0.47215f, -0.273117f, -0.590343f, -0.826529f, -0.725381f, -0.194821f, -0.259661f, -0.0949207f, -0.180302f, 0.0446834f, -0.222133f, -0.40393f, 0.295772f, -0.92949f, 0.580079f, -0.169856f, 0.330311f, 0.0173551f, -0.635823f, 0.475942f, 0.907175f, 0.242777f, -0.512208f, 0.362463f, 0.0496289f, 0.65171f, 0.990057f, 0.690733f, -0.469013f, -0.101311f, -0.68372f, -0.157841f, -0.677711f, -0.708224f, -0.659437f, -0.407607f, 0.677033f, 0.89032f, 0.228307f, -0.749514f, 0.772958f, 0.054701f, 0.551705f, 0.917052f, -0.895022f, -0.702397f, 0.484142f, 0.108648f, 0.833347f, 0.478872f, -0.984112f, 0.387176f, -0.73299f, 0.7526f, 0.443312f, -0.0987856f, 0.125415f, 0.10876f, -0.498108f, 0.43209f, 0.344609f, 0.928941f, -0.130732f, -0.0569167f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.06709f, -1.16534f, 1.52694f, -0.797245f, 0.802736f, -0.997109f, 2.2661f, -1.45548f, 2.15506f, -1.33682f, 1.15225f, -3.09324f, 0.943457f, 0.885211f, 0.987944f, -0.345875f, -0.114708f, 1.7107f, 0.104745f, 0.828324f, -2.49964f, -0.489415f, 1.74889f, -0.378257f, -2.10237f, 0.613022f, -2.5225f, -0.746785f, 3.63816f, -1.9287f, 0.774279f, -0.613917f, -0.650011f, 1.03753f, -0.177923f, 0.891815f, -1.00373f, 1.83859f, -1.59239f, -0.0662623f, 0.218806f, -1.088f, 3.04734f, -1.57302f, 1.10881f, -0.980369f, -3.85305f, -0.955859f, 1.64909f, 2.33573f, 0.31144f, -0.594375f, 0.325747f, -0.952566f, -0.613449f, 2.85073f, 1.94692f, 1.12977f, 1.1351f, -0.449652f, 0.118765f, -0.199547f, 2.873f, 1.38049f, 2.38342f, 0.882321f, 1.03795f, -0.321571f, -2.60202f, -1.6372f, 1.09302f, 0.461768f, 1.8485f, -0.158928f, 4.28871f, -0.437375f, -1.5794f, 1.59869f, 0.0811864f, 0.912054f, 0.452176f, 2.01812f, 2.62907f, 1.50304f, 0.609824f, -0.11105f, 3.35635f, 2.02386f, 1.4687f, -0.708365f, -0.508992f, -3.02602f, -0.75725f, 1.85277f, 2.92817f, -0.172997f, -1.13279f, -0.355636f, -0.337669f, -0.588752f, 2.05759f, 1.0651f, 0.884758f, -0.0712112f, 3.81319f, -2.19264f, 0.114521f, 0.543556f, -1.63197f, -0.267442f, 1.15701f, -2.37862f, 2.57646f, 0.531208f, 0.9499f, -0.231441f, 1.51461f, 1.58888f, 0.895931f, -0.753084f, 0.545251f, 0.746904f, 0.0129939f, -0.790398f, -1.1055f, 1.77789f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/conv_float_channels_relaxed.example.cpp b/nn/runtime/test/generated/examples/conv_float_channels_relaxed.example.cpp
new file mode 100644
index 0000000..e98aff1
--- /dev/null
+++ b/nn/runtime/test/generated/examples/conv_float_channels_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: conv_float_channels_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {99.0f, 99.0f, 99.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {297.0f, 594.0f, 891.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/conv_float_channels_weights_as_inputs_relaxed.example.cpp b/nn/runtime/test/generated/examples/conv_float_channels_weights_as_inputs_relaxed.example.cpp
new file mode 100644
index 0000000..9a9fbd8
--- /dev/null
+++ b/nn/runtime/test/generated/examples/conv_float_channels_weights_as_inputs_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: conv_float_channels_weights_as_inputs_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {99.0f, 99.0f, 99.0f}}, {1, {1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f, 3.0f, 3.0f, 3.0f}}, {2, {0.0f, 0.0f, 0.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {297.0f, 594.0f, 891.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/conv_float_large_relaxed.example.cpp b/nn/runtime/test/generated/examples/conv_float_large_relaxed.example.cpp
new file mode 100644
index 0000000..e06001c
--- /dev/null
+++ b/nn/runtime/test/generated/examples/conv_float_large_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: conv_float_large_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {30.0f, 36.0f, 42.0f, 66.0f, 81.0f, 96.0f, 102.0f, 126.0f, 150.0f, 138.0f, 171.0f, 204.0f, 174.0f, 216.0f, 258.0f, 210.0f, 261.0f, 312.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/conv_float_large_weights_as_inputs_relaxed.example.cpp b/nn/runtime/test/generated/examples/conv_float_large_weights_as_inputs_relaxed.example.cpp
new file mode 100644
index 0000000..b8b51b5
--- /dev/null
+++ b/nn/runtime/test/generated/examples/conv_float_large_weights_as_inputs_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: conv_float_large_weights_as_inputs_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f}}, {1, {1.0f, 4.0f, 7.0f, 2.0f, 5.0f, 8.0f, 3.0f, 6.0f, 9.0f}}, {2, {0.0f, 0.0f, 0.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {30.0f, 36.0f, 42.0f, 66.0f, 81.0f, 96.0f, 102.0f, 126.0f, 150.0f, 138.0f, 171.0f, 204.0f, 174.0f, 216.0f, 258.0f, 210.0f, 261.0f, 312.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/conv_float_relaxed.example.cpp b/nn/runtime/test/generated/examples/conv_float_relaxed.example.cpp
new file mode 100644
index 0000000..5ecc83b
--- /dev/null
+++ b/nn/runtime/test/generated/examples/conv_float_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: conv_float_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 1.0f, 1.0f, 1.0f, 0.5f, 1.0f, 1.0f, 1.0f, 1.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.875f, 0.875f, 0.875f, 0.875f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/conv_float_weights_as_inputs_relaxed.example.cpp b/nn/runtime/test/generated/examples/conv_float_weights_as_inputs_relaxed.example.cpp
new file mode 100644
index 0000000..051f74c
--- /dev/null
+++ b/nn/runtime/test/generated/examples/conv_float_weights_as_inputs_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: conv_float_weights_as_inputs_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 1.0f, 1.0f, 1.0f, 0.5f, 1.0f, 1.0f, 1.0f, 1.0f}}, {1, {0.25f, 0.25f, 0.25f, 0.25f}}, {2, {0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.875f, 0.875f, 0.875f, 0.875f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/depth_to_space_float_1_relaxed.example.cpp b/nn/runtime/test/generated/examples/depth_to_space_float_1_relaxed.example.cpp
new file mode 100644
index 0000000..80418fc
--- /dev/null
+++ b/nn/runtime/test/generated/examples/depth_to_space_float_1_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: depth_to_space_float_1_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/depth_to_space_float_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/depth_to_space_float_2_relaxed.example.cpp
new file mode 100644
index 0000000..b454ae3
--- /dev/null
+++ b/nn/runtime/test/generated/examples/depth_to_space_float_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: depth_to_space_float_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 5.0f, 6.0f, 3.0f, 4.0f, 7.0f, 8.0f, 9.0f, 10.0f, 13.0f, 14.0f, 11.0f, 12.0f, 15.0f, 16.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/depth_to_space_float_3_relaxed.example.cpp b/nn/runtime/test/generated/examples/depth_to_space_float_3_relaxed.example.cpp
new file mode 100644
index 0000000..4848779
--- /dev/null
+++ b/nn/runtime/test/generated/examples/depth_to_space_float_3_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: depth_to_space_float_3_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {10, 20, 11, 21, 14, 24, 15, 25, 12, 22, 13, 23, 16, 26, 17, 27, 18, 28, 19, 29, 112, 212, 113, 213, 110, 210, 111, 211, 114, 214, 115, 215}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {10, 20, 11, 21, 12, 22, 13, 23, 14, 24, 15, 25, 16, 26, 17, 27, 18, 28, 19, 29, 110, 210, 111, 211, 112, 212, 113, 213, 114, 214, 115, 215}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_relaxed.example.cpp b/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_relaxed.example.cpp
new file mode 100644
index 0000000..64449b1
--- /dev/null
+++ b/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: depthwise_conv2d_float_large_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {10, 21, 10, 22, 10, 23, 10, 24}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {110, 246}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_weights_as_inputs_relaxed.example.cpp b/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_weights_as_inputs_relaxed.example.cpp
new file mode 100644
index 0000000..474fb29
--- /dev/null
+++ b/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_weights_as_inputs_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: depthwise_conv2d_float_large_weights_as_inputs_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {10, 21, 10, 22, 10, 23, 10, 24}}, {1, {0.25f, 0, 0.25f, 1, 0.25f, 0, 0.25f, 1}}, {2, {100, 200}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {110, 246}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/depthwise_conv_relaxed.example.cpp b/nn/runtime/test/generated/examples/depthwise_conv_relaxed.example.cpp
new file mode 100644
index 0000000..f2a4d39
--- /dev/null
+++ b/nn/runtime/test/generated/examples/depthwise_conv_relaxed.example.cpp
@@ -0,0 +1,43 @@
+// Generated file (from: depthwise_conv_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.869931f, 0.644628f, -0.918393f, 0.153672f, 0.868562f, -0.358177f, -0.134931f, -0.247565f, 0.22174f, -0.259157f, -0.284296f, -0.538065f, 0.765559f, 0.41986f, -0.556241f, 0.658494f, 0.214355f, -0.850169f, -0.252893f, -0.478935f, 0.530526f, -0.0700663f, -0.988729f, -0.303061f, 0.150845f, 0.829915f, 0.476349f, 0.406537f, -0.355343f, 0.757145f, -0.356362f, 0.800482f, -0.713861f, 0.210483f, -0.634303f, 0.718236f, -0.752038f, 0.457547f, -0.550769f, -0.551178f, 0.446766f, -0.227462f, 0.216348f, -0.852806f, -0.351486f, 0.55906f, -0.668493f, -0.303493f, -0.363763f, -0.162837f, 0.0701012f, 0.756097f, -0.142269f, 0.329724f, -0.656317f, -0.998086f, -0.652949f, -0.40316f, -0.893682f, 0.432744f, 0.612362f, -0.869588f, -0.71327f, -0.398092f, -0.0423559f, 0.436576f, -0.925272f, 0.176549f, 0.822904f, 0.096833f, -0.296802f, -0.427195f, 0.031654f, -0.254479f, 0.244905f, 0.0948254f, 0.643769f, -0.90391f, 0.352665f, -0.901179f, 0.266159f, -0.968068f, -0.615401f, -0.388975f, 0.939052f, -0.116289f, 0.107523f, -0.0582711f, 0.435172f, 0.334675f, 0.459711f, 0.717436f, 0.496627f, -0.680175f, -0.415066f, 0.339848f, 0.506004f, -0.337808f, -0.107218f, -0.172496f, 0.870638f, 0.931872f, -0.953884f, 0.903042f, 0.760078f, 0.209727f, -0.285384f, -0.45514f, 0.113194f, 0.0756611f, 0.0924435f, -0.472863f, 0.960609f, -0.160385f, -0.839445f, 0.457097f, 0.163348f, 0.344867f, -0.131619f, 0.688715f, -0.540827f, 0.571259f, -0.95587f, 0.506164f, -0.155839f, 0.0789621f, 0.756772f, -0.662069f, 0.242908f, 0.460821f, 0.177872f, -0.289839f, -0.640603f, 0.702598f, -0.506406f, -0.568262f, -0.0713716f, 0.413792f, 0.159673f, -0.305208f, 0.133816f, -0.160254f, 0.787323f, -0.753244f, 0.600721f, 0.263186f, -0.162387f, 0.477962f, -0.702951f, -0.731036f, -0.939481f, -0.524519f, 0.934072f, -0.511637f, -0.503499f, 0.106236f, -0.323684f, 0.534444f, -0.843745f, 0.364171f, 0.0370358f, -0.168801f, -0.404559f, -0.814178f, 0.91745f, -0.334276f, 0.66925f, -0.801201f, 0.156511f, -0.427949f, 0.379153f, 0.818597f, -0.649902f, 0.427087f, -0.586015f, -0.559789f, -0.833923f, 0.0892409f, -0.621251f, 0.213826f, 0.465509f, 0.4704f, 0.380261f, 0.413067f, 0.180822f, 0.172866f, 0.59614f, 0.825575f, 0.662916f, -0.704381f, -0.297631f, 0.697778f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.840539f, -0.301347f, 0.754947f, -0.14848f, -0.40603f, 0.294432f, 0.130372f, 0.11573f, -0.182277f, 0.2504f, 0.132901f, 0.442306f, -0.739693f, -0.196274f, 0.457246f, -0.636246f, -0.100205f, 0.698864f, 0.244348f, 0.22389f, -0.436108f, 0.067699f, 0.462205f, 0.249125f, -0.145748f, -0.387964f, -0.391573f, -0.392801f, 0.166114f, -0.622396f, 0.344322f, -0.374205f, 0.586815f, -0.203372f, 0.29652f, -0.590411f, 0.726629f, -0.213891f, 0.452749f, 0.532555f, -0.208851f, 0.186981f, -0.209039f, 0.398664f, 0.288932f, -0.540171f, 0.312503f, 0.24948f, 0.351473f, 0.076122f, -0.0576253f, -0.73055f, 0.0665069f, -0.271043f, 0.634142f, 0.466579f, 0.536743f, 0.389538f, 0.417773f, -0.355728f, -0.591672f, 0.40651f, 0.586329f, 0.384641f, 0.0198003f, -0.358878f, 0.894009f, -0.0825318f, -0.676451f, -0.0935613f, 0.138747f, 0.351167f, -0.0305845f, 0.118962f, -0.201319f, -0.0916215f, -0.300945f, 0.743041f, -0.34075f, 0.421278f, -0.218791f, 0.935359f, 0.287684f, 0.319749f, -0.907324f, 0.054362f, -0.0883874f, 0.0563023f, -0.203432f, -0.275113f, -0.444178f, -0.335382f, -0.408242f, 0.657194f, 0.194033f, -0.279365f, -0.488907f, 0.157917f, 0.0881365f, 0.166668f, -0.407001f, -0.766027f, 0.921655f, -0.422149f, -0.624807f, -0.202641f, 0.13341f, 0.374139f, -0.109369f, -0.0353696f, -0.0759913f, 0.456887f, -0.44906f, 0.131841f, 0.811082f, -0.213681f, -0.134277f, -0.333215f, 0.0615286f, -0.566144f, 0.522554f, -0.267049f, 0.785754f, -0.489062f, 0.0728509f, -0.0649092f, -0.731203f, 0.3095f, -0.199677f, -0.445251f, -0.0831503f, 0.238257f, 0.618959f, -0.328446f, 0.416281f, 0.549062f, 0.0333644f, -0.340149f, -0.154278f, 0.142677f, -0.110001f, 0.15484f, -0.368053f, 0.619189f, -0.580424f, -0.123033f, 0.133487f, -0.461813f, 0.328611f, 0.600933f, 0.907739f, 0.245199f, -0.767835f, 0.49435f, 0.235373f, -0.0873295f, 0.312748f, -0.249839f, 0.693584f, -0.351866f, -0.0173133f, 0.13876f, 0.39089f, 0.380607f, -0.754171f, 0.322982f, -0.312857f, 0.658611f, -0.151223f, 0.200055f, -0.311675f, -0.790939f, 0.303812f, -0.351079f, 0.566216f, 0.261687f, 0.68551f, -0.0862257f, 0.290419f, -0.175771f, -0.449781f, -0.2199f, -0.312586f, -0.399111f, -0.0845297f, -0.142101f, -0.575998f, -0.385935f, -0.544937f, 0.680582f, 0.139135f, -0.573594f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.295335f, -0.00387601f, -0.552251f, 0.166084f, -0.28482f, -0.152143f, -0.719885f, -0.869386f, -0.745598f, 0.823947f, 0.473183f, -0.331337f, 0.187631f, 0.0426571f, -0.826897f, -0.755085f, -0.472453f, -0.0233656f, 0.0483436f, 0.933418f, -0.961974f, 0.0125783f, 0.219742f, 0.342604f, -0.15166f, 0.0934905f, 0.783221f, 0.129664f, 0.838844f, -0.271388f, 0.924519f, 0.342843f, 0.274418f, 0.350817f, 0.841638f, -0.543993f, -0.00283395f, -0.128467f, -0.682943f, -0.319117f, 0.84634f, 0.283003f, 0.32865f, 0.0293755f, -0.0335696f, 0.591266f, -0.0743476f, -0.741271f, 0.462056f, -0.583625f, -0.590183f, 0.6234f, 0.535269f, -0.670818f, -0.955642f, -0.770173f, 0.479986f, 0.664377f, 0.399445f, -0.968874f, -0.276263f, -0.901951f, 0.544104f, -0.958981f, 0.482658f, -0.807284f, 0.305369f, -0.947818f, 0.827498f, -0.382887f, -0.805741f, -0.796678f, -0.299804f, -0.229828f, 0.818783f, -0.103055f, -0.45568f, -0.227827f, 0.543743f, -0.96073f, 0.946747f, -0.857182f, -0.96426f, -0.292411f, -0.715614f, 0.765278f, -0.475043f, -0.590142f, -0.238507f, 0.673002f, -0.473357f, -0.319626f, 0.936014f, 0.486607f, 0.580844f, 0.425352f, -0.800994f, 0.290763f, -0.494953f, -0.441162f, 0.718677f, -0.828427f, 0.96965f, 7.53637e-05f, -0.699973f, -0.526886f, -0.352682f, 0.799466f, 0.332789f, 0.723389f, 0.407659f, -0.934084f, -0.284705f, 0.961484f, -0.700395f, -0.985808f, -0.595342f, -0.691721f, 0.49448f, -0.0842649f, 0.0390966f, 0.298938f, -0.128094f, -0.97158f, 0.86393f, 0.270606f, -0.468986f, -0.256605f, 0.47215f, -0.273117f, -0.590343f, -0.826529f, -0.725381f, -0.194821f, -0.259661f, -0.0949207f, -0.180302f, 0.0446834f, -0.222133f, -0.40393f, 0.295772f, -0.92949f, 0.580079f, -0.169856f, 0.330311f, 0.0173551f, -0.635823f, 0.475942f, 0.907175f, 0.242777f, -0.512208f, 0.362463f, 0.0496289f, 0.65171f, 0.990057f, 0.690733f, -0.469013f, -0.101311f, -0.68372f, -0.157841f, -0.677711f, -0.708224f, -0.659437f, -0.407607f, 0.677033f, 0.89032f, 0.228307f, -0.749514f, 0.772958f, 0.054701f, 0.551705f, 0.917052f, -0.895022f, -0.702397f, 0.484142f, 0.108648f, 0.833347f, 0.478872f, -0.984112f, 0.387176f, -0.73299f, 0.7526f, 0.443312f, -0.0987856f, 0.125415f, 0.10876f, -0.498108f, 0.43209f, 0.344609f, 0.928941f, -0.130732f, -0.0569167f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.285357f, 0.00181194f, 0.453967f, -0.160473f, 0.133146f, 0.125066f, 0.695562f, 0.406415f, 0.612903f, -0.796108f, -0.221201f, 0.272369f, -0.181291f, -0.0199411f, 0.679734f, 0.729573f, 0.22086f, 0.0192072f, -0.0467102f, -0.436349f, 0.790771f, -0.0121533f, -0.102724f, -0.281631f, 0.146536f, -0.0437044f, -0.643831f, -0.125283f, -0.392138f, 0.223089f, -0.893282f, -0.16027f, -0.22558f, -0.338964f, -0.393444f, 0.447179f, 0.0027382f, 0.0600548f, 0.5614f, 0.308335f, -0.395642f, -0.232637f, -0.317546f, -0.0137323f, 0.0275952f, -0.571289f, 0.0347555f, 0.609347f, -0.446445f, 0.27283f, 0.485148f, -0.602337f, -0.250224f, 0.551432f, 0.923353f, 0.360036f, -0.394563f, -0.64193f, -0.18673f, 0.796443f, 0.266929f, 0.421638f, -0.44727f, 0.926579f, -0.22563f, 0.663612f, -0.295051f, 0.44308f, -0.680228f, 0.36995f, 0.376663f, 0.654893f, 0.289675f, 0.107439f, -0.673064f, 0.0995729f, 0.213019f, 0.18728f, -0.525372f, 0.449116f, -0.778254f, 0.82822f, 0.450766f, 0.24037f, 0.691436f, -0.357748f, 0.3905f, 0.570203f, 0.111496f, -0.553228f, 0.457363f, 0.149417f, -0.769431f, -0.470166f, -0.271529f, -0.349652f, 0.773931f, -0.135924f, 0.406866f, 0.426256f, -0.335963f, 0.680992f, -0.936889f, -3.52306e-05f, 0.575398f, 0.509084f, 0.16487f, -0.657185f, -0.321545f, -0.338165f, -0.335108f, 0.902524f, 0.133092f, -0.790369f, 0.676731f, 0.46084f, 0.489389f, 0.66835f, -0.231156f, 0.0692682f, -0.0377757f, -0.139746f, 0.105297f, 0.938753f, -0.403865f, -0.222446f, 0.45314f, 0.119956f, -0.388121f, 0.26389f, 0.27597f, 0.679432f, 0.700873f, 0.0910737f, 0.213449f, 0.0917136f, 0.0842865f, -0.0367311f, 0.214628f, 0.188827f, -0.243133f, 0.898085f, -0.271172f, 0.139627f, -0.319151f, -0.00811307f, 0.522665f, -0.459861f, -0.424081f, -0.19957f, 0.494902f, -0.169442f, -0.0407964f, -0.629691f, -0.462826f, -0.567803f, 0.453167f, 0.0473601f, 0.562038f, 0.152508f, 0.316812f, 0.582181f, 0.637157f, 0.190546f, -0.556541f, -0.860239f, -0.106728f, 0.616123f, -0.746842f, -0.0255713f, -0.453518f, -0.886067f, 0.418399f, 0.577391f, -0.467784f, -0.05079f, -0.685036f, -0.462692f, 0.460047f, -0.318271f, 0.708224f, -0.351821f, -0.364416f, 0.0954479f, -0.0586282f, -0.0894044f, 0.481278f, -0.201991f, -0.283279f, -0.897555f, 0.0611137f, 0.0467872f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/embedding_lookup_relaxed.example.cpp b/nn/runtime/test/generated/examples/embedding_lookup_relaxed.example.cpp
new file mode 100644
index 0000000..3afef6f
--- /dev/null
+++ b/nn/runtime/test/generated/examples/embedding_lookup_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: embedding_lookup_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{1, {0.0f, 0.01f, 0.02f, 0.03f, 0.1f, 0.11f, 0.12000000000000001f, 0.13f, 1.0f, 1.01f, 1.02f, 1.03f, 1.1f, 1.11f, 1.12f, 1.1300000000000001f, 2.0f, 2.01f, 2.02f, 2.03f, 2.1f, 2.11f, 2.12f, 2.13f}}},
+  // int -> INT32 map
+  {{0, {1, 0, 2}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 1.01f, 1.02f, 1.03f, 1.1f, 1.11f, 1.12f, 1.13f, 0.0f, 0.01f, 0.02f, 0.03f, 0.1f, 0.11f, 0.12f, 0.13f, 2.0f, 2.01f, 2.02f, 2.03f, 2.1f, 2.11f, 2.12f, 2.13f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/floor_relaxed.example.cpp b/nn/runtime/test/generated/examples/floor_relaxed.example.cpp
new file mode 100644
index 0000000..88519ed
--- /dev/null
+++ b/nn/runtime/test/generated/examples/floor_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: floor_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-1.5f, -1.0f, -0.5f, 0.0f, 0.5f, 1.0f, 1.5f, 10.2f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-2.0f, -1.0f, -1.0f, 0.0f, 0.0f, 1.0f, 1.0f, 10}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/fully_connected_float_relaxed.example.cpp b/nn/runtime/test/generated/examples/fully_connected_float_relaxed.example.cpp
new file mode 100644
index 0000000..95309cf
--- /dev/null
+++ b/nn/runtime/test/generated/examples/fully_connected_float_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: fully_connected_float_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {2, 32, 16}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {8, 68, 36}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/fully_connected_float_weights_as_inputs_relaxed.example.cpp b/nn/runtime/test/generated/examples/fully_connected_float_weights_as_inputs_relaxed.example.cpp
new file mode 100644
index 0000000..2baa63f
--- /dev/null
+++ b/nn/runtime/test/generated/examples/fully_connected_float_weights_as_inputs_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: fully_connected_float_weights_as_inputs_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {2, 32, 16}}, {1, {2}}, {2, {4}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {8, 68, 36}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/hashtable_lookup_float_relaxed.example.cpp b/nn/runtime/test/generated/examples/hashtable_lookup_float_relaxed.example.cpp
new file mode 100644
index 0000000..da7fae9
--- /dev/null
+++ b/nn/runtime/test/generated/examples/hashtable_lookup_float_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: hashtable_lookup_float_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{2, {0.0f, 0.1f, 1.0f, 1.1f, 2.0f, 2.1f}}},
+  // int -> INT32 map
+  {{0, {1234, -292, -11, 0}}, {1, {-11, 0, 1234}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {2.0f, 2.1f, 0, 0, 0.0f, 0.1f, 1.0f, 1.1f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {{1, {1, 0, 1, 1}}}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/l2_normalization_large_relaxed.example.cpp b/nn/runtime/test/generated/examples/l2_normalization_large_relaxed.example.cpp
new file mode 100644
index 0000000..97a734d
--- /dev/null
+++ b/nn/runtime/test/generated/examples/l2_normalization_large_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: l2_normalization_large_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 3, 4, 0, 5, 12, 0, 8, 15, 0, 7, 24}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 0.6f, 0.8f, 0, 0.38461539149284363f, 0.9230769872665405f, 0, 0.47058823704719543f, 0.8823529481887817f, 0, 0.28f, 0.96f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/l2_normalization_relaxed.example.cpp b/nn/runtime/test/generated/examples/l2_normalization_relaxed.example.cpp
new file mode 100644
index 0000000..72be16a
--- /dev/null
+++ b/nn/runtime/test/generated/examples/l2_normalization_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: l2_normalization_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 3, 4}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 0.6f, 0.8f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/l2_pool_float_relaxed.example.cpp b/nn/runtime/test/generated/examples/l2_pool_float_relaxed.example.cpp
new file mode 100644
index 0000000..684eac6
--- /dev/null
+++ b/nn/runtime/test/generated/examples/l2_pool_float_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: l2_pool_float_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/local_response_norm_float_1_relaxed.example.cpp b/nn/runtime/test/generated/examples/local_response_norm_float_1_relaxed.example.cpp
new file mode 100644
index 0000000..d708482
--- /dev/null
+++ b/nn/runtime/test/generated/examples/local_response_norm_float_1_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: local_response_norm_float_1_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-1.1f, 0.6f, 0.7f, 1.2f, -0.7f, 0.1f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.22f, 0.12f, 0.14f, 0.24f, -0.14f, 0.02f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/local_response_norm_float_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/local_response_norm_float_2_relaxed.example.cpp
new file mode 100644
index 0000000..0500b0f
--- /dev/null
+++ b/nn/runtime/test/generated/examples/local_response_norm_float_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: local_response_norm_float_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-1.1f, 0.6f, 0.7f, 1.2f, -0.7f, 0.1f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.55f, 0.3f, 0.35f, 0.6f, -0.35f, 0.05f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/local_response_norm_float_3_relaxed.example.cpp b/nn/runtime/test/generated/examples/local_response_norm_float_3_relaxed.example.cpp
new file mode 100644
index 0000000..9c4c893
--- /dev/null
+++ b/nn/runtime/test/generated/examples/local_response_norm_float_3_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: local_response_norm_float_3_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-1.1f, 0.6f, 0.7f, 1.2f, -0.7f, 0.1f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.275f, 0.15f, 0.175f, 0.3f, -0.175f, 0.025f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/local_response_norm_float_4_relaxed.example.cpp b/nn/runtime/test/generated/examples/local_response_norm_float_4_relaxed.example.cpp
new file mode 100644
index 0000000..2d57c8e
--- /dev/null
+++ b/nn/runtime/test/generated/examples/local_response_norm_float_4_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: local_response_norm_float_4_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-1.1f, 0.6f, 0.7f, 1.2f, -0.7f, 0.1f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.26492569f, 0.12510864f, 0.14011213f, 0.26726127f, -0.16178755f, 0.0244266f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/logistic_float_1_relaxed.example.cpp b/nn/runtime/test/generated/examples/logistic_float_1_relaxed.example.cpp
new file mode 100644
index 0000000..557c1fe
--- /dev/null
+++ b/nn/runtime/test/generated/examples/logistic_float_1_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: logistic_float_1_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 4.0f, 8.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.7310585975646973f, 0.8807970285415649f, 0.9820137619972229f, 0.9996646642684937f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/logistic_float_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/logistic_float_2_relaxed.example.cpp
new file mode 100644
index 0000000..bc52eac
--- /dev/null
+++ b/nn/runtime/test/generated/examples/logistic_float_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: logistic_float_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.0f, 1.0f, 510.0f, 3.0f, 508.0f, 5.0f, 506.0f, 7.0f, 504.0f, 9.0f, 502.0f, 11.0f, 500.0f, 13.0f, 498.0f, 15.0f, 496.0f, 17.0f, 494.0f, 19.0f, 492.0f, 21.0f, 490.0f, 23.0f, 488.0f, 25.0f, 486.0f, 27.0f, 484.0f, 29.0f, 482.0f, 31.0f, 480.0f, 33.0f, 478.0f, 35.0f, 476.0f, 37.0f, 474.0f, 39.0f, 472.0f, 41.0f, 470.0f, 43.0f, 468.0f, 45.0f, 466.0f, 47.0f, 464.0f, 49.0f, 462.0f, 51.0f, 460.0f, 53.0f, 458.0f, 55.0f, 456.0f, 57.0f, 454.0f, 59.0f, 452.0f, 61.0f, 450.0f, 63.0f, 448.0f, 65.0f, 446.0f, 67.0f, 444.0f, 69.0f, 442.0f, 71.0f, 440.0f, 73.0f, 438.0f, 75.0f, 436.0f, 77.0f, 434.0f, 79.0f, 432.0f, 81.0f, 430.0f, 83.0f, 428.0f, 85.0f, 426.0f, 87.0f, 424.0f, 89.0f, 422.0f, 91.0f, 420.0f, 93.0f, 418.0f, 95.0f, 416.0f, 97.0f, 414.0f, 99.0f, 412.0f, 101.0f, 410.0f, 103.0f, 408.0f, 105.0f, 406.0f, 107.0f, 404.0f, 109.0f, 402.0f, 111.0f, 400.0f, 113.0f, 398.0f, 115.0f, 396.0f, 117.0f, 394.0f, 119.0f, 392.0f, 121.0f, 390.0f, 123.0f, 388.0f, 125.0f, 386.0f, 127.0f, 384.0f, 129.0f, 382.0f, 131.0f, 380.0f, 133.0f, 378.0f, 135.0f, 376.0f, 137.0f, 374.0f, 139.0f, 372.0f, 141.0f, 370.0f, 143.0f, 368.0f, 145.0f, 366.0f, 147.0f, 364.0f, 149.0f, 362.0f, 151.0f, 360.0f, 153.0f, 358.0f, 155.0f, 356.0f, 157.0f, 354.0f, 159.0f, 352.0f, 161.0f, 350.0f, 163.0f, 348.0f, 165.0f, 346.0f, 167.0f, 344.0f, 169.0f, 342.0f, 171.0f, 340.0f, 173.0f, 338.0f, 175.0f, 336.0f, 177.0f, 334.0f, 179.0f, 332.0f, 181.0f, 330.0f, 183.0f, 328.0f, 185.0f, 326.0f, 187.0f, 324.0f, 189.0f, 322.0f, 191.0f, 320.0f, 193.0f, 318.0f, 195.0f, 316.0f, 197.0f, 314.0f, 199.0f, 312.0f, 201.0f, 310.0f, 203.0f, 308.0f, 205.0f, 306.0f, 207.0f, 304.0f, 209.0f, 302.0f, 211.0f, 300.0f, 213.0f, 298.0f, 215.0f, 296.0f, 217.0f, 294.0f, 219.0f, 292.0f, 221.0f, 290.0f, 223.0f, 288.0f, 225.0f, 286.0f, 227.0f, 284.0f, 229.0f, 282.0f, 231.0f, 280.0f, 233.0f, 278.0f, 235.0f, 276.0f, 237.0f, 274.0f, 239.0f, 272.0f, 241.0f, 270.0f, 243.0f, 268.0f, 245.0f, 266.0f, 247.0f, 264.0f, 249.0f, 262.0f, 251.0f, 260.0f, 253.0f, 258.0f, 255.0f, 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381.0f, 130.0f, 383.0f, 128.0f, 385.0f, 126.0f, 387.0f, 124.0f, 389.0f, 122.0f, 391.0f, 120.0f, 393.0f, 118.0f, 395.0f, 116.0f, 397.0f, 114.0f, 399.0f, 112.0f, 401.0f, 110.0f, 403.0f, 108.0f, 405.0f, 106.0f, 407.0f, 104.0f, 409.0f, 102.0f, 411.0f, 100.0f, 413.0f, 98.0f, 415.0f, 96.0f, 417.0f, 94.0f, 419.0f, 92.0f, 421.0f, 90.0f, 423.0f, 88.0f, 425.0f, 86.0f, 427.0f, 84.0f, 429.0f, 82.0f, 431.0f, 80.0f, 433.0f, 78.0f, 435.0f, 76.0f, 437.0f, 74.0f, 439.0f, 72.0f, 441.0f, 70.0f, 443.0f, 68.0f, 445.0f, 66.0f, 447.0f, 64.0f, 449.0f, 62.0f, 451.0f, 60.0f, 453.0f, 58.0f, 455.0f, 56.0f, 457.0f, 54.0f, 459.0f, 52.0f, 461.0f, 50.0f, 463.0f, 48.0f, 465.0f, 46.0f, 467.0f, 44.0f, 469.0f, 42.0f, 471.0f, 40.0f, 473.0f, 38.0f, 475.0f, 36.0f, 477.0f, 34.0f, 479.0f, 32.0f, 481.0f, 30.0f, 483.0f, 28.0f, 485.0f, 26.0f, 487.0f, 24.0f, 489.0f, 22.0f, 491.0f, 20.0f, 493.0f, 18.0f, 495.0f, 16.0f, 497.0f, 14.0f, 499.0f, 12.0f, 501.0f, 10.0f, 503.0f, 8.0f, 505.0f, 6.0f, 507.0f, 4.0f, 509.0f, 2.0f, 511.0f, 0.0f, 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120.0f, 393.0f, 118.0f, 395.0f, 116.0f, 397.0f, 114.0f, 399.0f, 112.0f, 401.0f, 110.0f, 403.0f, 108.0f, 405.0f, 106.0f, 407.0f, 104.0f, 409.0f, 102.0f, 411.0f, 100.0f, 413.0f, 98.0f, 415.0f, 96.0f, 417.0f, 94.0f, 419.0f, 92.0f, 421.0f, 90.0f, 423.0f, 88.0f, 425.0f, 86.0f, 427.0f, 84.0f, 429.0f, 82.0f, 431.0f, 80.0f, 433.0f, 78.0f, 435.0f, 76.0f, 437.0f, 74.0f, 439.0f, 72.0f, 441.0f, 70.0f, 443.0f, 68.0f, 445.0f, 66.0f, 447.0f, 64.0f, 449.0f, 62.0f, 451.0f, 60.0f, 453.0f, 58.0f, 455.0f, 56.0f, 457.0f, 54.0f, 459.0f, 52.0f, 461.0f, 50.0f, 463.0f, 48.0f, 465.0f, 46.0f, 467.0f, 44.0f, 469.0f, 42.0f, 471.0f, 40.0f, 473.0f, 38.0f, 475.0f, 36.0f, 477.0f, 34.0f, 479.0f, 32.0f, 481.0f, 30.0f, 483.0f, 28.0f, 485.0f, 26.0f, 487.0f, 24.0f, 489.0f, 22.0f, 491.0f, 20.0f, 493.0f, 18.0f, 495.0f, 16.0f, 497.0f, 14.0f, 499.0f, 12.0f, 501.0f, 10.0f, 503.0f, 8.0f, 505.0f, 6.0f, 507.0f, 4.0f, 509.0f, 2.0f, 511.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.5f, 0.7310585786300049f, 1.0f, 0.9525741268224334f, 1.0f, 0.9933071490757153f, 1.0f, 0.9990889488055994f, 1.0f, 0.9998766054240137f, 1.0f, 0.999983298578152f, 1.0f, 0.999997739675702f, 1.0f, 0.999999694097773f, 1.0f, 0.9999999586006244f, 1.0f, 0.9999999943972036f, 1.0f, 0.9999999992417439f, 1.0f, 0.9999999998973812f, 1.0f, 0.999999999986112f, 1.0f, 0.9999999999981204f, 1.0f, 0.9999999999997455f, 1.0f, 0.9999999999999656f, 1.0f, 0.9999999999999953f, 1.0f, 0.9999999999999993f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 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0.9999998874648379f, 1.0f, 0.9999991684719722f, 1.0f, 0.9999938558253978f, 1.0f, 0.9999546021312976f, 1.0f, 0.9996646498695336f, 1.0f, 0.9975273768433653f, 1.0f, 0.9820137900379085f, 1.0f, 0.8807970779778823f, 1.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/lsh_projection_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/lsh_projection_2_relaxed.example.cpp
new file mode 100644
index 0000000..0c94e8c
--- /dev/null
+++ b/nn/runtime/test/generated/examples/lsh_projection_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: lsh_projection_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{1, {}}},
+  // int -> INT32 map
+  {{0, {12345, 54321, 67890, 9876, -12345678, -87654321}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {},
+  // int -> INT32 map
+  {{0, {1, 2, 2, 0}}},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/lsh_projection_relaxed.example.cpp b/nn/runtime/test/generated/examples/lsh_projection_relaxed.example.cpp
new file mode 100644
index 0000000..341c72e
--- /dev/null
+++ b/nn/runtime/test/generated/examples/lsh_projection_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: lsh_projection_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{1, {0.12f, 0.34f, 0.56f}}},
+  // int -> INT32 map
+  {{0, {12345, 54321, 67890, 9876, -12345678, -87654321}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {},
+  // int -> INT32 map
+  {{0, {1, 1, 1, 0, 1, 1, 1, 0}}},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/lsh_projection_weights_as_inputs_relaxed.example.cpp b/nn/runtime/test/generated/examples/lsh_projection_weights_as_inputs_relaxed.example.cpp
new file mode 100644
index 0000000..4e6b754
--- /dev/null
+++ b/nn/runtime/test/generated/examples/lsh_projection_weights_as_inputs_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: lsh_projection_weights_as_inputs_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.123f, 0.456f, -0.321f, -0.654f, 1.234f, 5.678f, -4.321f, -8.765f}}, {2, {0.12f, 0.34f, 0.56f}}},
+  // int -> INT32 map
+  {{1, {12345, 54321, 67890, 9876, -12345678, -87654321}}, {3, {2}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {},
+  // int -> INT32 map
+  {{0, {1, 1, 1, 0, 1, 1, 1, 0}}},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/lstm2_relaxed.example.cpp b/nn/runtime/test/generated/examples/lstm2_relaxed.example.cpp
new file mode 100644
index 0000000..4b79fb1
--- /dev/null
+++ b/nn/runtime/test/generated/examples/lstm2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: lstm2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {2.0f, 3.0f}}, {1, {}}, {2, {-0.55291498f, -0.42866567f, 0.13056988f, -0.3633365f, -0.22755712f, 0.28253698f, 0.24407166f, 0.33826375f}}, {3, {-0.49770179f, -0.27711356f, -0.09624726f, 0.05100781f, 0.04717243f, 0.48944736f, -0.38535351f, -0.17212132f}}, {4, {0.10725588f, -0.02335852f, -0.55932593f, -0.09426838f, -0.44257352f, 0.54939759f, 0.01533556f, 0.42751634f}}, {5, {}}, {6, {-0.13832897f, -0.0515101f, -0.2359007f, -0.16661474f, -0.14340827f, 0.36986142f, 0.23414481f, 0.55899f, 0.10798943f, -0.41174671f, 0.17751795f, -0.34484994f, -0.35874045f, -0.11352962f, 0.27268326f, 0.54058349f}}, {7, {0.54066205f, -0.32668582f, -0.43562764f, -0.56094903f, 0.42957711f, 0.01841056f, -0.32764608f, -0.33027974f, -0.10826075f, 0.20675004f, 0.19069612f, -0.03026325f, -0.54532051f, 0.33003211f, 0.44901288f, 0.21193194f}}, {8, {0.41613156f, 0.42610586f, -0.16495961f, -0.5663873f, 0.30579174f, -0.05115908f, -0.33941799f, 0.23364776f, 0.11178309f, 0.09481031f, -0.26424935f, 0.46261835f, 0.50248802f, 0.26114327f, -0.43736315f, 0.33149987f}}, {9, {}}, {10, {0.47485286f, -0.51955009f, -0.24458408f, 0.31544167f}}, {11, {-0.17135078f, 0.82760304f, 0.85573703f, -0.77109635f}}, {12, {}}, {13, {1.0f, 1.0f, 1.0f, 1.0f}}, {14, {0.0f, 0.0f, 0.0f, 0.0f}}, {15, {0.0f, 0.0f, 0.0f, 0.0f}}, {16, {}}, {17, {}}, {18, {0, 0, 0, 0}}, {19, {0, 0, 0, 0}}, {21, {0.0f}}, {22, {0.0f}}},
+  // int -> INT32 map
+  {{20, {4}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{1, {-0.364445f, -0.00352185f, 0.128866f, -0.0516365f}}, {2, {-0.760444f, -0.0180416f, 0.182264f, -0.0649371f}}, {3, {-0.36444446f, -0.00352185f, 0.12886585f, -0.05163646f}}, {0, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/lstm2_state2_relaxed.example.cpp b/nn/runtime/test/generated/examples/lstm2_state2_relaxed.example.cpp
new file mode 100644
index 0000000..6b8fe96
--- /dev/null
+++ b/nn/runtime/test/generated/examples/lstm2_state2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: lstm2_state2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 1.0f}}, {1, {}}, {2, {-0.55291498f, -0.42866567f, 0.13056988f, -0.3633365f, -0.22755712f, 0.28253698f, 0.24407166f, 0.33826375f}}, {3, {-0.49770179f, -0.27711356f, -0.09624726f, 0.05100781f, 0.04717243f, 0.48944736f, -0.38535351f, -0.17212132f}}, {4, {0.10725588f, -0.02335852f, -0.55932593f, -0.09426838f, -0.44257352f, 0.54939759f, 0.01533556f, 0.42751634f}}, {5, {}}, {6, {-0.13832897f, -0.0515101f, -0.2359007f, -0.16661474f, -0.14340827f, 0.36986142f, 0.23414481f, 0.55899f, 0.10798943f, -0.41174671f, 0.17751795f, -0.34484994f, -0.35874045f, -0.11352962f, 0.27268326f, 0.54058349f}}, {7, {0.54066205f, -0.32668582f, -0.43562764f, -0.56094903f, 0.42957711f, 0.01841056f, -0.32764608f, -0.33027974f, -0.10826075f, 0.20675004f, 0.19069612f, -0.03026325f, -0.54532051f, 0.33003211f, 0.44901288f, 0.21193194f}}, {8, {0.41613156f, 0.42610586f, -0.16495961f, -0.5663873f, 0.30579174f, -0.05115908f, -0.33941799f, 0.23364776f, 0.11178309f, 0.09481031f, -0.26424935f, 0.46261835f, 0.50248802f, 0.26114327f, -0.43736315f, 0.33149987f}}, {9, {}}, {10, {0.47485286f, -0.51955009f, -0.24458408f, 0.31544167f}}, {11, {-0.17135078f, 0.82760304f, 0.85573703f, -0.77109635f}}, {12, {}}, {13, {1.0f, 1.0f, 1.0f, 1.0f}}, {14, {0.0f, 0.0f, 0.0f, 0.0f}}, {15, {0.0f, 0.0f, 0.0f, 0.0f}}, {16, {}}, {17, {}}, {18, {-0.423122f, -0.0121822f, 0.24201f, -0.0812458f}}, {19, {-0.978419f, -0.139203f, 0.338163f, -0.0983904f}}, {21, {0.0f}}, {22, {0.0f}}},
+  // int -> INT32 map
+  {{20, {4}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{1, {0, 0, 0, 0}}, {2, {0, 0, 0, 0}}, {3, {-0.358325f, -0.04621704f, 0.21641694f, -0.06471302f}}, {0, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/lstm2_state_relaxed.example.cpp b/nn/runtime/test/generated/examples/lstm2_state_relaxed.example.cpp
new file mode 100644
index 0000000..353f9ba
--- /dev/null
+++ b/nn/runtime/test/generated/examples/lstm2_state_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: lstm2_state_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {3.0f, 4.0f}}, {1, {}}, {2, {-0.55291498f, -0.42866567f, 0.13056988f, -0.3633365f, -0.22755712f, 0.28253698f, 0.24407166f, 0.33826375f}}, {3, {-0.49770179f, -0.27711356f, -0.09624726f, 0.05100781f, 0.04717243f, 0.48944736f, -0.38535351f, -0.17212132f}}, {4, {0.10725588f, -0.02335852f, -0.55932593f, -0.09426838f, -0.44257352f, 0.54939759f, 0.01533556f, 0.42751634f}}, {5, {}}, {6, {-0.13832897f, -0.0515101f, -0.2359007f, -0.16661474f, -0.14340827f, 0.36986142f, 0.23414481f, 0.55899f, 0.10798943f, -0.41174671f, 0.17751795f, -0.34484994f, -0.35874045f, -0.11352962f, 0.27268326f, 0.54058349f}}, {7, {0.54066205f, -0.32668582f, -0.43562764f, -0.56094903f, 0.42957711f, 0.01841056f, -0.32764608f, -0.33027974f, -0.10826075f, 0.20675004f, 0.19069612f, -0.03026325f, -0.54532051f, 0.33003211f, 0.44901288f, 0.21193194f}}, {8, {0.41613156f, 0.42610586f, -0.16495961f, -0.5663873f, 0.30579174f, -0.05115908f, -0.33941799f, 0.23364776f, 0.11178309f, 0.09481031f, -0.26424935f, 0.46261835f, 0.50248802f, 0.26114327f, -0.43736315f, 0.33149987f}}, {9, {}}, {10, {0.47485286f, -0.51955009f, -0.24458408f, 0.31544167f}}, {11, {-0.17135078f, 0.82760304f, 0.85573703f, -0.77109635f}}, {12, {}}, {13, {1.0f, 1.0f, 1.0f, 1.0f}}, {14, {0.0f, 0.0f, 0.0f, 0.0f}}, {15, {0.0f, 0.0f, 0.0f, 0.0f}}, {16, {}}, {17, {}}, {18, {-0.364445f, -0.00352185f, 0.128866f, -0.0516365f}}, {19, {-0.760444f, -0.0180416f, 0.182264f, -0.0649371f}}, {21, {0.0f}}, {22, {0.0f}}},
+  // int -> INT32 map
+  {{20, {4}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{1, {-0.423122f, -0.0121822f, 0.24201f, -0.0812458f}}, {2, {-0.978419f, -0.139203f, 0.338163f, -0.0983904f}}, {3, {-0.42312205f, -0.01218222f, 0.24201041f, -0.08124574f}}, {0, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/lstm3_relaxed.example.cpp b/nn/runtime/test/generated/examples/lstm3_relaxed.example.cpp
new file mode 100644
index 0000000..129c626
--- /dev/null
+++ b/nn/runtime/test/generated/examples/lstm3_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: lstm3_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.787926f, 0.151646f, 0.071352f, 0.118426f, 0.458058f, 0.295743f, 0.544053f, 0.690064f, 0.858138f, 0.497181f}}, {1, {0.021393683f, 0.06124551f, 0.046905167f, -0.014657677f, -0.03149463f, 0.09171803f, 0.14647801f, 0.10797193f, -0.0057968358f, 0.0019193048f, -0.2726754f, 0.10154029f, -0.018539885f, 0.080349885f, -0.10262385f, -0.022599787f, -0.09121155f, -0.008675967f, -0.045206103f, -0.0821282f, -0.008045952f, 0.015478081f, 0.055217247f, 0.038719587f, 0.044153627f, -0.06453243f, 0.05031825f, -0.046935108f, -0.008164439f, 0.014574226f, -0.1671009f, -0.15519552f, -0.16819797f, -0.13971269f, -0.11953059f, 0.25005487f, -0.22790983f, 0.009855087f, -0.028140958f, -0.11200698f, 0.11295408f, -0.0035217577f, 0.054485075f, 0.05184695f, 0.064711206f, 0.10989193f, 0.11674786f, 0.03490607f, 0.07727357f, 0.11390585f, -0.1863375f, -0.1034451f, -0.13945189f, -0.049401227f, -0.18767063f, 0.042483903f, 0.14233552f, 0.13832581f, 0.18350165f, 0.14545603f, -0.028545704f, 0.024939531f, 0.050929718f, 0.0076203286f, -0.0029723682f, -0.042484224f, -0.11827596f, -0.09171104f, -0.10808628f, -0.16327988f, -0.2273378f, -0.0993647f, -0.017155107f, 0.0023917493f, 0.049272764f, 0.0038534778f, 0.054764505f, 0.089753784f, 0.06947234f, 0.08014476f, -0.04544234f, -0.0497073f, -0.07135631f, -0.048929106f, -0.004042012f, -0.009284026f, 0.018042054f, 0.0036860977f, -0.07427302f, -0.11434604f, -0.018995456f, 0.031487543f, 0.012834908f, 0.019977754f, 0.044256654f, -0.39292613f, -0.18519334f, -0.11651281f, -0.06809892f, 0.011373677f}}, {2, {-0.0018401089f, -0.004852237f, 0.03698424f, 0.014181704f, 0.028273236f, -0.016726194f, -0.05249759f, -0.10204261f, 0.00861066f, -0.040979505f, -0.009899187f, 0.01923892f, -0.028177269f, -0.08535103f, -0.14585495f, 0.10662567f, -0.01909731f, -0.017883534f, -0.0047269356f, -0.045103323f, 0.0030784295f, 0.076784775f, 0.07463696f, 0.094531395f, 0.0814421f, -0.12257899f, -0.033945758f, -0.031303465f, 0.045630626f, 0.06843887f, -0.13492945f, -0.012480007f, -0.0811829f, -0.07224499f, -0.09628791f, 0.045100946f, 0.0012300825f, 0.013964662f, 0.099372394f, 0.02543059f, 0.06958324f, 0.034257296f, 0.0482646f, 0.06267997f, 0.052625068f, 0.12784666f, 0.07077897f, 0.025725935f, 0.04165009f, 0.07241905f, 0.018668644f, -0.037377294f, -0.06277783f, -0.08833636f, -0.040120605f, -0.011405586f, -0.007808335f, -0.010301386f, -0.005102167f, 0.027717464f, 0.05483423f, 0.11449111f, 0.11289652f, 0.10939839f, 0.13396506f, -0.08402166f, -0.01901462f, -0.044678304f, -0.07720565f, 0.014350063f, -0.11757958f, -0.0652038f, -0.08185733f, -0.076754324f, -0.092614375f, 0.10405491f, 0.052960336f, 0.035755895f, 0.035839386f, -0.012540553f, 0.036881298f, 0.02913376f, 0.03420159f, 0.05448447f, -0.054523353f, 0.02582715f, 0.02327355f, -0.011857179f, -0.0011980024f, -0.034641717f, -0.026125094f, -0.17582615f, -0.15923657f, -0.27486774f, -0.0006143371f, 0.0001771948f, -8.470171e-05f, 0.02651807f, 0.045790765f, 0.06956496f}}, {3, {-0.04580283f, -0.09549462f, -0.032418985f, -0.06454633f, -0.043528453f, 0.043018587f, -0.049152344f, -0.12418144f, -0.078985475f, -0.07596889f, 0.019484362f, -0.11434962f, -0.0074034138f, -0.06314844f, -0.092981495f, 0.0062155537f, -0.025034338f, -0.0028890965f, 0.048929527f, 0.06235075f, 0.10665918f, -0.032036792f, -0.08505916f, -0.10843358f, -0.13002433f, -0.036816437f, -0.02130134f, -0.016518239f, 0.0047691227f, -0.0025825808f, 0.066017866f, 0.029991534f, -0.10652836f, -0.1037554f, -0.13056071f, -0.03266643f, -0.033702414f, -0.006473424f, -0.04611692f, 0.014419339f, -0.025174323f, 0.0396852f, 0.081777506f, 0.06157468f, 0.10210095f, -0.009658194f, 0.046511717f, 0.03603906f, 0.0069369148f, 0.015960095f, -0.06507666f, 0.09551598f, 0.053568836f, 0.06408714f, 0.12835667f, -0.008714329f, -0.20211966f, -0.12093674f, 0.029450472f, 0.2849013f, -0.029227901f, 0.1164364f, -0.08560263f, 0.09941786f, -0.036999565f, -0.028842626f, -0.0033637602f, -0.017012902f, -0.09720865f, -0.11193351f, -0.029155117f, -0.017936034f, -0.009768936f, -0.04223324f, -0.036159635f, 0.06505112f, -0.021742892f, -0.023377212f, -0.07221364f, -0.06430552f, 0.05453865f, 0.091149814f, 0.06387331f, 0.007518393f, 0.055960953f, 0.069779344f, 0.046411168f, 0.10509911f, 0.07463894f, 0.0075130584f, 0.012850982f, 0.04555431f, 0.056955688f, 0.06555285f, 0.050801456f, -0.009862683f, 0.00826772f, -0.026555609f, -0.0073611983f, -0.0014897042f}}, {4, {-0.0998932f, -0.07201956f, -0.052803773f, -0.15629593f, -0.15001918f, -0.07650751f, 0.02359855f, -0.075155355f, -0.08037709f, -0.15093534f, 0.029517552f, -0.04751393f, 0.010350531f, -0.02664851f, -0.016839722f, -0.023121163f, 0.0077019283f, 0.012851257f, -0.05040649f, -0.0129761f, -0.021737747f, -0.038305793f, -0.06870586f, -0.01481247f, -0.001285394f, 0.10124236f, 0.083122835f, 0.053313006f, -0.062235646f, -0.075637154f, -0.027833903f, 0.029774971f, 0.1130802f, 0.09218906f, 0.09506135f, -0.086665764f, -0.037162706f, -0.038880914f, -0.035832845f, -0.014481564f, -0.09825003f, -0.12048569f, -0.097665586f, -0.05287633f, 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+  // int -> INT32 map
+  {{20, {4}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{1, {-0.00396806f, 0.029352f, -0.00279226f, 0.0159977f, -0.00835577f, -0.0211779f, 0.0283512f, -0.0114597f, 0.00907307f, -0.0244004f, -0.0152191f, -0.0259063f, 0.00914318f, 0.00415119f, 0.017147f, 0.0134203f, -0.013869f, 0.0287268f, -0.00334694f, 0.00733397f, -0.0287926f, -0.0186926f, 0.0193662f, -0.0115437f, 0.00422612f, -0.0345232f, 0.00223253f, -0.00957321f, 0.0210624f, 0.013331f, 0.0150954f, 0.0216801f}}, {2, {-0.0531632f, -0.0118138f, 0.0870833f, 0.0347929f, -0.076144f, -0.0659219f, -0.0463811f, 0.0141307f, -0.0127706f, -0.03782f, -0.00402401f, -0.00571876f, -0.187957f, -0.0247127f, 0.0711425f, 0.008244f, 0.0492649f, 0.126972f, 0.0933097f, 0.29848f, -0.0966178f, -0.114417f, 0.0387229f, 0.0453255f, -0.181286f, -0.0651251f, -0.0996879f, -0.00276995f, 0.0617558f, -0.0100728f, 0.056304f, -0.077416f, -0.162858f, -0.0541251f, 0.0571202f, -0.0525331f, 0.0724297f, 0.171029f, 0.141738f, 0.295483f}}, {3, {-0.00396806f, 0.029352f, -0.00279226f, 0.0159977f, -0.00835576f, -0.0211779f, 0.0283512f, -0.0114597f, 0.00907307f, -0.0244004f, -0.0152191f, -0.0259063f, 0.00914318f, 0.00415118f, 0.017147f, 0.0134203f, -0.013869f, 0.0287268f, -0.00334693f, 0.00733398f, -0.0287926f, -0.0186926f, 0.0193662f, -0.0115437f, 0.00422612f, -0.0345232f, 0.00223253f, -0.00957321f, 0.0210624f, 0.013331f, 0.0150954f, 0.02168f}}, {0, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/lstm3_state2_relaxed.example.cpp b/nn/runtime/test/generated/examples/lstm3_state2_relaxed.example.cpp
new file mode 100644
index 0000000..c8c0d96
--- /dev/null
+++ b/nn/runtime/test/generated/examples/lstm3_state2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: lstm3_state2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.073204f, 0.296072f, 0.743333f, 0.069199f, 0.045348f, 0.640394f, 0.930399f, 0.050782f, 0.432485f, 0.988078f}}, {1, {0.021393683f, 0.06124551f, 0.046905167f, -0.014657677f, -0.03149463f, 0.09171803f, 0.14647801f, 0.10797193f, -0.0057968358f, 0.0019193048f, -0.2726754f, 0.10154029f, -0.018539885f, 0.080349885f, -0.10262385f, -0.022599787f, -0.09121155f, -0.008675967f, -0.045206103f, -0.0821282f, -0.008045952f, 0.015478081f, 0.055217247f, 0.038719587f, 0.044153627f, -0.06453243f, 0.05031825f, -0.046935108f, -0.008164439f, 0.014574226f, -0.1671009f, -0.15519552f, -0.16819797f, -0.13971269f, -0.11953059f, 0.25005487f, -0.22790983f, 0.009855087f, -0.028140958f, -0.11200698f, 0.11295408f, -0.0035217577f, 0.054485075f, 0.05184695f, 0.064711206f, 0.10989193f, 0.11674786f, 0.03490607f, 0.07727357f, 0.11390585f, -0.1863375f, -0.1034451f, -0.13945189f, -0.049401227f, -0.18767063f, 0.042483903f, 0.14233552f, 0.13832581f, 0.18350165f, 0.14545603f, -0.028545704f, 0.024939531f, 0.050929718f, 0.0076203286f, -0.0029723682f, -0.042484224f, -0.11827596f, -0.09171104f, -0.10808628f, -0.16327988f, -0.2273378f, -0.0993647f, -0.017155107f, 0.0023917493f, 0.049272764f, 0.0038534778f, 0.054764505f, 0.089753784f, 0.06947234f, 0.08014476f, -0.04544234f, -0.0497073f, -0.07135631f, -0.048929106f, -0.004042012f, -0.009284026f, 0.018042054f, 0.0036860977f, -0.07427302f, -0.11434604f, -0.018995456f, 0.031487543f, 0.012834908f, 0.019977754f, 0.044256654f, -0.39292613f, -0.18519334f, -0.11651281f, -0.06809892f, 0.011373677f}}, {2, {-0.0018401089f, -0.004852237f, 0.03698424f, 0.014181704f, 0.028273236f, -0.016726194f, -0.05249759f, -0.10204261f, 0.00861066f, -0.040979505f, -0.009899187f, 0.01923892f, -0.028177269f, -0.08535103f, -0.14585495f, 0.10662567f, -0.01909731f, -0.017883534f, -0.0047269356f, -0.045103323f, 0.0030784295f, 0.076784775f, 0.07463696f, 0.094531395f, 0.0814421f, -0.12257899f, -0.033945758f, -0.031303465f, 0.045630626f, 0.06843887f, -0.13492945f, -0.012480007f, -0.0811829f, -0.07224499f, -0.09628791f, 0.045100946f, 0.0012300825f, 0.013964662f, 0.099372394f, 0.02543059f, 0.06958324f, 0.034257296f, 0.0482646f, 0.06267997f, 0.052625068f, 0.12784666f, 0.07077897f, 0.025725935f, 0.04165009f, 0.07241905f, 0.018668644f, -0.037377294f, -0.06277783f, -0.08833636f, -0.040120605f, -0.011405586f, -0.007808335f, -0.010301386f, -0.005102167f, 0.027717464f, 0.05483423f, 0.11449111f, 0.11289652f, 0.10939839f, 0.13396506f, -0.08402166f, -0.01901462f, -0.044678304f, -0.07720565f, 0.014350063f, -0.11757958f, -0.0652038f, -0.08185733f, -0.076754324f, -0.092614375f, 0.10405491f, 0.052960336f, 0.035755895f, 0.035839386f, -0.012540553f, 0.036881298f, 0.02913376f, 0.03420159f, 0.05448447f, -0.054523353f, 0.02582715f, 0.02327355f, -0.011857179f, -0.0011980024f, -0.034641717f, -0.026125094f, -0.17582615f, -0.15923657f, -0.27486774f, -0.0006143371f, 0.0001771948f, -8.470171e-05f, 0.02651807f, 0.045790765f, 0.06956496f}}, {3, {-0.04580283f, -0.09549462f, -0.032418985f, -0.06454633f, -0.043528453f, 0.043018587f, -0.049152344f, -0.12418144f, -0.078985475f, -0.07596889f, 0.019484362f, -0.11434962f, -0.0074034138f, -0.06314844f, -0.092981495f, 0.0062155537f, -0.025034338f, -0.0028890965f, 0.048929527f, 0.06235075f, 0.10665918f, -0.032036792f, -0.08505916f, -0.10843358f, -0.13002433f, -0.036816437f, -0.02130134f, -0.016518239f, 0.0047691227f, -0.0025825808f, 0.066017866f, 0.029991534f, -0.10652836f, -0.1037554f, -0.13056071f, -0.03266643f, -0.033702414f, -0.006473424f, -0.04611692f, 0.014419339f, -0.025174323f, 0.0396852f, 0.081777506f, 0.06157468f, 0.10210095f, -0.009658194f, 0.046511717f, 0.03603906f, 0.0069369148f, 0.015960095f, -0.06507666f, 0.09551598f, 0.053568836f, 0.06408714f, 0.12835667f, -0.008714329f, -0.20211966f, -0.12093674f, 0.029450472f, 0.2849013f, -0.029227901f, 0.1164364f, -0.08560263f, 0.09941786f, -0.036999565f, -0.028842626f, -0.0033637602f, -0.017012902f, -0.09720865f, -0.11193351f, -0.029155117f, -0.017936034f, -0.009768936f, -0.04223324f, -0.036159635f, 0.06505112f, -0.021742892f, -0.023377212f, -0.07221364f, -0.06430552f, 0.05453865f, 0.091149814f, 0.06387331f, 0.007518393f, 0.055960953f, 0.069779344f, 0.046411168f, 0.10509911f, 0.07463894f, 0.0075130584f, 0.012850982f, 0.04555431f, 0.056955688f, 0.06555285f, 0.050801456f, -0.009862683f, 0.00826772f, -0.026555609f, -0.0073611983f, -0.0014897042f}}, {4, {-0.0998932f, -0.07201956f, -0.052803773f, -0.15629593f, -0.15001918f, -0.07650751f, 0.02359855f, -0.075155355f, -0.08037709f, -0.15093534f, 0.029517552f, -0.04751393f, 0.010350531f, -0.02664851f, -0.016839722f, -0.023121163f, 0.0077019283f, 0.012851257f, -0.05040649f, -0.0129761f, -0.021737747f, -0.038305793f, -0.06870586f, -0.01481247f, -0.001285394f, 0.10124236f, 0.083122835f, 0.053313006f, -0.062235646f, -0.075637154f, -0.027833903f, 0.029774971f, 0.1130802f, 0.09218906f, 0.09506135f, -0.086665764f, -0.037162706f, -0.038880914f, -0.035832845f, -0.014481564f, -0.09825003f, -0.12048569f, -0.097665586f, -0.05287633f, -0.0964047f, -0.11366429f, 0.035777505f, 0.13568819f, 0.052451383f, 0.050649304f, 0.05798951f, -0.021852335f, -0.099848844f, 0.014740475f, -0.078897946f, 0.04974699f, 0.014160473f, 0.06973932f, 0.04964942f, 0.033364646f, 0.08190124f, 0.025535367f, 0.050893165f, 0.048514254f, 0.06945813f, -0.078907564f, -0.06707616f, -0.11844508f, -0.09986688f, -0.07509403f, 0.06263226f, 0.14925587f, 0.20188436f, 0.12098451f, 0.14639415f, 0.0015017595f, -0.014267382f, -0.03417257f, 0.012711468f, 0.0028300495f, -0.024758482f, -0.05098548f, -0.0821182f, 0.014225672f, 0.021544158f, 0.08949725f, 0.07505268f, -0.0020780868f, 0.04908258f, 0.06476295f, -0.022907063f, 0.027562456f, 0.040185735f, 0.019567577f, -0.015598739f, -0.049097303f, -0.017121866f, -0.083368234f, -0.02332002f, -0.0840956f}}, {5, {-0.001374326f, -0.078856036f, 0.10672688f, 0.029162422f, -0.11585556f, 0.02557986f, -0.13446963f, -0.035785314f, -0.01244275f, 0.025961924f, -0.02337298f, -0.044228926f, -0.055839065f, -0.046598054f, -0.010546039f, -0.06900766f, 0.027239809f, 0.022582639f, -0.013296484f, -0.05459212f, 0.08981f, -0.045407712f, 0.08682226f, -0.06867011f, -0.14390695f, -0.02916037f, 0.000996957f, 0.091420636f, 0.14283475f, -0.07390571f, -0.06402044f, 0.062524505f, -0.093129106f, 0.04860203f, -0.08364217f, -0.08119002f, 0.009352075f, 0.22920375f, 0.0016303885f, 0.11583097f, -0.13732095f, 0.012405723f, -0.07551853f, 0.06343048f, 0.12162708f, -0.031923793f, -0.014335606f, 0.01790974f, -0.10650317f, -0.0724401f, 0.08554849f, -0.05727212f, 0.06556731f, -0.042729504f, -0.043227166f, 0.011683251f, -0.013082158f, -0.029302018f, -0.010899579f, -0.062036745f, -0.022509435f, -0.00964907f, -0.01567329f, 0.04260106f, -0.07787477f, -0.11576462f, 0.017356863f, 0.048673786f, -0.017577527f, -0.05527947f, -0.082487635f, -0.040137455f, -0.10820036f, -0.04666372f, 0.022746278f, -0.07851417f, 0.01068115f, 0.032956902f, 0.022433773f, 0.0026891115f, 0.08944216f, -0.0685835f, 0.010513544f, 0.07228705f, 0.02032331f, -0.059686817f, -0.0005566496f, -0.086984694f, 0.040414046f, -0.1380399f, 0.094208956f, -0.05722982f, 0.012092817f, -0.04989123f, -0.086576f, -0.003399834f, -0.04696032f, -0.045747425f, 0.10091314f, 0.048676282f, -0.029037097f, 0.031399418f, -0.0040285117f, 0.047237843f, 0.09504992f, 0.041799378f, -0.049185462f, -0.031518843f, -0.10516937f, 0.026374253f, 0.10058866f, -0.0033195973f, -0.041975245f, 0.0073591834f, 0.0033782164f, -0.004325073f, -0.10167381f, 0.042500053f, -0.01447153f, 0.06464186f, -0.017142897f, 0.03312627f, 0.009205989f, 0.024138335f, -0.011337001f, 0.035530265f, -0.010912711f, 0.0706555f, -0.005894094f, 0.051841937f, -0.1401738f, -0.02351249f, 0.0365468f, 0.07590991f, 0.08838724f, 0.021681072f, -0.10086113f, 0.019608743f, -0.06195883f, 0.077335775f, 0.023646897f, -0.095322326f, 0.02233014f, 0.09756986f, -0.048691444f, -0.009579111f, 0.07595467f, 0.11480546f, -0.09801813f, 0.019894179f, 0.08502348f, 0.004032281f, 0.037211012f, 0.068537936f, -0.048005626f, -0.091520436f, -0.028379958f, -0.01556313f, 0.06554592f, -0.045599163f, -0.01672207f, -0.020169014f, -0.011877351f, -0.20212261f, 0.010889619f, 0.0047078193f, 0.038385306f, 0.08540671f, -0.017140968f, -0.0035865551f, 0.016678626f, 0.005633034f, 0.015963363f, 0.00871737f, 0.060130805f, 0.028611384f, 0.10109069f, -0.015060172f, -0.07894427f, 0.06401885f, 0.011584063f, -0.024466386f, 0.0047652307f, -0.09041358f, 0.030737216f, -0.0046374933f, 0.14215417f, -0.11823516f, 0.019899689f, 0.006106124f, -0.027092824f, 0.0786356f, 0.05052217f, -0.058925f, -0.011402121f, -0.024987547f, -0.0013661642f, -0.06832946f, -0.015667673f, -0.1083353f, -0.00096863037f, -0.06988685f, -0.053350925f, -0.027275559f, -0.033664223f, -0.07978348f, -0.025200296f, -0.017207067f, -0.058403496f, -0.055697463f, 0.005798788f, 0.12965427f, -0.062582195f, 0.0013350133f, -0.10482091f, 0.0379771f, 0.072521195f, -0.0029455067f, -0.13797039f, -0.03628521f, 0.013806405f, -0.017858358f, -0.01008298f, -0.07700066f, -0.017081132f, 0.019358726f, 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-0.10549954f, 0.090567775f, 0.042013682f, -0.03176985f, 0.12569028f, -0.02421228f, -0.029526481f, 0.023851605f, 0.031539805f, 0.05292009f, -0.02344001f, -0.07811758f, -0.08834428f, 0.10094801f, 0.16594367f, -0.06861939f, -0.021256343f, -0.041093912f, -0.06669611f, 0.035498552f, 0.021757556f, -0.09302526f, -0.015403468f, -0.06614931f, -0.051798206f, -0.013874718f, 0.03630673f, 0.010412845f, -0.08077351f, 0.046185967f, 0.0035662893f, 0.03541868f, -0.094149634f, -0.034814864f, 0.003128424f, -0.020674974f, -0.03944324f, -0.008110165f, -0.11113267f, 0.08484226f, 0.043586485f, 0.040582247f, 0.0968012f, -0.065249965f, -0.028036479f, 0.0050708856f, 0.0017462453f, 0.0326779f, 0.041296225f, 0.09164146f, -0.047743853f, -0.015952192f, -0.034451712f, 0.084197424f, -0.05347844f, -0.11768019f, 0.085926116f, -0.08251791f, -0.045081906f, 0.0948852f, 0.068401024f, 0.024856757f, 0.06978981f, -0.057309967f, -0.012775832f, -0.0032452994f, 0.01977615f, -0.041040014f, -0.024264973f, 0.063464895f, 0.05431621f}}, {9, {0.040369894f, 0.030746894f, 0.24704495f, 0.018586371f, -0.037586458f, -0.15312155f, -0.11812848f, -0.11465643f, 0.20259799f, 0.11418174f, -0.10116027f, -0.011334949f, 0.12411352f, -0.076769054f, -0.052169047f, 0.21198851f, -0.38871562f, -0.09061183f, -0.09683246f, -0.21929175f}}, {10, {-0.01998659f, -0.15568835f, -0.24248174f, -0.012770197f, 0.041331276f, -0.072311886f, -0.052123554f, -0.0066330447f, -0.043891653f, 0.036225766f, -0.047248036f, 0.021479502f, 0.033189066f, 0.11952997f, -0.020432774f, 0.64658105f, -0.06650122f, -0.03467612f, 0.095340036f, 0.23647355f}}, {11, {0.08286371f, -0.08261836f, -0.51210177f, 0.002913762f, 0.17764764f, -0.5495371f, -0.08460716f, -0.24552552f, 0.030037103f, 0.04123544f, -0.11940523f, 0.007358328f, 0.1890978f, 0.4833202f, -0.34441817f, 0.36312827f, -0.26375428f, 0.1457655f, -0.19724406f, 0.15548733f}}, {12, {0.02234832f, 0.14757581f, 0.18176508f, 0.10380666f, 0.053110216f, -0.06928846f, -0.13942584f, -0.11816189f, 0.19483899f, 0.03652339f, -0.10250295f, 0.036714908f, -0.18426876f, 0.036065217f, 0.21810818f, 0.02383196f, -0.043370757f, 0.08690144f, -0.04444982f, 0.00030581196f}}, {13, {0.035185695f, -0.042891346f, -0.03032477f, 0.23027696f, 0.11098921f, 0.15378423f, 0.09263801f, 0.09790885f, 0.09508917f, 0.061199076f, 0.07665568f, -0.015443159f, -0.03499149f, 0.046190713f, 0.08895977f, 0.10899629f, 0.40694186f, 0.06030037f, 0.012413437f, -0.06108739f}}, {14, {-0.024379363f, 0.0055531194f, 0.23377132f, 0.033463873f, -0.1483596f, -0.10639995f, -0.091433935f, 0.058573797f, -0.06809782f, -0.07889636f, -0.043246906f, -0.09829136f, -0.4279842f, 0.034901652f, 0.18797937f, 0.0075234566f, 0.016178843f, 0.1749513f, 0.13975595f, 0.92058027f}}, {15, {0.046159424f, -0.0012809046f, 0.03563469f, 0.12648113f, 0.027195795f, 0.35373217f, -0.018957434f, 0.008907322f, -0.0762701f, 0.12018895f, 0.04216877f, 0.0022856654f, 0.040952638f, 0.3147856f, 0.08225149f, -0.057416286f, -0.14995944f, -0.008040261f, 0.13208859f, 0.029760877f}}, {16, {-0.009802181f, 0.09401916f, 0.0717386f, -0.13895074f, 0.09641832f, 0.060420845f, 0.08539281f, 0.054285463f, 0.061395317f, 0.034448683f, -0.042991187f, 0.019801661f, -0.16840284f, -0.015726732f, -0.23041931f, -0.024478018f, -0.10959692f, -0.013875541f, 0.18600968f, -0.061274476f, 0.0138165f, -0.08160894f, -0.07661644f, 0.032372914f, 0.16169067f, 0.22465782f, -0.03993472f, -0.004017731f, 0.08633481f, -0.28869787f, 0.08682067f, 0.17240396f, 0.014975425f, 0.056431185f, 0.031037588f, 0.16702051f, 0.0077946745f, 0.15140012f, 0.29405436f, 0.120285f, -0.188994f, -0.027265169f, 0.043389652f, -0.022061434f, 0.014777949f, -0.20203483f, 0.094781205f, 0.19100232f, 0.13987629f, -0.036132768f, -0.06426278f, -0.05108664f, 0.13221376f, 0.009441198f, -0.16715929f, 0.15859416f, -0.040437475f, 0.050779544f, -0.022187516f, 0.012166504f, 0.027685808f, -0.07675938f, -0.0055694645f, -0.09444123f, 0.0046453946f, 0.050794356f, 0.10770313f, -0.20790008f, -0.07149004f, -0.11425117f, 0.008225835f, -0.035802525f, 0.14374903f, 0.15262283f, 0.048710253f, 0.1847461f, -0.007487823f, 0.11000021f, -0.09542012f, 0.22619456f, -0.029149994f, 0.08527916f, 0.009043713f, 0.0042746216f, 0.016261552f, 0.022461696f, 0.12689082f, -0.043589946f, -0.12035478f, -0.08361797f, -0.050666027f, -0.1248618f, -0.1275799f, -0.071875185f, 0.07377272f, 0.09944291f, -0.18897448f, -0.1593054f, -0.06526116f, -0.040107165f, -0.004618631f, -0.067624845f, -0.007576253f, 0.10727444f, 0.041546922f, -0.20424393f, 0.06907816f, 0.050412357f, 0.00724631f, 0.039827548f, 0.12449835f, 0.10747581f, 0.13708383f, 0.09134148f, -0.12617786f, -0.06428341f, 0.09956831f, 0.1208086f, -0.14676677f, -0.0727722f, 0.1126304f, 0.010139365f, 0.015571211f, -0.038128063f, 0.022913318f, -0.042050496f, 0.16842307f, -0.060597885f, 0.10531834f, -0.06411776f, -0.07451711f, -0.03410368f, -0.13393489f, 0.06534304f, 0.003620307f, 0.04490757f, 0.05970546f, 0.05197996f, 0.02839995f, 0.10434969f, -0.013699693f, -0.028353551f, -0.07260381f, 0.047201227f, -0.024575593f, -0.036445823f, 0.07155557f, 0.009672501f, -0.02328883f, 0.009533515f, -0.03606021f, -0.07421458f, -0.028082801f, -0.2678904f, -0.13221288f, 0.18419984f, -0.13012612f, -0.014588381f, -0.035059117f, -0.04824723f, 0.07830115f, -0.056184657f, 0.03277091f, 0.025466874f, 0.14494097f, -0.12522776f, -0.098633975f, -0.10766018f, -0.08317623f, 0.08594209f, 0.07749552f, 0.039474737f, 0.1776665f, -0.07409566f, -0.0477268f, 0.29323658f, 0.10801441f, 0.1154011f, 0.013952499f, 0.10739139f, 0.10708251f, -0.051456142f, 0.0074137426f, -0.10430189f, 0.10034707f, 0.045594677f, 0.0635285f, -0.0715442f, -0.089667566f, -0.10811871f, 0.00026344223f, 0.08298446f, -0.009525053f, 0.006585689f, -0.24567553f, -0.09450807f, 0.09648481f, 0.026996298f, -0.06419476f, -0.04752702f, -0.11063944f, -0.23441927f, -0.17608605f, -0.052156363f, 0.067035615f, 0.19271925f, -0.0032889997f, -0.043264326f, 0.09663576f, -0.057112187f, -0.10100678f, 0.0628376f, 0.04447668f, 0.017961001f, -0.10094388f, -0.10190601f, 0.18335468f, 0.10494553f, -0.052095775f, -0.0026118709f, 0.10539724f, -0.04383912f, -0.042349473f, 0.08438151f, -0.1947263f, 0.02251204f, 0.11216432f, -0.10307853f, 0.17351969f, -0.039091777f, 0.08066188f, -0.00561982f, 0.12633002f, 0.11335965f, -0.0088127935f, -0.019777594f, 0.06864014f, -0.059751723f, 0.016233567f, -0.06894641f, -0.28651384f, -0.004228674f, 0.019708522f, -0.16305895f, -0.07468996f, -0.0855457f, 0.099339016f, -0.07580735f, -0.13775392f, 0.08434318f, 0.08330512f, -0.12131499f, 0.031935584f, 0.09180414f, -0.08876437f, -0.08049874f, 0.008753825f, 0.03498998f, 0.030215185f, 0.03907079f, 0.089751154f, 0.029194152f, -0.03337423f, -0.019092513f, 0.04331237f, 0.04299654f, -0.036394123f, -0.12915532f, 0.09793732f, 0.07512415f, -0.11319543f, -0.032502122f, 0.15661901f, 0.07671967f, -0.005491124f, -0.19379048f, -0.218606f, 0.21448623f, 0.017840758f, 0.1416943f, -0.07051762f, 0.19488361f, 0.02664691f, -0.18104725f, -0.09334311f, 0.15026465f, -0.15493552f, -0.057762887f, -0.11604192f, -0.262013f, -0.01391798f, 0.012185008f, 0.11156489f, -0.07483202f, 0.06693364f, -0.26151478f, 0.046425626f, 0.036540434f, -0.16435726f, 0.17338543f, -0.21401681f, -0.11385144f, -0.08283257f, -0.069031075f, 0.030635102f, 0.010969227f, 0.11109743f, 0.010919218f, 0.027526086f, 0.13519906f, 0.01891392f, -0.046839405f, -0.040167913f, 0.017953383f, -0.09700955f, 0.0061885654f, -0.07000971f, 0.026893595f, -0.038844477f, 0.14543656f}}, {17, {}}, {18, {-0.0166936f, 0.0381209f, 0.000889684f, 0.0143363f, -0.0328911f, -0.0234288f, 0.0333051f, -0.012229f, 0.0110322f, -0.0457725f, -0.000832209f, -0.0202817f, 0.0327257f, 0.0121309f, 0.0155969f, 0.0312091f, -0.0141913f, 0.0322082f, 0.00227024f, 0.0260507f, -0.0188721f, -0.0296489f, 0.0399134f, -0.0160509f, 0.011604f, -0.0447318f, -0.0150515f, -0.0277406f, 0.0316596f, 0.0118233f, 0.0214762f, 0.0293641f}}, {19, {-0.154022f, -0.124934f, 0.0478463f, 0.0607819f, -0.218727f, -0.111053f, -0.103885f, -0.00447221f, 0.0554757f, -0.0207068f, 0.0595767f, -0.116297f, -0.249466f, -0.0723206f, 0.0794942f, -0.0377107f, 0.124532f, 0.249952f, 0.188641f, 0.411865f, -0.11012f, -0.0694494f, 0.103501f, 0.0428427f, -0.167345f, -0.106061f, -0.0775679f, 0.00936161f, 0.0105526f, -0.0314523f, 0.0243475f, -0.132179f, -0.258763f, -0.0307266f, 0.107047f, -0.0115197f, 0.0995485f, 0.220027f, 0.158355f, 0.436369f}}, {21, {0.0f}}, {22, {0.0f}}},
+  // int -> INT32 map
+  {{20, {4}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{1, {-0.0213783f, 0.0350169f, 0.000324787f, 0.0276012f, -0.0263374f, -0.0371449f, 0.0446149f, -0.0205474f, 0.0103729f, -0.0576349f, -0.0150052f, -0.0292043f, 0.0376827f, 0.0136115f, 0.0243435f, 0.0354492f, -0.0204549f, 0.0450315f, -0.00117379f, 0.0167673f, -0.0375007f, -0.0238314f, 0.038784f, -0.0174034f, 0.0131743f, -0.0506589f, -0.00484469f, -0.0240239f, 0.0325789f, 0.00790064f, 0.0220157f, 0.0333314f}}, {2, {-0.126572f, -0.121882f, 0.121569f, 0.0489971f, -0.240177f, -0.124685f, -0.122565f, 0.0162748f, 0.0317536f, -0.0270355f, 0.0418199f, -0.179755f, -0.327279f, -0.0342741f, 0.133831f, -0.0238279f, 0.122148f, 0.269115f, 0.185989f, 0.525976f, -0.167208f, -0.109612f, 0.0531226f, 0.0695387f, -0.248335f, -0.134123f, -0.108246f, 0.00628498f, 0.0492984f, -0.0264919f, 0.0698144f, -0.0635602f, -0.295363f, -0.0760078f, 0.102725f, -0.0351708f, 0.149804f, 0.259131f, 0.202573f, 0.500664f}}, {3, {-0.0213783f, 0.0350169f, 0.000324794f, 0.0276012f, -0.0263374f, -0.0371449f, 0.0446149f, -0.0205474f, 0.0103729f, -0.0576349f, -0.0150052f, -0.0292043f, 0.0376827f, 0.0136115f, 0.0243435f, 0.0354492f, -0.0204549f, 0.0450315f, -0.00117378f, 0.0167673f, -0.0375007f, -0.0238314f, 0.038784f, -0.0174034f, 0.0131743f, -0.0506589f, -0.0048447f, -0.0240239f, 0.0325789f, 0.00790065f, 0.0220157f, 0.0333314f}}, {0, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/lstm3_state3_relaxed.example.cpp b/nn/runtime/test/generated/examples/lstm3_state3_relaxed.example.cpp
new file mode 100644
index 0000000..2bb2917
--- /dev/null
+++ b/nn/runtime/test/generated/examples/lstm3_state3_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: lstm3_state3_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.867394f, 0.291279f, 0.013714f, 0.482521f, 0.626339f, 0.082922f, 0.563329f, 0.865614f, 0.333232f, 0.259916f}}, {1, {0.021393683f, 0.06124551f, 0.046905167f, -0.014657677f, -0.03149463f, 0.09171803f, 0.14647801f, 0.10797193f, -0.0057968358f, 0.0019193048f, -0.2726754f, 0.10154029f, -0.018539885f, 0.080349885f, -0.10262385f, -0.022599787f, -0.09121155f, -0.008675967f, -0.045206103f, -0.0821282f, -0.008045952f, 0.015478081f, 0.055217247f, 0.038719587f, 0.044153627f, -0.06453243f, 0.05031825f, -0.046935108f, -0.008164439f, 0.014574226f, -0.1671009f, -0.15519552f, -0.16819797f, -0.13971269f, -0.11953059f, 0.25005487f, -0.22790983f, 0.009855087f, -0.028140958f, -0.11200698f, 0.11295408f, -0.0035217577f, 0.054485075f, 0.05184695f, 0.064711206f, 0.10989193f, 0.11674786f, 0.03490607f, 0.07727357f, 0.11390585f, -0.1863375f, -0.1034451f, -0.13945189f, -0.049401227f, -0.18767063f, 0.042483903f, 0.14233552f, 0.13832581f, 0.18350165f, 0.14545603f, -0.028545704f, 0.024939531f, 0.050929718f, 0.0076203286f, -0.0029723682f, -0.042484224f, -0.11827596f, -0.09171104f, -0.10808628f, -0.16327988f, -0.2273378f, -0.0993647f, -0.017155107f, 0.0023917493f, 0.049272764f, 0.0038534778f, 0.054764505f, 0.089753784f, 0.06947234f, 0.08014476f, -0.04544234f, -0.0497073f, -0.07135631f, -0.048929106f, -0.004042012f, -0.009284026f, 0.018042054f, 0.0036860977f, -0.07427302f, -0.11434604f, -0.018995456f, 0.031487543f, 0.012834908f, 0.019977754f, 0.044256654f, -0.39292613f, -0.18519334f, -0.11651281f, -0.06809892f, 0.011373677f}}, {2, {-0.0018401089f, -0.004852237f, 0.03698424f, 0.014181704f, 0.028273236f, -0.016726194f, -0.05249759f, -0.10204261f, 0.00861066f, -0.040979505f, -0.009899187f, 0.01923892f, -0.028177269f, -0.08535103f, -0.14585495f, 0.10662567f, -0.01909731f, -0.017883534f, -0.0047269356f, -0.045103323f, 0.0030784295f, 0.076784775f, 0.07463696f, 0.094531395f, 0.0814421f, -0.12257899f, -0.033945758f, -0.031303465f, 0.045630626f, 0.06843887f, -0.13492945f, -0.012480007f, -0.0811829f, -0.07224499f, -0.09628791f, 0.045100946f, 0.0012300825f, 0.013964662f, 0.099372394f, 0.02543059f, 0.06958324f, 0.034257296f, 0.0482646f, 0.06267997f, 0.052625068f, 0.12784666f, 0.07077897f, 0.025725935f, 0.04165009f, 0.07241905f, 0.018668644f, -0.037377294f, -0.06277783f, -0.08833636f, -0.040120605f, -0.011405586f, -0.007808335f, -0.010301386f, -0.005102167f, 0.027717464f, 0.05483423f, 0.11449111f, 0.11289652f, 0.10939839f, 0.13396506f, -0.08402166f, -0.01901462f, -0.044678304f, -0.07720565f, 0.014350063f, -0.11757958f, -0.0652038f, -0.08185733f, -0.076754324f, -0.092614375f, 0.10405491f, 0.052960336f, 0.035755895f, 0.035839386f, -0.012540553f, 0.036881298f, 0.02913376f, 0.03420159f, 0.05448447f, -0.054523353f, 0.02582715f, 0.02327355f, -0.011857179f, -0.0011980024f, -0.034641717f, -0.026125094f, -0.17582615f, -0.15923657f, -0.27486774f, -0.0006143371f, 0.0001771948f, -8.470171e-05f, 0.02651807f, 0.045790765f, 0.06956496f}}, {3, {-0.04580283f, -0.09549462f, -0.032418985f, -0.06454633f, -0.043528453f, 0.043018587f, -0.049152344f, -0.12418144f, -0.078985475f, -0.07596889f, 0.019484362f, -0.11434962f, -0.0074034138f, -0.06314844f, -0.092981495f, 0.0062155537f, -0.025034338f, -0.0028890965f, 0.048929527f, 0.06235075f, 0.10665918f, -0.032036792f, -0.08505916f, -0.10843358f, -0.13002433f, -0.036816437f, -0.02130134f, -0.016518239f, 0.0047691227f, -0.0025825808f, 0.066017866f, 0.029991534f, -0.10652836f, -0.1037554f, -0.13056071f, -0.03266643f, -0.033702414f, -0.006473424f, -0.04611692f, 0.014419339f, -0.025174323f, 0.0396852f, 0.081777506f, 0.06157468f, 0.10210095f, -0.009658194f, 0.046511717f, 0.03603906f, 0.0069369148f, 0.015960095f, -0.06507666f, 0.09551598f, 0.053568836f, 0.06408714f, 0.12835667f, -0.008714329f, -0.20211966f, -0.12093674f, 0.029450472f, 0.2849013f, -0.029227901f, 0.1164364f, -0.08560263f, 0.09941786f, -0.036999565f, -0.028842626f, -0.0033637602f, -0.017012902f, -0.09720865f, -0.11193351f, -0.029155117f, -0.017936034f, -0.009768936f, -0.04223324f, -0.036159635f, 0.06505112f, -0.021742892f, -0.023377212f, -0.07221364f, -0.06430552f, 0.05453865f, 0.091149814f, 0.06387331f, 0.007518393f, 0.055960953f, 0.069779344f, 0.046411168f, 0.10509911f, 0.07463894f, 0.0075130584f, 0.012850982f, 0.04555431f, 0.056955688f, 0.06555285f, 0.050801456f, -0.009862683f, 0.00826772f, -0.026555609f, -0.0073611983f, -0.0014897042f}}, {4, {-0.0998932f, -0.07201956f, -0.052803773f, -0.15629593f, -0.15001918f, -0.07650751f, 0.02359855f, -0.075155355f, -0.08037709f, -0.15093534f, 0.029517552f, -0.04751393f, 0.010350531f, -0.02664851f, -0.016839722f, -0.023121163f, 0.0077019283f, 0.012851257f, -0.05040649f, -0.0129761f, -0.021737747f, -0.038305793f, -0.06870586f, -0.01481247f, -0.001285394f, 0.10124236f, 0.083122835f, 0.053313006f, -0.062235646f, -0.075637154f, -0.027833903f, 0.029774971f, 0.1130802f, 0.09218906f, 0.09506135f, -0.086665764f, -0.037162706f, -0.038880914f, -0.035832845f, -0.014481564f, -0.09825003f, -0.12048569f, -0.097665586f, -0.05287633f, -0.0964047f, -0.11366429f, 0.035777505f, 0.13568819f, 0.052451383f, 0.050649304f, 0.05798951f, -0.021852335f, -0.099848844f, 0.014740475f, -0.078897946f, 0.04974699f, 0.014160473f, 0.06973932f, 0.04964942f, 0.033364646f, 0.08190124f, 0.025535367f, 0.050893165f, 0.048514254f, 0.06945813f, -0.078907564f, -0.06707616f, -0.11844508f, -0.09986688f, -0.07509403f, 0.06263226f, 0.14925587f, 0.20188436f, 0.12098451f, 0.14639415f, 0.0015017595f, -0.014267382f, -0.03417257f, 0.012711468f, 0.0028300495f, -0.024758482f, -0.05098548f, -0.0821182f, 0.014225672f, 0.021544158f, 0.08949725f, 0.07505268f, -0.0020780868f, 0.04908258f, 0.06476295f, -0.022907063f, 0.027562456f, 0.040185735f, 0.019567577f, -0.015598739f, -0.049097303f, -0.017121866f, -0.083368234f, -0.02332002f, -0.0840956f}}, {5, {-0.001374326f, -0.078856036f, 0.10672688f, 0.029162422f, -0.11585556f, 0.02557986f, -0.13446963f, -0.035785314f, -0.01244275f, 0.025961924f, -0.02337298f, -0.044228926f, -0.055839065f, -0.046598054f, -0.010546039f, -0.06900766f, 0.027239809f, 0.022582639f, -0.013296484f, -0.05459212f, 0.08981f, -0.045407712f, 0.08682226f, -0.06867011f, -0.14390695f, -0.02916037f, 0.000996957f, 0.091420636f, 0.14283475f, -0.07390571f, -0.06402044f, 0.062524505f, -0.093129106f, 0.04860203f, -0.08364217f, -0.08119002f, 0.009352075f, 0.22920375f, 0.0016303885f, 0.11583097f, -0.13732095f, 0.012405723f, -0.07551853f, 0.06343048f, 0.12162708f, -0.031923793f, -0.014335606f, 0.01790974f, -0.10650317f, -0.0724401f, 0.08554849f, -0.05727212f, 0.06556731f, -0.042729504f, -0.043227166f, 0.011683251f, -0.013082158f, -0.029302018f, -0.010899579f, -0.062036745f, -0.022509435f, -0.00964907f, -0.01567329f, 0.04260106f, -0.07787477f, -0.11576462f, 0.017356863f, 0.048673786f, -0.017577527f, -0.05527947f, -0.082487635f, -0.040137455f, -0.10820036f, -0.04666372f, 0.022746278f, -0.07851417f, 0.01068115f, 0.032956902f, 0.022433773f, 0.0026891115f, 0.08944216f, -0.0685835f, 0.010513544f, 0.07228705f, 0.02032331f, -0.059686817f, -0.0005566496f, -0.086984694f, 0.040414046f, -0.1380399f, 0.094208956f, -0.05722982f, 0.012092817f, -0.04989123f, -0.086576f, -0.003399834f, -0.04696032f, -0.045747425f, 0.10091314f, 0.048676282f, -0.029037097f, 0.031399418f, -0.0040285117f, 0.047237843f, 0.09504992f, 0.041799378f, -0.049185462f, -0.031518843f, -0.10516937f, 0.026374253f, 0.10058866f, -0.0033195973f, -0.041975245f, 0.0073591834f, 0.0033782164f, -0.004325073f, -0.10167381f, 0.042500053f, -0.01447153f, 0.06464186f, -0.017142897f, 0.03312627f, 0.009205989f, 0.024138335f, -0.011337001f, 0.035530265f, -0.010912711f, 0.0706555f, -0.005894094f, 0.051841937f, -0.1401738f, -0.02351249f, 0.0365468f, 0.07590991f, 0.08838724f, 0.021681072f, -0.10086113f, 0.019608743f, -0.06195883f, 0.077335775f, 0.023646897f, -0.095322326f, 0.02233014f, 0.09756986f, -0.048691444f, -0.009579111f, 0.07595467f, 0.11480546f, -0.09801813f, 0.019894179f, 0.08502348f, 0.004032281f, 0.037211012f, 0.068537936f, -0.048005626f, -0.091520436f, 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0.0027079724f, 0.004635139f, 0.062634714f, -0.02338735f, -0.039547626f, -0.02050681f, 0.03385117f, -0.083611414f, 0.002862572f, -0.09421313f, 0.058618143f, -0.08598433f, 0.00972939f, 0.023867095f, -0.053934585f, -0.023203006f, 0.07452513f, -0.048767887f, -0.07314807f, -0.056307215f, -0.10433547f, -0.06440842f, 0.04328182f, 0.04389765f, -0.020006588f, -0.09076438f, -0.11652589f, -0.021705797f, 0.03345259f, -0.010329105f, -0.025767034f, 0.013057034f, -0.07316461f, -0.10145612f, 0.06358255f, 0.18531723f, 0.07759293f, 0.12006465f, 0.1305557f, 0.058638252f, -0.03393652f, 0.09622831f, -0.16253184f, -2.4580743e-06f, 0.079869635f, -0.070196845f, -0.005644518f, 0.06857898f, -0.12598175f, -0.035084512f, 0.03156317f, -0.12794146f, -0.031963028f, 0.04692781f, 0.030070418f, 0.0071660685f, -0.095516115f, -0.004643372f, 0.040170413f, -0.062104587f, -0.0037324072f, 0.0554317f, 0.08184801f, -0.019164372f, 0.06791302f, 0.034257166f, -0.10307039f, 0.021943003f, 0.046745934f, 0.0790918f, -0.0265588f, 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-0.095442444f, -0.029564252f, 0.016493602f, -0.035026584f, 0.022337519f, -0.026871363f, 0.004780428f, 0.0077918363f, -0.03601621f, 0.016435321f, -0.03263031f, -0.09543275f, -0.047392778f, 0.013454138f, 0.028934088f, 0.01685226f, -0.086110644f, -0.046250615f, -0.01847454f, 0.047608484f, 0.07339695f, 0.034546845f, -0.04881143f, 0.009128804f, -0.08802852f, 0.03761666f, 0.008096139f, -0.014454086f, 0.014361001f, -0.023502491f, -0.0011840804f, -0.07607001f, 0.001856849f, -0.06509276f, -0.006021153f, -0.08570962f, -0.1451793f, 0.060212336f, 0.055259194f, 0.06974018f, 0.049454916f, -0.027794661f, -0.08077226f, -0.016179763f, 0.1169753f, 0.17213494f, -0.0056326236f, -0.053934924f, -0.0124349f, -0.11520337f, 0.05409887f, 0.088759385f, 0.0019655675f, 0.0042065294f, 0.03881498f, 0.019844765f, 0.041858196f, -0.05695512f, 0.047233116f, 0.038937137f, -0.06542224f, 0.014429736f, -0.09719407f, 0.13908425f, -0.05379757f, 0.012321099f, 0.082840554f, -0.029899208f, 0.044217527f, 0.059855383f, 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0.029760877f}}, {16, {-0.009802181f, 0.09401916f, 0.0717386f, -0.13895074f, 0.09641832f, 0.060420845f, 0.08539281f, 0.054285463f, 0.061395317f, 0.034448683f, -0.042991187f, 0.019801661f, -0.16840284f, -0.015726732f, -0.23041931f, -0.024478018f, -0.10959692f, -0.013875541f, 0.18600968f, -0.061274476f, 0.0138165f, -0.08160894f, -0.07661644f, 0.032372914f, 0.16169067f, 0.22465782f, -0.03993472f, -0.004017731f, 0.08633481f, -0.28869787f, 0.08682067f, 0.17240396f, 0.014975425f, 0.056431185f, 0.031037588f, 0.16702051f, 0.0077946745f, 0.15140012f, 0.29405436f, 0.120285f, -0.188994f, -0.027265169f, 0.043389652f, -0.022061434f, 0.014777949f, -0.20203483f, 0.094781205f, 0.19100232f, 0.13987629f, -0.036132768f, -0.06426278f, -0.05108664f, 0.13221376f, 0.009441198f, -0.16715929f, 0.15859416f, -0.040437475f, 0.050779544f, -0.022187516f, 0.012166504f, 0.027685808f, -0.07675938f, -0.0055694645f, -0.09444123f, 0.0046453946f, 0.050794356f, 0.10770313f, -0.20790008f, -0.07149004f, -0.11425117f, 0.008225835f, -0.035802525f, 0.14374903f, 0.15262283f, 0.048710253f, 0.1847461f, -0.007487823f, 0.11000021f, -0.09542012f, 0.22619456f, -0.029149994f, 0.08527916f, 0.009043713f, 0.0042746216f, 0.016261552f, 0.022461696f, 0.12689082f, -0.043589946f, -0.12035478f, -0.08361797f, -0.050666027f, -0.1248618f, -0.1275799f, -0.071875185f, 0.07377272f, 0.09944291f, -0.18897448f, -0.1593054f, -0.06526116f, -0.040107165f, -0.004618631f, -0.067624845f, -0.007576253f, 0.10727444f, 0.041546922f, -0.20424393f, 0.06907816f, 0.050412357f, 0.00724631f, 0.039827548f, 0.12449835f, 0.10747581f, 0.13708383f, 0.09134148f, -0.12617786f, -0.06428341f, 0.09956831f, 0.1208086f, -0.14676677f, -0.0727722f, 0.1126304f, 0.010139365f, 0.015571211f, -0.038128063f, 0.022913318f, -0.042050496f, 0.16842307f, -0.060597885f, 0.10531834f, -0.06411776f, -0.07451711f, -0.03410368f, -0.13393489f, 0.06534304f, 0.003620307f, 0.04490757f, 0.05970546f, 0.05197996f, 0.02839995f, 0.10434969f, -0.013699693f, -0.028353551f, -0.07260381f, 0.047201227f, -0.024575593f, -0.036445823f, 0.07155557f, 0.009672501f, -0.02328883f, 0.009533515f, -0.03606021f, -0.07421458f, -0.028082801f, -0.2678904f, -0.13221288f, 0.18419984f, -0.13012612f, -0.014588381f, -0.035059117f, -0.04824723f, 0.07830115f, -0.056184657f, 0.03277091f, 0.025466874f, 0.14494097f, -0.12522776f, -0.098633975f, -0.10766018f, -0.08317623f, 0.08594209f, 0.07749552f, 0.039474737f, 0.1776665f, -0.07409566f, -0.0477268f, 0.29323658f, 0.10801441f, 0.1154011f, 0.013952499f, 0.10739139f, 0.10708251f, -0.051456142f, 0.0074137426f, -0.10430189f, 0.10034707f, 0.045594677f, 0.0635285f, -0.0715442f, -0.089667566f, -0.10811871f, 0.00026344223f, 0.08298446f, -0.009525053f, 0.006585689f, -0.24567553f, -0.09450807f, 0.09648481f, 0.026996298f, -0.06419476f, -0.04752702f, -0.11063944f, -0.23441927f, -0.17608605f, -0.052156363f, 0.067035615f, 0.19271925f, -0.0032889997f, -0.043264326f, 0.09663576f, -0.057112187f, -0.10100678f, 0.0628376f, 0.04447668f, 0.017961001f, -0.10094388f, -0.10190601f, 0.18335468f, 0.10494553f, -0.052095775f, -0.0026118709f, 0.10539724f, -0.04383912f, -0.042349473f, 0.08438151f, -0.1947263f, 0.02251204f, 0.11216432f, -0.10307853f, 0.17351969f, -0.039091777f, 0.08066188f, -0.00561982f, 0.12633002f, 0.11335965f, -0.0088127935f, -0.019777594f, 0.06864014f, -0.059751723f, 0.016233567f, -0.06894641f, -0.28651384f, -0.004228674f, 0.019708522f, -0.16305895f, -0.07468996f, -0.0855457f, 0.099339016f, -0.07580735f, -0.13775392f, 0.08434318f, 0.08330512f, -0.12131499f, 0.031935584f, 0.09180414f, -0.08876437f, -0.08049874f, 0.008753825f, 0.03498998f, 0.030215185f, 0.03907079f, 0.089751154f, 0.029194152f, -0.03337423f, -0.019092513f, 0.04331237f, 0.04299654f, -0.036394123f, -0.12915532f, 0.09793732f, 0.07512415f, -0.11319543f, -0.032502122f, 0.15661901f, 0.07671967f, -0.005491124f, -0.19379048f, -0.218606f, 0.21448623f, 0.017840758f, 0.1416943f, -0.07051762f, 0.19488361f, 0.02664691f, -0.18104725f, -0.09334311f, 0.15026465f, -0.15493552f, -0.057762887f, -0.11604192f, -0.262013f, -0.01391798f, 0.012185008f, 0.11156489f, -0.07483202f, 0.06693364f, -0.26151478f, 0.046425626f, 0.036540434f, -0.16435726f, 0.17338543f, -0.21401681f, -0.11385144f, -0.08283257f, -0.069031075f, 0.030635102f, 0.010969227f, 0.11109743f, 0.010919218f, 0.027526086f, 0.13519906f, 0.01891392f, -0.046839405f, -0.040167913f, 0.017953383f, -0.09700955f, 0.0061885654f, -0.07000971f, 0.026893595f, -0.038844477f, 0.14543656f}}, {17, {}}, {18, {-0.0213783f, 0.0350169f, 0.000324787f, 0.0276012f, -0.0263374f, -0.0371449f, 0.0446149f, -0.0205474f, 0.0103729f, -0.0576349f, -0.0150052f, -0.0292043f, 0.0376827f, 0.0136115f, 0.0243435f, 0.0354492f, -0.0204549f, 0.0450315f, -0.00117379f, 0.0167673f, -0.0375007f, -0.0238314f, 0.038784f, -0.0174034f, 0.0131743f, -0.0506589f, -0.00484469f, -0.0240239f, 0.0325789f, 0.00790064f, 0.0220157f, 0.0333314f}}, {19, {-0.126572f, -0.121882f, 0.121569f, 0.0489971f, -0.240177f, -0.124685f, -0.122565f, 0.0162748f, 0.0317536f, -0.0270355f, 0.0418199f, -0.179755f, -0.327279f, -0.0342741f, 0.133831f, -0.0238279f, 0.122148f, 0.269115f, 0.185989f, 0.525976f, -0.167208f, -0.109612f, 0.0531226f, 0.0695387f, -0.248335f, -0.134123f, -0.108246f, 0.00628498f, 0.0492984f, -0.0264919f, 0.0698144f, -0.0635602f, -0.295363f, -0.0760078f, 0.102725f, -0.0351708f, 0.149804f, 0.259131f, 0.202573f, 0.500664f}}, {21, {0.0f}}, {22, {0.0f}}},
+  // int -> INT32 map
+  {{20, {4}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{1, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}, {2, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}, {3, {-0.0189322f, 0.0464512f, -0.00251373f, 0.0225745f, -0.0308346f, -0.0317124f, 0.0460407f, -0.0189395f, 0.0149363f, -0.0530162f, -0.0150767f, -0.0340193f, 0.0286833f, 0.00824207f, 0.0264887f, 0.0305169f, -0.0264787f, 0.0387855f, -0.000764675f, 0.0217599f, -0.037537f, -0.0335206f, 0.0431679f, -0.0211424f, 0.010203f, -0.062785f, -0.00832363f, -0.025181f, 0.0412031f, 0.0118723f, 0.0239643f, 0.0394009f}}, {0, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/lstm3_state_relaxed.example.cpp b/nn/runtime/test/generated/examples/lstm3_state_relaxed.example.cpp
new file mode 100644
index 0000000..019ebcf
--- /dev/null
+++ b/nn/runtime/test/generated/examples/lstm3_state_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: lstm3_state_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.596268f, 0.998386f, 0.568695f, 0.864524f, 0.571277f, 0.642421f, 0.52426f, 0.134799f, 0.003639f, 0.162482f}}, {1, {0.021393683f, 0.06124551f, 0.046905167f, -0.014657677f, -0.03149463f, 0.09171803f, 0.14647801f, 0.10797193f, -0.0057968358f, 0.0019193048f, -0.2726754f, 0.10154029f, -0.018539885f, 0.080349885f, -0.10262385f, -0.022599787f, -0.09121155f, -0.008675967f, -0.045206103f, -0.0821282f, -0.008045952f, 0.015478081f, 0.055217247f, 0.038719587f, 0.044153627f, -0.06453243f, 0.05031825f, -0.046935108f, -0.008164439f, 0.014574226f, -0.1671009f, -0.15519552f, -0.16819797f, -0.13971269f, -0.11953059f, 0.25005487f, -0.22790983f, 0.009855087f, -0.028140958f, -0.11200698f, 0.11295408f, -0.0035217577f, 0.054485075f, 0.05184695f, 0.064711206f, 0.10989193f, 0.11674786f, 0.03490607f, 0.07727357f, 0.11390585f, -0.1863375f, -0.1034451f, -0.13945189f, -0.049401227f, -0.18767063f, 0.042483903f, 0.14233552f, 0.13832581f, 0.18350165f, 0.14545603f, -0.028545704f, 0.024939531f, 0.050929718f, 0.0076203286f, -0.0029723682f, -0.042484224f, -0.11827596f, -0.09171104f, -0.10808628f, -0.16327988f, -0.2273378f, -0.0993647f, -0.017155107f, 0.0023917493f, 0.049272764f, 0.0038534778f, 0.054764505f, 0.089753784f, 0.06947234f, 0.08014476f, -0.04544234f, -0.0497073f, -0.07135631f, -0.048929106f, -0.004042012f, -0.009284026f, 0.018042054f, 0.0036860977f, -0.07427302f, -0.11434604f, -0.018995456f, 0.031487543f, 0.012834908f, 0.019977754f, 0.044256654f, -0.39292613f, -0.18519334f, -0.11651281f, -0.06809892f, 0.011373677f}}, {2, {-0.0018401089f, -0.004852237f, 0.03698424f, 0.014181704f, 0.028273236f, -0.016726194f, -0.05249759f, -0.10204261f, 0.00861066f, -0.040979505f, -0.009899187f, 0.01923892f, -0.028177269f, -0.08535103f, -0.14585495f, 0.10662567f, -0.01909731f, -0.017883534f, -0.0047269356f, -0.045103323f, 0.0030784295f, 0.076784775f, 0.07463696f, 0.094531395f, 0.0814421f, -0.12257899f, -0.033945758f, -0.031303465f, 0.045630626f, 0.06843887f, -0.13492945f, -0.012480007f, -0.0811829f, 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-0.07260381f, 0.047201227f, -0.024575593f, -0.036445823f, 0.07155557f, 0.009672501f, -0.02328883f, 0.009533515f, -0.03606021f, -0.07421458f, -0.028082801f, -0.2678904f, -0.13221288f, 0.18419984f, -0.13012612f, -0.014588381f, -0.035059117f, -0.04824723f, 0.07830115f, -0.056184657f, 0.03277091f, 0.025466874f, 0.14494097f, -0.12522776f, -0.098633975f, -0.10766018f, -0.08317623f, 0.08594209f, 0.07749552f, 0.039474737f, 0.1776665f, -0.07409566f, -0.0477268f, 0.29323658f, 0.10801441f, 0.1154011f, 0.013952499f, 0.10739139f, 0.10708251f, -0.051456142f, 0.0074137426f, -0.10430189f, 0.10034707f, 0.045594677f, 0.0635285f, -0.0715442f, -0.089667566f, -0.10811871f, 0.00026344223f, 0.08298446f, -0.009525053f, 0.006585689f, -0.24567553f, -0.09450807f, 0.09648481f, 0.026996298f, -0.06419476f, -0.04752702f, -0.11063944f, -0.23441927f, -0.17608605f, -0.052156363f, 0.067035615f, 0.19271925f, -0.0032889997f, -0.043264326f, 0.09663576f, -0.057112187f, -0.10100678f, 0.0628376f, 0.04447668f, 0.017961001f, -0.10094388f, -0.10190601f, 0.18335468f, 0.10494553f, -0.052095775f, -0.0026118709f, 0.10539724f, -0.04383912f, -0.042349473f, 0.08438151f, -0.1947263f, 0.02251204f, 0.11216432f, -0.10307853f, 0.17351969f, -0.039091777f, 0.08066188f, -0.00561982f, 0.12633002f, 0.11335965f, -0.0088127935f, -0.019777594f, 0.06864014f, -0.059751723f, 0.016233567f, -0.06894641f, -0.28651384f, -0.004228674f, 0.019708522f, -0.16305895f, -0.07468996f, -0.0855457f, 0.099339016f, -0.07580735f, -0.13775392f, 0.08434318f, 0.08330512f, -0.12131499f, 0.031935584f, 0.09180414f, -0.08876437f, -0.08049874f, 0.008753825f, 0.03498998f, 0.030215185f, 0.03907079f, 0.089751154f, 0.029194152f, -0.03337423f, -0.019092513f, 0.04331237f, 0.04299654f, -0.036394123f, -0.12915532f, 0.09793732f, 0.07512415f, -0.11319543f, -0.032502122f, 0.15661901f, 0.07671967f, -0.005491124f, -0.19379048f, -0.218606f, 0.21448623f, 0.017840758f, 0.1416943f, -0.07051762f, 0.19488361f, 0.02664691f, -0.18104725f, -0.09334311f, 0.15026465f, -0.15493552f, -0.057762887f, -0.11604192f, -0.262013f, -0.01391798f, 0.012185008f, 0.11156489f, -0.07483202f, 0.06693364f, -0.26151478f, 0.046425626f, 0.036540434f, -0.16435726f, 0.17338543f, -0.21401681f, -0.11385144f, -0.08283257f, -0.069031075f, 0.030635102f, 0.010969227f, 0.11109743f, 0.010919218f, 0.027526086f, 0.13519906f, 0.01891392f, -0.046839405f, -0.040167913f, 0.017953383f, -0.09700955f, 0.0061885654f, -0.07000971f, 0.026893595f, -0.038844477f, 0.14543656f}}, {17, {}}, {18, {-0.00396806f, 0.029352f, -0.00279226f, 0.0159977f, -0.00835577f, -0.0211779f, 0.0283512f, -0.0114597f, 0.00907307f, -0.0244004f, -0.0152191f, -0.0259063f, 0.00914318f, 0.00415119f, 0.017147f, 0.0134203f, -0.013869f, 0.0287268f, -0.00334694f, 0.00733397f, -0.0287926f, -0.0186926f, 0.0193662f, -0.0115437f, 0.00422612f, -0.0345232f, 0.00223253f, -0.00957321f, 0.0210624f, 0.013331f, 0.0150954f, 0.0216801f}}, {19, {-0.0531632f, -0.0118138f, 0.0870833f, 0.0347929f, -0.076144f, -0.0659219f, -0.0463811f, 0.0141307f, -0.0127706f, -0.03782f, -0.00402401f, -0.00571876f, -0.187957f, -0.0247127f, 0.0711425f, 0.008244f, 0.0492649f, 0.126972f, 0.0933097f, 0.29848f, -0.0966178f, -0.114417f, 0.0387229f, 0.0453255f, -0.181286f, -0.0651251f, -0.0996879f, -0.00276995f, 0.0617558f, -0.0100728f, 0.056304f, -0.077416f, -0.162858f, -0.0541251f, 0.0571202f, -0.0525331f, 0.0724297f, 0.171029f, 0.141738f, 0.295483f}}, {21, {0.0f}}, {22, {0.0f}}},
+  // int -> INT32 map
+  {{20, {4}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{1, {-0.0166936f, 0.0381209f, 0.000889684f, 0.0143363f, -0.0328911f, -0.0234288f, 0.0333051f, -0.012229f, 0.0110322f, -0.0457725f, -0.000832209f, -0.0202817f, 0.0327257f, 0.0121309f, 0.0155969f, 0.0312091f, -0.0141913f, 0.0322082f, 0.00227024f, 0.0260507f, -0.0188721f, -0.0296489f, 0.0399134f, -0.0160509f, 0.011604f, -0.0447318f, -0.0150515f, -0.0277406f, 0.0316596f, 0.0118233f, 0.0214762f, 0.0293641f}}, {2, {-0.154022f, -0.124934f, 0.0478463f, 0.0607819f, -0.218727f, -0.111053f, -0.103885f, -0.00447221f, 0.0554757f, -0.0207068f, 0.0595767f, -0.116297f, -0.249466f, -0.0723206f, 0.0794942f, -0.0377107f, 0.124532f, 0.249952f, 0.188641f, 0.411865f, -0.11012f, -0.0694494f, 0.103501f, 0.0428427f, -0.167345f, -0.106061f, -0.0775679f, 0.00936161f, 0.0105526f, -0.0314523f, 0.0243475f, -0.132179f, -0.258763f, -0.0307266f, 0.107047f, -0.0115197f, 0.0995485f, 0.220027f, 0.158355f, 0.436369f}}, {3, {-0.0166936f, 0.0381209f, 0.000889694f, 0.0143363f, -0.0328911f, -0.0234288f, 0.0333051f, -0.012229f, 0.0110322f, -0.0457725f, -0.000832209f, -0.0202817f, 0.0327257f, 0.0121308f, 0.0155969f, 0.0312091f, -0.0141913f, 0.0322082f, 0.00227024f, 0.0260507f, -0.0188721f, -0.0296489f, 0.0399134f, -0.0160509f, 0.0116039f, -0.0447318f, -0.0150515f, -0.0277406f, 0.0316596f, 0.0118233f, 0.0214762f, 0.0293641f}}, {0, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/lstm_relaxed.example.cpp b/nn/runtime/test/generated/examples/lstm_relaxed.example.cpp
new file mode 100644
index 0000000..b037d40
--- /dev/null
+++ b/nn/runtime/test/generated/examples/lstm_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: lstm_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {2.0f, 3.0f}}, {1, {-0.45018822f, -0.02338299f, -0.0870589f, -0.34550029f, 0.04266912f, -0.15680569f, -0.34856534f, 0.43890524f}}, {2, {0.09701663f, 0.20334584f, -0.50592935f, -0.31343272f, -0.40032279f, 0.44781327f, 0.01387155f, -0.35593212f}}, {3, {-0.50013041f, 0.1370284f, 0.11810488f, 0.2013163f, -0.20583314f, 0.44344562f, 0.22077113f, -0.29909778f}}, {4, {-0.25065863f, -0.28290087f, 0.04613829f, 0.40525138f, 0.44272184f, 0.03897077f, -0.1556896f, 0.19487578f}}, {5, {-0.0063535f, -0.2042388f, 0.31454784f, -0.35746509f, 0.28902304f, 0.08183324f, -0.16555229f, 0.02286911f, -0.13566875f, 0.03034258f, 0.48091322f, -0.12528998f, 0.24077177f, -0.51332325f, -0.33502164f, 0.10629296f}}, {6, {-0.48684245f, -0.06655136f, 0.42224967f, 0.2112639f, 0.27654213f, 0.20864892f, -0.07646349f, 0.45877004f, 0.00141793f, -0.14609534f, 0.36447752f, 0.09196436f, 0.28053468f, 0.01560611f, -0.20127171f, -0.01140004f}}, {7, {-0.3407414f, 0.24443203f, -0.2078532f, 0.26320225f, 0.05695659f, -0.00123841f, -0.4744786f, -0.35869038f, -0.06418842f, -0.13502428f, -0.501764f, 0.22830659f, -0.46367589f, 0.26016325f, -0.03894562f, -0.16368064f}}, {8, {0.43385774f, -0.17194885f, 0.2718237f, 0.09215671f, 0.24107647f, -0.39835793f, 0.18212086f, 0.01301402f, 0.48572797f, -0.50656658f, 0.20047462f, -0.20607421f, -0.51818722f, -0.15390486f, 0.0468148f, 0.39922136f}}, {9, {}}, {10, {}}, {11, {}}, {12, {0.0f, 0.0f, 0.0f, 0.0f}}, {13, {1.0f, 1.0f, 1.0f, 1.0f}}, {14, {0.0f, 0.0f, 0.0f, 0.0f}}, {15, {0.0f, 0.0f, 0.0f, 0.0f}}, {16, {}}, {17, {}}, {18, {0, 0, 0, 0}}, {19, {0, 0, 0, 0}}, {21, {0.0f}}, {22, {0.0f}}},
+  // int -> INT32 map
+  {{20, {4}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{1, {-0.0297319f, 0.122947f, 0.208851f, -0.153588f}}, {2, {-0.145439f, 0.157475f, 0.293663f, -0.277353f}}, {3, {-0.02973187f, 0.1229473f, 0.20885126f, -0.15358765f}}, {0, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/lstm_state2_relaxed.example.cpp b/nn/runtime/test/generated/examples/lstm_state2_relaxed.example.cpp
new file mode 100644
index 0000000..c5b3d8f
--- /dev/null
+++ b/nn/runtime/test/generated/examples/lstm_state2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: lstm_state2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 1.0f}}, {1, {-0.45018822f, -0.02338299f, -0.0870589f, -0.34550029f, 0.04266912f, -0.15680569f, -0.34856534f, 0.43890524f}}, {2, {0.09701663f, 0.20334584f, -0.50592935f, -0.31343272f, -0.40032279f, 0.44781327f, 0.01387155f, -0.35593212f}}, {3, {-0.50013041f, 0.1370284f, 0.11810488f, 0.2013163f, -0.20583314f, 0.44344562f, 0.22077113f, -0.29909778f}}, {4, {-0.25065863f, -0.28290087f, 0.04613829f, 0.40525138f, 0.44272184f, 0.03897077f, -0.1556896f, 0.19487578f}}, {5, {-0.0063535f, -0.2042388f, 0.31454784f, -0.35746509f, 0.28902304f, 0.08183324f, -0.16555229f, 0.02286911f, -0.13566875f, 0.03034258f, 0.48091322f, -0.12528998f, 0.24077177f, -0.51332325f, -0.33502164f, 0.10629296f}}, {6, {-0.48684245f, -0.06655136f, 0.42224967f, 0.2112639f, 0.27654213f, 0.20864892f, -0.07646349f, 0.45877004f, 0.00141793f, -0.14609534f, 0.36447752f, 0.09196436f, 0.28053468f, 0.01560611f, -0.20127171f, -0.01140004f}}, {7, {-0.3407414f, 0.24443203f, -0.2078532f, 0.26320225f, 0.05695659f, -0.00123841f, -0.4744786f, -0.35869038f, -0.06418842f, -0.13502428f, -0.501764f, 0.22830659f, -0.46367589f, 0.26016325f, -0.03894562f, -0.16368064f}}, {8, {0.43385774f, -0.17194885f, 0.2718237f, 0.09215671f, 0.24107647f, -0.39835793f, 0.18212086f, 0.01301402f, 0.48572797f, -0.50656658f, 0.20047462f, -0.20607421f, -0.51818722f, -0.15390486f, 0.0468148f, 0.39922136f}}, {9, {}}, {10, {}}, {11, {}}, {12, {0.0f, 0.0f, 0.0f, 0.0f}}, {13, {1.0f, 1.0f, 1.0f, 1.0f}}, {14, {0.0f, 0.0f, 0.0f, 0.0f}}, {15, {0.0f, 0.0f, 0.0f, 0.0f}}, {16, {}}, {17, {}}, {18, {-0.0371611f, 0.125073f, 0.411934f, -0.208605f}}, {19, {-0.287121f, 0.148115f, 0.556837f, -0.388276f}}, {21, {0.0f}}, {22, {0.0f}}},
+  // int -> INT32 map
+  {{20, {4}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{1, {0, 0, 0, 0}}, {2, {0, 0, 0, 0}}, {3, {-0.15053082f, 0.09120187f, 0.24278517f, -0.12222792f}}, {0, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/lstm_state_relaxed.example.cpp b/nn/runtime/test/generated/examples/lstm_state_relaxed.example.cpp
new file mode 100644
index 0000000..4ed3805
--- /dev/null
+++ b/nn/runtime/test/generated/examples/lstm_state_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: lstm_state_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {3.0f, 4.0f}}, {1, {-0.45018822f, -0.02338299f, -0.0870589f, -0.34550029f, 0.04266912f, -0.15680569f, -0.34856534f, 0.43890524f}}, {2, {0.09701663f, 0.20334584f, -0.50592935f, -0.31343272f, -0.40032279f, 0.44781327f, 0.01387155f, -0.35593212f}}, {3, {-0.50013041f, 0.1370284f, 0.11810488f, 0.2013163f, -0.20583314f, 0.44344562f, 0.22077113f, -0.29909778f}}, {4, {-0.25065863f, -0.28290087f, 0.04613829f, 0.40525138f, 0.44272184f, 0.03897077f, -0.1556896f, 0.19487578f}}, {5, {-0.0063535f, -0.2042388f, 0.31454784f, -0.35746509f, 0.28902304f, 0.08183324f, -0.16555229f, 0.02286911f, -0.13566875f, 0.03034258f, 0.48091322f, -0.12528998f, 0.24077177f, -0.51332325f, -0.33502164f, 0.10629296f}}, {6, {-0.48684245f, -0.06655136f, 0.42224967f, 0.2112639f, 0.27654213f, 0.20864892f, -0.07646349f, 0.45877004f, 0.00141793f, -0.14609534f, 0.36447752f, 0.09196436f, 0.28053468f, 0.01560611f, -0.20127171f, -0.01140004f}}, {7, {-0.3407414f, 0.24443203f, -0.2078532f, 0.26320225f, 0.05695659f, -0.00123841f, -0.4744786f, -0.35869038f, -0.06418842f, -0.13502428f, -0.501764f, 0.22830659f, -0.46367589f, 0.26016325f, -0.03894562f, -0.16368064f}}, {8, {0.43385774f, -0.17194885f, 0.2718237f, 0.09215671f, 0.24107647f, -0.39835793f, 0.18212086f, 0.01301402f, 0.48572797f, -0.50656658f, 0.20047462f, -0.20607421f, -0.51818722f, -0.15390486f, 0.0468148f, 0.39922136f}}, {9, {}}, {10, {}}, {11, {}}, {12, {0.0f, 0.0f, 0.0f, 0.0f}}, {13, {1.0f, 1.0f, 1.0f, 1.0f}}, {14, {0.0f, 0.0f, 0.0f, 0.0f}}, {15, {0.0f, 0.0f, 0.0f, 0.0f}}, {16, {}}, {17, {}}, {18, {-0.0297319f, 0.122947f, 0.208851f, -0.153588f}}, {19, {-0.145439f, 0.157475f, 0.293663f, -0.277353f}}, {21, {0.0f}}, {22, {0.0f}}},
+  // int -> INT32 map
+  {{20, {4}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{1, {-0.0371611f, 0.125073f, 0.411934f, -0.208605f}}, {2, {-0.287121f, 0.148115f, 0.556837f, -0.388276f}}, {3, {-0.03716109f, 0.12507336f, 0.41193449f, -0.20860538f}}, {0, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/max_pool_float_1_relaxed.example.cpp b/nn/runtime/test/generated/examples/max_pool_float_1_relaxed.example.cpp
new file mode 100644
index 0000000..ebeda6c
--- /dev/null
+++ b/nn/runtime/test/generated/examples/max_pool_float_1_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: max_pool_float_1_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/max_pool_float_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/max_pool_float_2_relaxed.example.cpp
new file mode 100644
index 0000000..418862f
--- /dev/null
+++ b/nn/runtime/test/generated/examples/max_pool_float_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: max_pool_float_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 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18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/max_pool_float_3_relaxed.example.cpp b/nn/runtime/test/generated/examples/max_pool_float_3_relaxed.example.cpp
new file mode 100644
index 0000000..c96bd6b
--- /dev/null
+++ b/nn/runtime/test/generated/examples/max_pool_float_3_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: max_pool_float_3_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 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4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/mobilenet_224_gender_basic_fixed.example.cpp b/nn/runtime/test/generated/examples/mobilenet_224_gender_basic_fixed.example.cpp
index 5d4e187..ce855a9 100644
--- a/nn/runtime/test/generated/examples/mobilenet_224_gender_basic_fixed.example.cpp
+++ b/nn/runtime/test/generated/examples/mobilenet_224_gender_basic_fixed.example.cpp
@@ -13,7 +13,7 @@
 //Output(s)
 { // See tools/test_generator/include/TestHarness.h:MixedTyped
   // int -> FLOAT32 map
-  {{0, {0.605074f, 0.0733608f, 0.0200205f, 0.114568f, 0.178815f, 0.0580576f, 0.123144f, 0.232838f, 0.0916902f, 0.111395f, 0.138349f}}},
+  {{0, {0.605085f, 0.0733608f, 0.0200205f, 0.114568f, 0.178815f, 0.0580576f, 0.123144f, 0.232838f, 0.0916902f, 0.111395f, 0.138349f}}},
   // int -> INT32 map
   {},
   // int -> QUANT8_ASYMM map
diff --git a/nn/runtime/test/generated/examples/mobilenet_224_gender_basic_fixed_relaxed.example.cpp b/nn/runtime/test/generated/examples/mobilenet_224_gender_basic_fixed_relaxed.example.cpp
new file mode 100644
index 0000000..aea5d2b
--- /dev/null
+++ b/nn/runtime/test/generated/examples/mobilenet_224_gender_basic_fixed_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: mobilenet_224_gender_basic_fixed_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.791841f, 0.131271f, 0.840444f, 0.524133f, 0.301398f, 0.711596f, 8.78908e-05f, 0.358888f, 0.156309f, 0.273055f, 0.143706f, 0.663516f, 0.817875f, 0.0178006f, 0.0663899f, 0.38532f, 0.108224f, 0.120309f, 0.252355f, 0.468634f, 0.535587f, 0.372087f, 0.0191815f, 0.0750463f, 0.896686f, 0.564102f, 0.781927f, 0.138955f, 0.876559f, 0.672544f, 0.47254f, 0.685613f, 0.864712f, 0.678431f, 0.681087f, 0.954624f, 0.707985f, 0.0945955f, 0.663676f, 0.0174337f, 0.514265f, 0.0993437f, 0.837646f, 0.16886f, 0.0206787f, 0.460454f, 0.298217f, 0.0939906f, 0.792089f, 0.145739f, 0.124991f, 0.152928f, 0.18507f, 0.0910606f, 0.886938f, 0.703805f, 0.738545f, 0.0914867f, 0.785625f, 0.255978f, 0.25971f, 0.564347f, 0.496365f, 0.40138f, 0.181351f, 0.229051f, 0.528806f, 0.815946f, 0.723594f, 0.0782805f, 0.417488f, 0.357831f, 0.699987f, 0.110877f, 0.706929f, 0.361355f, 0.44735f, 0.51417f, 0.234213f, 0.49157f, 0.754239f, 0.35671f, 0.90015f, 0.368686f, 0.162982f, 0.467298f, 0.712059f, 0.73199f, 0.394652f, 0.216439f, 0.0325005f, 0.675254f, 0.0965207f, 0.919576f, 0.46926f, 0.923022f, 0.0721544f, 0.0620356f, 0.570436f, 0.418233f, 0.734994f, 0.626141f, 0.189962f, 0.680934f, 0.576122f, 0.377738f, 0.927142f, 0.31627f, 0.0390065f, 0.305891f, 0.777981f, 0.576827f, 0.999185f, 0.849222f, 0.221597f, 0.0529092f, 0.741046f, 0.810611f, 0.641734f, 0.2737f, 0.0306115f, 0.382373f, 0.117532f, 0.690233f, 0.20231f, 0.599944f, 0.464123f, 0.79606f, 0.171281f, 0.0924674f, 0.502584f, 0.689291f, 0.549744f, 0.951152f, 0.579524f, 0.796293f, 0.971173f, 0.903601f, 0.376714f, 0.915486f, 0.521651f, 0.888365f, 0.355228f, 0.648741f, 0.900593f, 0.48239f, 0.317946f, 0.524421f, 0.99061f, 0.842221f, 0.102702f, 0.679481f, 0.588507f, 0.7512f, 0.177413f, 0.762043f, 0.63814f, 0.509979f, 0.245258f, 0.97713f, 0.206899f, 0.0342631f, 0.582589f, 0.677466f, 0.548678f, 0.969459f, 0.763207f, 0.659911f, 0.720006f, 0.492729f, 0.721137f, 0.198181f, 0.0767499f, 0.279166f, 0.563685f, 0.578014f, 0.284114f, 0.0313309f, 0.545107f, 0.675547f, 0.902745f, 0.799514f, 0.14417f, 0.197687f, 0.187282f, 0.0420023f, 0.238308f, 0.154671f, 0.243883f, 0.777129f, 0.291907f, 0.959133f, 0.166203f, 0.355963f, 0.831646f, 0.308086f, 0.148097f, 0.342163f, 0.366069f, 0.669976f, 0.482005f, 0.50455f, 0.114772f, 0.909615f, 0.592529f, 0.819863f, 0.7448f, 0.733599f, 0.0818953f, 0.333677f, 0.436425f, 0.640028f, 0.128689f, 0.802751f, 0.053884f, 0.0968059f, 0.0141547f, 0.189447f, 0.458282f, 0.301719f, 0.332669f, 0.697625f, 0.607359f, 0.96581f, 0.0482129f, 0.658574f, 0.283779f, 0.428031f, 0.120848f, 0.387377f, 0.169832f, 0.0381746f, 0.549549f, 0.721105f, 0.281996f, 0.282577f, 0.183188f, 0.237784f, 0.590087f, 0.289398f, 0.540784f, 0.301099f, 0.396178f, 0.855404f, 0.460563f, 0.125632f, 0.150601f, 0.271058f, 0.696146f, 0.947483f, 0.735739f, 0.425141f, 0.977515f, 0.3452f, 0.143326f, 0.274614f, 0.925826f, 0.81308f, 0.535078f, 0.998599f, 0.427464f, 0.260845f, 0.137486f, 0.837797f, 0.0631066f, 0.0876196f, 0.588056f, 0.40014f, 0.815027f, 0.494389f, 0.355774f, 0.450119f, 0.717888f, 0.423054f, 0.20979f, 0.842124f, 0.399906f, 0.410846f, 0.559933f, 0.451017f, 0.558568f, 0.944169f, 0.881834f, 0.00384158f, 0.103625f, 0.309752f, 0.40491f, 0.98423f, 0.303001f, 0.486862f, 0.394447f, 0.108623f, 0.258184f, 0.172573f, 0.0685831f, 0.358462f, 0.272746f, 0.875298f, 0.690985f, 0.800497f, 0.512517f, 0.692277f, 0.0706645f, 0.259856f, 0.37559f, 0.213658f, 0.53025f, 0.405643f, 0.656994f, 0.228048f, 0.247219f, 0.300241f, 0.700641f, 0.0177141f, 0.466215f, 0.200764f, 0.857363f, 0.483106f, 0.522657f, 0.144218f, 0.267424f, 0.291684f, 0.67167f, 0.0357309f, 0.265176f, 0.520329f, 0.556993f, 0.984931f, 0.183227f, 0.335942f, 0.992855f, 0.175479f, 0.425192f, 0.826319f, 0.433081f, 0.727791f, 0.245524f, 0.0597154f, 0.156634f, 0.64591f, 0.958063f, 0.537418f, 0.295089f, 0.0732913f, 0.742363f, 0.642074f, 0.826581f, 0.682193f, 0.852718f, 0.999771f, 0.315818f, 0.571465f, 0.491486f, 0.235984f, 0.0818711f, 0.636604f, 0.212895f, 0.660947f, 0.765877f, 0.0767624f, 0.73344f, 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0.645657f, 0.199259f, 0.724836f, 0.258711f, 0.771646f, 0.623592f, 0.7923f, 0.525011f, 0.79812f, 0.917418f, 0.0408786f, 0.70516f, 0.685949f, 0.845311f, 0.848584f, 0.816048f, 0.577728f, 0.0632474f, 0.0337705f, 0.749029f, 0.354352f, 0.115613f, 0.405688f, 0.354145f, 0.0960672f, 0.545181f, 0.128382f, 0.707834f, 0.777129f, 0.455415f, 0.291398f, 0.202387f, 0.312735f, 0.231164f, 0.915044f, 0.105688f, 0.992714f, 0.475474f, 0.547683f, 0.536471f, 0.12417f, 0.890503f, 0.969704f, 0.398818f, 0.652417f, 0.43562f, 0.459029f, 0.526732f, 0.623382f, 0.328677f, 0.629836f, 0.921082f, 0.18711f, 0.214384f, 0.233311f, 0.226147f, 0.797971f, 0.534456f, 0.256337f, 0.689548f, 0.193202f, 0.503527f, 0.132612f, 0.0113974f, 0.561125f, 0.951401f, 0.642326f, 0.713237f, 0.257228f, 0.287788f, 0.0727935f, 0.992315f, 0.492784f, 0.753093f, 0.787538f, 0.302604f, 0.276507f, 0.421724f, 0.53667f, 0.521195f, 0.914161f, 0.477701f, 0.667751f, 0.834651f, 0.719402f, 0.622925f, 0.610117f, 0.0918504f, 0.827973f, 0.776474f, 0.997031f, 0.604986f, 0.693104f, 0.920856f, 0.953291f, 0.753704f, 0.937652f, 0.49416f, 0.0343811f, 0.210229f, 0.718012f, 0.00326219f, 0.662774f, 0.545044f, 0.605222f, 0.793254f, 0.812442f, 0.223717f, 0.222193f, 0.414127f, 0.109099f, 0.0470771f, 0.81452f, 0.52753f, 0.40668f, 0.862339f, 0.45624f, 0.403171f, 0.949618f, 0.0508641f, 0.107696f, 0.548259f, 0.703493f, 0.77282f, 0.897441f, 0.960316f, 0.375285f, 0.672975f, 0.0594269f, 0.211847f, 0.596767f, 0.375966f, 0.264368f, 0.153689f, 0.43175f, 0.334658f, 0.792881f, 0.712137f, 0.255055f, 0.835249f, 0.19435f, 0.523901f, 0.747742f, 0.021932f, 0.825722f, 0.12995f, 0.746476f, 0.0302897f, 0.143445f, 0.633426f, 0.667043f, 0.062095f, 0.378326f, 0.992086f, 0.460239f, 0.868868f, 0.510366f, 0.870358f, 0.384342f, 0.225636f, 0.0825906f, 0.0475967f, 0.202343f, 0.63943f, 0.753755f, 0.00888219f, 0.92597f, 0.4676f, 0.526284f, 0.312375f, 0.526216f, 0.663695f, 0.0312666f, 0.102075f, 0.0150701f, 0.693283f, 0.997117f, 0.954093f, 0.815279f, 0.763802f, 0.725875f, 0.292492f, 0.344055f, 0.627345f, 0.522168f, 0.621334f, 0.333947f, 0.1424f, 0.165267f, 0.499736f, 0.746754f, 0.79877f, 0.776785f, 0.557139f, 0.0425215f, 0.90292f, 0.316732f, 0.869703f, 0.785483f, 0.0158521f, 0.94999f, 0.484853f, 0.980765f, 0.216394f, 0.536688f, 0.882527f, 0.29969f, 0.474124f, 0.660068f, 0.978133f, 0.562514f, 0.922584f, 0.106834f, 0.561946f, 0.898387f, 0.53585f, 0.520597f, 0.411147f, 0.0280199f, 0.0521744f, 0.98895f, 0.0385853f, 0.0455102f, 0.970508f, 0.256327f, 0.0389597f, 0.624331f, 0.274006f, 0.378284f, 0.33111f, 0.482736f, 0.923735f, 0.0209944f, 0.931935f, 0.435454f, 0.174434f, 0.346234f, 0.317617f, 0.850623f, 0.278118f, 0.927707f, 0.513877f, 0.381132f, 0.44689f, 0.930011f, 0.607872f, 0.928808f, 0.299398f, 0.203065f, 0.120989f, 0.316432f, 0.383152f, 0.842135f, 0.704556f, 0.118635f, 0.422995f, 0.000466669f, 0.147807f, 0.502291f, 0.993403f, 0.601303f, 0.222253f, 0.0296877f, 0.0284052f, 0.87341f, 0.233206f, 0.0381863f, 0.700907f, 0.689801f, 0.399134f, 0.784999f, 0.63014f, 0.865453f, 0.287433f, 0.990328f, 0.882574f, 0.0774038f, 0.778073f, 0.484293f, 0.738884f, 0.684839f, 0.468305f, 0.0653757f, 0.997647f, 0.0303581f, 0.0133819f, 0.670839f, 0.505136f, 0.607782f, 0.915422f, 0.861656f, 0.149417f, 0.707365f, 0.602442f, 0.647925f, 0.511412f, 0.956392f, 0.726319f, 0.30591f, 0.561806f, 0.297597f, 0.527965f, 0.43694f, 0.773655f, 0.763751f, 0.493458f, 0.224437f, 0.938869f, 0.546626f, 0.641176f, 0.676299f, 0.120913f, 0.244841f, 0.913733f, 0.392493f, 0.380461f, 0.917425f, 0.346866f, 0.946269f, 0.115818f, 0.19961f, 0.900466f, 0.0815982f, 0.91916f, 0.461648f, 0.865653f, 0.983458f, 0.810979f, 0.762103f, 0.384499f, 0.572888f, 0.156534f, 0.281532f, 0.862645f, 0.278199f, 0.337823f, 0.407339f, 0.193315f, 0.384848f, 0.986914f, 0.819812f, 0.828864f, 0.658969f, 0.424426f, 0.0739355f, 0.947452f, 0.368272f, 0.402025f, 0.242601f, 0.693957f, 0.215303f, 0.814995f, 0.265798f, 0.0264865f, 0.286466f, 0.015661f, 0.583045f, 0.291179f, 0.669322f, 0.511267f, 0.229816f, 0.131331f, 0.730827f, 0.74252f, 0.93343f, 0.720619f, 0.612438f, 0.259147f, 0.112357f, 0.586765f, 0.0858606f, 0.153671f, 0.773048f, 0.822479f, 0.443573f, 0.55486f, 0.910416f, 0.85707f, 0.0148852f, 0.853716f, 0.228104f, 0.513679f, 0.951789f, 0.727959f, 0.200735f, 0.210806f, 0.125079f, 0.228391f, 0.209873f, 0.237775f, 0.108994f, 0.446076f, 0.221169f, 0.834191f, 0.98984f, 0.0542308f, 0.58488f, 0.315972f, 0.254531f, 0.828329f, 0.904021f, 0.875414f, 0.150553f, 0.0298306f, 0.215226f, 0.586307f, 0.417627f, 0.479362f, 0.172838f, 0.5259f, 0.908004f, 0.0605249f, 0.859353f, 0.828878f, 0.984935f, 0.39564f, 0.749108f, 0.526107f, 0.157768f, 0.336767f, 0.580207f, 0.598838f, 0.755481f, 0.144988f, 0.698507f, 0.464909f, 0.344876f, 0.172977f, 0.468696f, 0.668333f, 0.919779f, 0.232349f, 0.715044f, 0.280844f, 0.1119f, 0.676872f, 0.209419f, 0.0207841f, 0.770692f, 0.610173f, 0.803793f, 0.47074f, 0.186878f, 0.269158f, 0.749201f, 0.540574f, 0.915717f, 0.523814f, 0.571266f, 0.10382f, 0.811718f, 0.731922f, 0.468545f, 0.708574f, 0.323435f, 0.610058f, 0.45889f, 0.356482f, 0.981413f, 0.812081f, 0.802843f, 0.140016f, 0.27479f, 0.879972f, 0.976442f, 0.0214847f, 0.606645f, 0.452834f, 0.33259f, 0.259304f, 0.324395f, 0.22969f, 0.0908657f, 0.994912f, 0.00520821f, 0.219624f, 0.419453f, 0.820987f, 0.279137f, 0.787163f, 0.742862f, 0.702888f, 0.0585412f, 0.17378f, 0.803108f, 0.967417f, 0.554914f, 0.676712f, 0.801808f, 0.203466f, 0.917554f, 0.547952f, 0.110401f, 0.566604f, 0.000901547f, 0.428874f, 0.410979f, 0.882269f, 0.568531f, 0.204807f, 0.158472f, 0.797748f, 0.923136f, 0.626076f, 0.995379f, 0.970147f, 0.636004f, 0.256138f, 0.263984f, 0.0188201f, 0.836662f, 0.891073f, 0.815278f, 0.213562f, 0.265101f, 0.287762f, 0.853247f, 0.162469f, 0.27606f, 0.396637f, 0.0501615f, 0.519138f, 0.364286f, 0.0357294f, 0.34329f, 0.43058f, 0.134315f, 0.399785f, 0.243176f, 0.897879f, 0.0347835f, 0.977129f, 0.964701f, 0.992374f, 0.5317f, 0.855217f, 0.0626301f, 0.720206f, 0.157749f, 0.331044f, 0.119822f, 0.361034f, 0.657655f, 0.734292f, 0.487953f, 0.878978f, 0.348533f, 0.361729f, 0.655813f, 0.495023f, 0.407889f, 0.922945f, 0.903442f, 0.38402f, 0.512097f, 0.429171f, 0.506999f, 0.895231f, 0.182171f, 0.618858f, 0.88438f, 0.296033f, 0.481725f, 0.858442f, 0.493233f, 0.151025f, 0.16046f, 0.180032f, 0.441936f, 0.211194f, 0.7617f, 0.867114f, 0.199935f, 0.743809f, 0.637003f, 0.808767f, 0.561247f, 0.776601f, 0.43555f, 0.188716f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.605074f, 0.0733608f, 0.0200205f, 0.114568f, 0.178815f, 0.0580576f, 0.123144f, 0.232838f, 0.0916902f, 0.111395f, 0.138349f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/mul_relaxed.example.cpp b/nn/runtime/test/generated/examples/mul_relaxed.example.cpp
new file mode 100644
index 0000000..bc6969a
--- /dev/null
+++ b/nn/runtime/test/generated/examples/mul_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: mul_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {2, -4, 8, -16}}, {1, {32, -16, -8, 4}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {64, 64, -64, -64}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/mul_relu_relaxed.example.cpp b/nn/runtime/test/generated/examples/mul_relu_relaxed.example.cpp
new file mode 100644
index 0000000..ffaa6ea
--- /dev/null
+++ b/nn/runtime/test/generated/examples/mul_relu_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: mul_relu_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {2, -4, 8, -16}}, {1, {32, -16, -8, 4}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {64, 64, 0, 0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/relu1_float_1_relaxed.example.cpp b/nn/runtime/test/generated/examples/relu1_float_1_relaxed.example.cpp
new file mode 100644
index 0000000..09c7db3
--- /dev/null
+++ b/nn/runtime/test/generated/examples/relu1_float_1_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: relu1_float_1_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-10.0f, -0.5f, 0.5f, 10.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-1.0f, -0.5f, 0.5f, 1.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/relu1_float_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/relu1_float_2_relaxed.example.cpp
new file mode 100644
index 0000000..833d186
--- /dev/null
+++ b/nn/runtime/test/generated/examples/relu1_float_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: relu1_float_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
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-2.436f, 2.437f, -2.438f, 2.439f, -2.44f, 2.441f, -2.442f, 2.443f, -2.444f, 2.445f, -2.446f, 2.447f, -2.448f, 2.449f, -2.45f, 2.451f, -2.452f, 2.453f, -2.454f, 2.455f, -2.456f, 2.457f, -2.458f, 2.459f, -2.46f, 2.461f, -2.462f, 2.463f, -2.464f, 2.465f, -2.466f, 2.467f, -2.468f, 2.469f, -2.47f, 2.471f, -2.472f, 2.473f, -2.474f, 2.475f, -2.476f, 2.477f, -2.478f, 2.479f, -2.48f, 2.481f, -2.482f, 2.483f, -2.484f, 2.485f, -2.486f, 2.487f, -2.488f, 2.489f, -2.49f, 2.491f, -2.492f, 2.493f, -2.494f, 2.495f, -2.496f, 2.497f, -2.498f, 2.499f, -2.5f, 2.501f, -2.5020000000000002f, 2.503f, -2.504f, 2.505f, -2.5060000000000002f, 2.507f, -2.508f, 2.509f, -2.5100000000000002f, 2.511f, -2.512f, 2.513f, -2.5140000000000002f, 2.515f, -2.516f, 2.517f, -2.5180000000000002f, 2.519f, -2.52f, 2.521f, -2.5220000000000002f, 2.523f, -2.524f, 2.525f, -2.5260000000000002f, 2.527f, -2.528f, 2.529f, -2.5300000000000002f, 2.531f, -2.532f, 2.533f, -2.5340000000000003f, 2.535f, -2.536f, 2.537f, -2.5380000000000003f, 2.539f, -2.54f, 2.541f, -2.5420000000000003f, 2.543f, -2.544f, 2.545f, -2.5460000000000003f, 2.547f, -2.548f, 2.549f, -2.5500000000000003f, 2.551f, -2.552f, 2.553f, -2.5540000000000003f, 2.555f, -2.556f, 2.557f, -2.5580000000000003f, 2.559f, -2.56f, 2.561f, -2.562f, 2.563f, -2.564f, 2.565f, -2.566f, 2.567f, -2.568f, 2.569f, -2.57f, 2.571f, -2.572f, 2.573f, -2.574f, 2.575f, -2.576f, 2.577f, -2.578f, 2.579f, -2.58f, 2.581f, -2.582f, 2.583f, -2.584f, 2.585f, -2.586f, 2.587f, -2.588f, 2.589f, -2.59f, 2.591f, -2.592f, 2.593f, -2.594f, 2.595f, -2.596f, 2.597f, -2.598f, 2.599f, -2.6f, 2.601f, -2.602f, 2.603f, -2.604f, 2.605f, -2.606f, 2.607f, -2.608f, 2.609f, -2.61f, 2.611f, -2.612f, 2.613f, -2.614f, 2.615f, -2.616f, 2.617f, -2.618f, 2.619f, -2.62f, 2.621f, -2.622f, 2.623f, -2.624f, 2.625f, -2.626f, 2.6270000000000002f, -2.628f, 2.629f, -2.63f, 2.6310000000000002f, -2.632f, 2.633f, -2.634f, 2.6350000000000002f, -2.636f, 2.637f, -2.638f, 2.6390000000000002f, -2.64f, 2.641f, -2.642f, 2.6430000000000002f, -2.644f, 2.645f, -2.646f, 2.6470000000000002f, -2.648f, 2.649f, -2.65f, 2.6510000000000002f, -2.652f, 2.653f, -2.654f, 2.6550000000000002f, -2.656f, 2.657f, -2.658f, 2.6590000000000003f, -2.66f, 2.661f, -2.662f, 2.6630000000000003f, -2.664f, 2.665f, -2.666f, 2.6670000000000003f, -2.668f, 2.669f, -2.67f, 2.6710000000000003f, -2.672f, 2.673f, -2.674f, 2.6750000000000003f, -2.676f, 2.677f, -2.678f, 2.6790000000000003f, -2.68f, 2.681f, -2.682f, 2.6830000000000003f, -2.684f, 2.685f, -2.686f, 2.6870000000000003f, -2.688f, 2.689f, -2.69f, 2.691f, -2.692f, 2.693f, -2.694f, 2.695f, -2.696f, 2.697f, -2.698f, 2.699f, -2.7f, 2.701f, -2.702f, 2.703f, -2.704f, 2.705f, -2.706f, 2.707f, -2.708f, 2.709f, -2.71f, 2.711f, -2.712f, 2.713f, -2.714f, 2.715f, -2.716f, 2.717f, -2.718f, 2.719f, -2.72f, 2.721f, -2.722f, 2.723f, -2.724f, 2.725f, -2.726f, 2.727f, -2.728f, 2.729f, -2.73f, 2.731f, -2.732f, 2.733f, -2.734f, 2.735f, -2.736f, 2.737f, -2.738f, 2.739f, -2.74f, 2.741f, -2.742f, 2.743f, -2.744f, 2.745f, -2.746f, 2.747f, -2.748f, 2.749f, -2.75f, 2.751f, -2.7520000000000002f, 2.753f, -2.754f, 2.755f, -2.7560000000000002f, 2.757f, -2.758f, 2.759f, -2.7600000000000002f, 2.761f, -2.762f, 2.763f, -2.7640000000000002f, 2.765f, -2.766f, 2.767f, -2.7680000000000002f, 2.769f, -2.77f, 2.771f, -2.7720000000000002f, 2.773f, -2.774f, 2.775f, -2.7760000000000002f, 2.777f, -2.778f, 2.779f, -2.7800000000000002f, 2.781f, -2.782f, 2.783f, -2.7840000000000003f, 2.785f, -2.786f, 2.787f, -2.7880000000000003f, 2.789f, -2.79f, 2.791f, -2.7920000000000003f, 2.793f, -2.794f, 2.795f, -2.7960000000000003f, 2.797f, -2.798f, 2.799f, -2.8000000000000003f, 2.801f, -2.802f, 2.803f, -2.8040000000000003f, 2.805f, -2.806f, 2.807f, -2.8080000000000003f, 2.809f, -2.81f, 2.811f, -2.8120000000000003f, 2.813f, -2.814f, 2.815f, -2.816f, 2.817f, -2.818f, 2.819f, -2.82f, 2.821f, -2.822f, 2.823f, -2.824f, 2.825f, -2.826f, 2.827f, -2.828f, 2.829f, -2.83f, 2.831f, -2.832f, 2.833f, -2.834f, 2.835f, -2.836f, 2.837f, -2.838f, 2.839f, -2.84f, 2.841f, -2.842f, 2.843f, -2.844f, 2.845f, -2.846f, 2.847f, -2.848f, 2.849f, -2.85f, 2.851f, -2.852f, 2.853f, -2.854f, 2.855f, -2.856f, 2.857f, -2.858f, 2.859f, -2.86f, 2.861f, -2.862f, 2.863f, -2.864f, 2.865f, -2.866f, 2.867f, -2.868f, 2.869f, -2.87f, 2.871f, -2.872f, 2.873f, -2.874f, 2.875f, -2.876f, 2.8770000000000002f, -2.878f, 2.879f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.0f, 0.001f, -0.002f, 0.003f, -0.004f, 0.005f, -0.006f, 0.007f, -0.008f, 0.009000000000000001f, -0.01f, 0.011f, -0.012f, 0.013000000000000001f, -0.014f, 0.015f, -0.016f, 0.017f, -0.018000000000000002f, 0.019f, -0.02f, 0.021f, -0.022f, 0.023f, -0.024f, 0.025f, -0.026000000000000002f, 0.027f, -0.028f, 0.029f, -0.03f, 0.031f, -0.032f, 0.033f, -0.034f, 0.035f, -0.036000000000000004f, 0.037f, -0.038f, 0.039f, -0.04f, 0.041f, -0.042f, 0.043000000000000003f, -0.044f, 0.045f, -0.046f, 0.047f, -0.048f, 0.049f, -0.05f, 0.051000000000000004f, -0.052000000000000005f, 0.053f, -0.054f, 0.055f, -0.056f, 0.057f, -0.058f, 0.059000000000000004f, -0.06f, 0.061f, -0.062f, 0.063f, -0.064f, 0.065f, -0.066f, 0.067f, -0.068f, 0.069f, -0.07f, 0.07100000000000001f, -0.07200000000000001f, 0.073f, -0.074f, 0.075f, -0.076f, 0.077f, -0.078f, 0.079f, -0.08f, 0.081f, -0.082f, 0.083f, -0.084f, 0.085f, -0.08600000000000001f, 0.08700000000000001f, -0.088f, 0.089f, -0.09f, 0.091f, -0.092f, 0.093f, -0.094f, 0.095f, -0.096f, 0.097f, -0.098f, 0.099f, -0.1f, 0.101f, -0.10200000000000001f, 0.10300000000000001f, -0.10400000000000001f, 0.105f, -0.106f, 0.107f, -0.108f, 0.109f, -0.11f, 0.111f, -0.112f, 0.113f, -0.114f, 0.115f, -0.116f, 0.117f, -0.11800000000000001f, 0.11900000000000001f, -0.12f, 0.121f, -0.122f, 0.123f, -0.124f, 0.125f, -0.126f, 0.127f, -0.128f, 0.129f, -0.13f, 0.131f, -0.132f, 0.133f, -0.134f, 0.135f, -0.136f, 0.137f, -0.138f, 0.139f, -0.14f, 0.14100000000000001f, -0.14200000000000002f, 0.14300000000000002f, -0.14400000000000002f, 0.145f, -0.146f, 0.147f, -0.148f, 0.149f, -0.15f, 0.151f, -0.152f, 0.153f, -0.154f, 0.155f, -0.156f, 0.157f, -0.158f, 0.159f, -0.16f, 0.161f, -0.162f, 0.163f, -0.164f, 0.165f, -0.166f, 0.167f, -0.168f, 0.169f, -0.17f, 0.171f, -0.17200000000000001f, 0.17300000000000001f, -0.17400000000000002f, 0.17500000000000002f, -0.176f, 0.177f, -0.178f, 0.179f, -0.18f, 0.181f, -0.182f, 0.183f, -0.184f, 0.185f, -0.186f, 0.187f, -0.188f, 0.189f, -0.19f, 0.191f, -0.192f, 0.193f, -0.194f, 0.195f, -0.196f, 0.197f, -0.198f, 0.199f, -0.2f, 0.201f, -0.202f, 0.203f, -0.20400000000000001f, 0.20500000000000002f, -0.20600000000000002f, 0.20700000000000002f, -0.20800000000000002f, 0.209f, -0.21f, 0.211f, -0.212f, 0.213f, -0.214f, 0.215f, -0.216f, 0.217f, -0.218f, 0.219f, -0.22f, 0.221f, -0.222f, 0.223f, -0.224f, 0.225f, -0.226f, 0.227f, -0.228f, 0.229f, -0.23f, 0.231f, -0.232f, 0.233f, -0.234f, 0.23500000000000001f, -0.23600000000000002f, 0.23700000000000002f, -0.23800000000000002f, 0.23900000000000002f, -0.24f, 0.241f, -0.242f, 0.243f, -0.244f, 0.245f, -0.246f, 0.247f, -0.248f, 0.249f, -0.25f, 0.251f, -0.252f, 0.253f, -0.254f, 0.255f, -0.256f, 0.257f, -0.258f, 0.259f, -0.26f, 0.261f, -0.262f, 0.263f, -0.264f, 0.265f, -0.266f, 0.267f, -0.268f, 0.269f, -0.27f, 0.271f, -0.272f, 0.273f, -0.274f, 0.275f, -0.276f, 0.277f, -0.278f, 0.279f, -0.28f, 0.281f, -0.28200000000000003f, 0.28300000000000003f, -0.28400000000000003f, 0.28500000000000003f, -0.28600000000000003f, 0.28700000000000003f, -0.28800000000000003f, 0.289f, -0.29f, 0.291f, -0.292f, 0.293f, -0.294f, 0.295f, -0.296f, 0.297f, -0.298f, 0.299f, -0.3f, 0.301f, -0.302f, 0.303f, -0.304f, 0.305f, -0.306f, 0.307f, -0.308f, 0.309f, -0.31f, 0.311f, -0.312f, 0.313f, -0.314f, 0.315f, -0.316f, 0.317f, -0.318f, 0.319f, -0.32f, 0.321f, -0.322f, 0.323f, -0.324f, 0.325f, -0.326f, 0.327f, -0.328f, 0.329f, -0.33f, 0.331f, -0.332f, 0.333f, -0.334f, 0.335f, -0.336f, 0.337f, -0.338f, 0.339f, -0.34f, 0.341f, -0.342f, 0.343f, -0.34400000000000003f, 0.34500000000000003f, -0.34600000000000003f, 0.34700000000000003f, -0.34800000000000003f, 0.34900000000000003f, -0.35000000000000003f, 0.35100000000000003f, -0.352f, 0.353f, -0.354f, 0.355f, -0.356f, 0.357f, -0.358f, 0.359f, -0.36f, 0.361f, -0.362f, 0.363f, -0.364f, 0.365f, -0.366f, 0.367f, -0.368f, 0.369f, -0.37f, 0.371f, -0.372f, 0.373f, -0.374f, 0.375f, -0.376f, 0.377f, -0.378f, 0.379f, -0.38f, 0.381f, -0.382f, 0.383f, -0.384f, 0.385f, -0.386f, 0.387f, -0.388f, 0.389f, -0.39f, 0.391f, -0.392f, 0.393f, -0.394f, 0.395f, -0.396f, 0.397f, -0.398f, 0.399f, -0.4f, 0.401f, -0.402f, 0.403f, -0.404f, 0.405f, -0.406f, 0.40700000000000003f, -0.40800000000000003f, 0.40900000000000003f, -0.41000000000000003f, 0.41100000000000003f, -0.41200000000000003f, 0.41300000000000003f, -0.41400000000000003f, 0.41500000000000004f, -0.41600000000000004f, 0.417f, -0.418f, 0.419f, -0.42f, 0.421f, -0.422f, 0.423f, -0.424f, 0.425f, -0.426f, 0.427f, -0.428f, 0.429f, -0.43f, 0.431f, -0.432f, 0.433f, -0.434f, 0.435f, -0.436f, 0.437f, -0.438f, 0.439f, -0.44f, 0.441f, -0.442f, 0.443f, -0.444f, 0.445f, -0.446f, 0.447f, -0.448f, 0.449f, -0.45f, 0.451f, -0.452f, 0.453f, -0.454f, 0.455f, -0.456f, 0.457f, -0.458f, 0.459f, -0.46f, 0.461f, -0.462f, 0.463f, -0.464f, 0.465f, -0.466f, 0.467f, -0.468f, 0.46900000000000003f, -0.47000000000000003f, 0.47100000000000003f, -0.47200000000000003f, 0.47300000000000003f, -0.47400000000000003f, 0.47500000000000003f, 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+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/relu6_float_1_relaxed.example.cpp b/nn/runtime/test/generated/examples/relu6_float_1_relaxed.example.cpp
new file mode 100644
index 0000000..9b17630
--- /dev/null
+++ b/nn/runtime/test/generated/examples/relu6_float_1_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: relu6_float_1_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-10.0f, -0.5f, 0.5f, 10.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.0f, 0.0f, 0.5f, 6.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/relu6_float_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/relu6_float_2_relaxed.example.cpp
new file mode 100644
index 0000000..7455916
--- /dev/null
+++ b/nn/runtime/test/generated/examples/relu6_float_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: relu6_float_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.0f, 0.001f, -0.002f, 0.003f, -0.004f, 0.005f, -0.006f, 0.007f, -0.008f, 0.009000000000000001f, -0.01f, 0.011f, -0.012f, 0.013000000000000001f, -0.014f, 0.015f, -0.016f, 0.017f, -0.018000000000000002f, 0.019f, -0.02f, 0.021f, -0.022f, 0.023f, -0.024f, 0.025f, -0.026000000000000002f, 0.027f, -0.028f, 0.029f, -0.03f, 0.031f, -0.032f, 0.033f, -0.034f, 0.035f, -0.036000000000000004f, 0.037f, -0.038f, 0.039f, -0.04f, 0.041f, -0.042f, 0.043000000000000003f, -0.044f, 0.045f, -0.046f, 0.047f, -0.048f, 0.049f, -0.05f, 0.051000000000000004f, -0.052000000000000005f, 0.053f, -0.054f, 0.055f, -0.056f, 0.057f, -0.058f, 0.059000000000000004f, -0.06f, 0.061f, -0.062f, 0.063f, -0.064f, 0.065f, -0.066f, 0.067f, -0.068f, 0.069f, -0.07f, 0.07100000000000001f, -0.07200000000000001f, 0.073f, -0.074f, 0.075f, -0.076f, 0.077f, -0.078f, 0.079f, -0.08f, 0.081f, -0.082f, 0.083f, -0.084f, 0.085f, -0.08600000000000001f, 0.08700000000000001f, -0.088f, 0.089f, -0.09f, 0.091f, -0.092f, 0.093f, -0.094f, 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-3.5140000000000002f, 3.515f, -3.516f, 3.517f, -3.5180000000000002f, 3.519f, -3.52f, 3.521f, -3.5220000000000002f, 3.523f, -3.524f, 3.525f, -3.5260000000000002f, 3.527f, -3.528f, 3.529f, -3.5300000000000002f, 3.531f, -3.532f, 3.533f, -3.5340000000000003f, 3.535f, -3.536f, 3.537f, -3.5380000000000003f, 3.539f, -3.54f, 3.541f, -3.5420000000000003f, 3.543f, -3.544f, 3.545f, -3.5460000000000003f, 3.547f, -3.548f, 3.549f, -3.5500000000000003f, 3.551f, -3.552f, 3.553f, -3.5540000000000003f, 3.555f, -3.556f, 3.557f, -3.5580000000000003f, 3.559f, -3.56f, 3.561f, -3.5620000000000003f, 3.563f, -3.564f, 3.565f, -3.5660000000000003f, 3.567f, -3.568f, 3.569f, -3.5700000000000003f, 3.571f, -3.572f, 3.573f, -3.5740000000000003f, 3.575f, -3.576f, 3.577f, -3.5780000000000003f, 3.579f, -3.58f, 3.581f, -3.5820000000000003f, 3.583f, -3.584f, 3.585f, -3.586f, 3.587f, -3.588f, 3.589f, -3.59f, 3.591f, -3.592f, 3.593f, -3.594f, 3.595f, -3.596f, 3.597f, -3.598f, 3.599f, -3.6f, 3.601f, -3.602f, 3.603f, -3.604f, 3.605f, -3.606f, 3.607f, -3.608f, 3.609f, -3.61f, 3.611f, -3.612f, 3.613f, -3.614f, 3.615f, -3.616f, 3.617f, -3.618f, 3.619f, -3.62f, 3.621f, -3.622f, 3.623f, -3.624f, 3.625f, -3.626f, 3.6270000000000002f, -3.628f, 3.629f, -3.63f, 3.6310000000000002f, -3.632f, 3.633f, -3.634f, 3.6350000000000002f, -3.636f, 3.637f, -3.638f, 3.6390000000000002f, -3.64f, 3.641f, -3.642f, 3.6430000000000002f, -3.644f, 3.645f, -3.646f, 3.6470000000000002f, -3.648f, 3.649f, -3.65f, 3.6510000000000002f, -3.652f, 3.653f, -3.654f, 3.6550000000000002f, -3.656f, 3.657f, -3.658f, 3.6590000000000003f, -3.66f, 3.661f, -3.662f, 3.6630000000000003f, -3.664f, 3.665f, -3.666f, 3.6670000000000003f, -3.668f, 3.669f, -3.67f, 3.6710000000000003f, -3.672f, 3.673f, -3.674f, 3.6750000000000003f, -3.676f, 3.677f, -3.678f, 3.6790000000000003f, -3.68f, 3.681f, -3.682f, 3.6830000000000003f, -3.684f, 3.685f, -3.686f, 3.6870000000000003f, -3.688f, 3.689f, -3.69f, 3.6910000000000003f, -3.692f, 3.693f, -3.694f, 3.6950000000000003f, -3.696f, 3.697f, -3.698f, 3.6990000000000003f, -3.7f, 3.701f, -3.702f, 3.7030000000000003f, -3.704f, 3.705f, -3.706f, 3.7070000000000003f, -3.708f, 3.709f, -3.71f, 3.7110000000000003f, -3.712f, 3.713f, -3.714f, 3.715f, -3.716f, 3.717f, -3.718f, 3.719f, -3.72f, 3.721f, -3.722f, 3.723f, -3.724f, 3.725f, -3.726f, 3.727f, -3.728f, 3.729f, -3.73f, 3.731f, -3.732f, 3.733f, -3.734f, 3.735f, -3.736f, 3.737f, -3.738f, 3.739f, -3.74f, 3.741f, -3.742f, 3.743f, -3.744f, 3.745f, -3.746f, 3.747f, -3.748f, 3.749f, -3.75f, 3.751f, -3.7520000000000002f, 3.753f, -3.754f, 3.755f, -3.7560000000000002f, 3.757f, -3.758f, 3.759f, -3.7600000000000002f, 3.761f, -3.762f, 3.763f, -3.7640000000000002f, 3.765f, -3.766f, 3.767f, -3.7680000000000002f, 3.769f, -3.77f, 3.771f, -3.7720000000000002f, 3.773f, -3.774f, 3.775f, -3.7760000000000002f, 3.777f, -3.778f, 3.779f, -3.7800000000000002f, 3.781f, -3.782f, 3.783f, -3.7840000000000003f, 3.785f, -3.786f, 3.787f, -3.7880000000000003f, 3.789f, -3.79f, 3.791f, -3.7920000000000003f, 3.793f, -3.794f, 3.795f, -3.7960000000000003f, 3.797f, -3.798f, 3.799f, -3.8000000000000003f, 3.801f, -3.802f, 3.803f, -3.8040000000000003f, 3.805f, -3.806f, 3.807f, -3.8080000000000003f, 3.809f, -3.81f, 3.811f, -3.8120000000000003f, 3.813f, -3.814f, 3.815f, -3.8160000000000003f, 3.817f, -3.818f, 3.819f, -3.8200000000000003f, 3.821f, -3.822f, 3.823f, -3.8240000000000003f, 3.825f, -3.826f, 3.827f, -3.8280000000000003f, 3.829f, -3.83f, 3.831f, -3.8320000000000003f, 3.833f, -3.834f, 3.835f, -3.8360000000000003f, 3.837f, -3.838f, 3.839f, -3.84f, 3.841f, -3.842f, 3.843f, -3.844f, 3.845f, -3.846f, 3.847f, -3.848f, 3.849f, -3.85f, 3.851f, -3.852f, 3.853f, -3.854f, 3.855f, -3.856f, 3.857f, -3.858f, 3.859f, -3.86f, 3.861f, -3.862f, 3.863f, -3.864f, 3.865f, -3.866f, 3.867f, -3.868f, 3.869f, -3.87f, 3.871f, -3.872f, 3.873f, -3.874f, 3.875f, -3.876f, 3.8770000000000002f, -3.878f, 3.879f, -3.88f, 3.8810000000000002f, -3.882f, 3.883f, -3.884f, 3.8850000000000002f, -3.886f, 3.887f, -3.888f, 3.8890000000000002f, -3.89f, 3.891f, -3.892f, 3.8930000000000002f, -3.894f, 3.895f, -3.896f, 3.8970000000000002f, -3.898f, 3.899f, -3.9f, 3.9010000000000002f, -3.902f, 3.903f, -3.904f, 3.9050000000000002f, -3.906f, 3.907f, -3.908f, 3.9090000000000003f, -3.91f, 3.911f, -3.912f, 3.9130000000000003f, -3.914f, 3.915f, -3.916f, 3.9170000000000003f, -3.918f, 3.919f, -3.92f, 3.9210000000000003f, -3.922f, 3.923f, -3.924f, 3.9250000000000003f, -3.926f, 3.927f, -3.928f, 3.9290000000000003f, -3.93f, 3.931f, -3.932f, 3.9330000000000003f, -3.934f, 3.935f, -3.936f, 3.9370000000000003f, -3.938f, 3.939f, -3.94f, 3.9410000000000003f, -3.942f, 3.943f, -3.944f, 3.9450000000000003f, -3.946f, 3.947f, -3.948f, 3.9490000000000003f, -3.95f, 3.951f, -3.952f, 3.9530000000000003f, -3.954f, 3.955f, -3.956f, 3.9570000000000003f, -3.958f, 3.959f, -3.96f, 3.9610000000000003f, -3.962f, 3.963f, -3.964f, 3.9650000000000003f, -3.966f, 3.967f, -3.968f, 3.969f, -3.97f, 3.971f, -3.972f, 3.973f, -3.974f, 3.975f, -3.976f, 3.977f, -3.978f, 3.979f, -3.98f, 3.981f, -3.982f, 3.983f, -3.984f, 3.985f, -3.986f, 3.987f, -3.988f, 3.989f, -3.99f, 3.991f, -3.992f, 3.993f, -3.994f, 3.995f, -3.996f, 3.997f, -3.998f, 3.999f, -4.0f, 4.001f, -4.002f, 4.003f, -4.0040000000000004f, 4.005f, -4.006f, 4.007f, -4.008f, 4.009f, -4.01f, 4.011f, -4.0120000000000005f, 4.013f, -4.014f, 4.015f, -4.016f, 4.017f, -4.018f, 4.019f, -4.0200000000000005f, 4.021f, -4.022f, 4.023f, -4.024f, 4.025f, -4.026f, 4.027f, -4.0280000000000005f, 4.029f, -4.03f, 4.031f, -4.032f, 4.033f, -4.034f, 4.035f, -4.0360000000000005f, 4.037f, -4.038f, 4.039f, -4.04f, 4.041f, -4.042f, 4.043f, -4.0440000000000005f, 4.045f, -4.046f, 4.047f, -4.048f, 4.049f, -4.05f, 4.051f, -4.0520000000000005f, 4.053f, -4.054f, 4.055f, -4.056f, 4.057f, -4.058f, 4.059f, -4.0600000000000005f, 4.061f, -4.062f, 4.063f, -4.064f, 4.065f, -4.066f, 4.067f, -4.0680000000000005f, 4.069f, -4.07f, 4.071f, -4.072f, 4.073f, -4.074f, 4.075f, -4.0760000000000005f, 4.077f, -4.078f, 4.079f, -4.08f, 4.081f, -4.082f, 4.083f, -4.0840000000000005f, 4.085f, -4.086f, 4.087f, -4.088f, 4.089f, -4.09f, 4.091f, -4.0920000000000005f, 4.093f, -4.094f, 4.095f, -4.096f, 4.097f, -4.098f, 4.099f, -4.1f, 4.101f, -4.102f, 4.103f, -4.104f, 4.105f, -4.106f, 4.107f, -4.108f, 4.109f, -4.11f, 4.111f, -4.112f, 4.113f, -4.114f, 4.115f, -4.116f, 4.117f, -4.118f, 4.119f, -4.12f, 4.121f, -4.122f, 4.123f, -4.124f, 4.125f, -4.126f, 4.127f, -4.128f, 4.1290000000000004f, -4.13f, 4.131f, -4.132f, 4.133f, -4.134f, 4.135f, -4.136f, 4.1370000000000005f, -4.138f, 4.139f, -4.14f, 4.141f, -4.142f, 4.143f, -4.144f, 4.1450000000000005f, -4.146f, 4.147f, -4.148f, 4.149f, -4.15f, 4.151f, -4.152f, 4.1530000000000005f, -4.154f, 4.155f, -4.156f, 4.157f, -4.158f, 4.159f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.0f, 0.001f, 0, 0.003f, 0, 0.005f, 0, 0.007f, 0, 0.009000000000000001f, 0, 0.011f, 0, 0.013000000000000001f, 0, 0.015f, 0, 0.017f, 0, 0.019f, 0, 0.021f, 0, 0.023f, 0, 0.025f, 0, 0.027f, 0, 0.029f, 0, 0.031f, 0, 0.033f, 0, 0.035f, 0, 0.037f, 0, 0.039f, 0, 0.041f, 0, 0.043000000000000003f, 0, 0.045f, 0, 0.047f, 0, 0.049f, 0, 0.051000000000000004f, 0, 0.053f, 0, 0.055f, 0, 0.057f, 0, 0.059000000000000004f, 0, 0.061f, 0, 0.063f, 0, 0.065f, 0, 0.067f, 0, 0.069f, 0, 0.07100000000000001f, 0, 0.073f, 0, 0.075f, 0, 0.077f, 0, 0.079f, 0, 0.081f, 0, 0.083f, 0, 0.085f, 0, 0.08700000000000001f, 0, 0.089f, 0, 0.091f, 0, 0.093f, 0, 0.095f, 0, 0.097f, 0, 0.099f, 0, 0.101f, 0, 0.10300000000000001f, 0, 0.105f, 0, 0.107f, 0, 0.109f, 0, 0.111f, 0, 0.113f, 0, 0.115f, 0, 0.117f, 0, 0.11900000000000001f, 0, 0.121f, 0, 0.123f, 0, 0.125f, 0, 0.127f, 0, 0.129f, 0, 0.131f, 0, 0.133f, 0, 0.135f, 0, 0.137f, 0, 0.139f, 0, 0.14100000000000001f, 0, 0.14300000000000002f, 0, 0.145f, 0, 0.147f, 0, 0.149f, 0, 0.151f, 0, 0.153f, 0, 0.155f, 0, 0.157f, 0, 0.159f, 0, 0.161f, 0, 0.163f, 0, 0.165f, 0, 0.167f, 0, 0.169f, 0, 0.171f, 0, 0.17300000000000001f, 0, 0.17500000000000002f, 0, 0.177f, 0, 0.179f, 0, 0.181f, 0, 0.183f, 0, 0.185f, 0, 0.187f, 0, 0.189f, 0, 0.191f, 0, 0.193f, 0, 0.195f, 0, 0.197f, 0, 0.199f, 0, 0.201f, 0, 0.203f, 0, 0.20500000000000002f, 0, 0.20700000000000002f, 0, 0.209f, 0, 0.211f, 0, 0.213f, 0, 0.215f, 0, 0.217f, 0, 0.219f, 0, 0.221f, 0, 0.223f, 0, 0.225f, 0, 0.227f, 0, 0.229f, 0, 0.231f, 0, 0.233f, 0, 0.23500000000000001f, 0, 0.23700000000000002f, 0, 0.23900000000000002f, 0, 0.241f, 0, 0.243f, 0, 0.245f, 0, 0.247f, 0, 0.249f, 0, 0.251f, 0, 0.253f, 0, 0.255f, 0, 0.257f, 0, 0.259f, 0, 0.261f, 0, 0.263f, 0, 0.265f, 0, 0.267f, 0, 0.269f, 0, 0.271f, 0, 0.273f, 0, 0.275f, 0, 0.277f, 0, 0.279f, 0, 0.281f, 0, 0.28300000000000003f, 0, 0.28500000000000003f, 0, 0.28700000000000003f, 0, 0.289f, 0, 0.291f, 0, 0.293f, 0, 0.295f, 0, 0.297f, 0, 0.299f, 0, 0.301f, 0, 0.303f, 0, 0.305f, 0, 0.307f, 0, 0.309f, 0, 0.311f, 0, 0.313f, 0, 0.315f, 0, 0.317f, 0, 0.319f, 0, 0.321f, 0, 0.323f, 0, 0.325f, 0, 0.327f, 0, 0.329f, 0, 0.331f, 0, 0.333f, 0, 0.335f, 0, 0.337f, 0, 0.339f, 0, 0.341f, 0, 0.343f, 0, 0.34500000000000003f, 0, 0.34700000000000003f, 0, 0.34900000000000003f, 0, 0.35100000000000003f, 0, 0.353f, 0, 0.355f, 0, 0.357f, 0, 0.359f, 0, 0.361f, 0, 0.363f, 0, 0.365f, 0, 0.367f, 0, 0.369f, 0, 0.371f, 0, 0.373f, 0, 0.375f, 0, 0.377f, 0, 0.379f, 0, 0.381f, 0, 0.383f, 0, 0.385f, 0, 0.387f, 0, 0.389f, 0, 0.391f, 0, 0.393f, 0, 0.395f, 0, 0.397f, 0, 0.399f, 0, 0.401f, 0, 0.403f, 0, 0.405f, 0, 0.40700000000000003f, 0, 0.40900000000000003f, 0, 0.41100000000000003f, 0, 0.41300000000000003f, 0, 0.41500000000000004f, 0, 0.417f, 0, 0.419f, 0, 0.421f, 0, 0.423f, 0, 0.425f, 0, 0.427f, 0, 0.429f, 0, 0.431f, 0, 0.433f, 0, 0.435f, 0, 0.437f, 0, 0.439f, 0, 0.441f, 0, 0.443f, 0, 0.445f, 0, 0.447f, 0, 0.449f, 0, 0.451f, 0, 0.453f, 0, 0.455f, 0, 0.457f, 0, 0.459f, 0, 0.461f, 0, 0.463f, 0, 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2.6630000000000003f, 0, 2.665f, 0, 2.6670000000000003f, 0, 2.669f, 0, 2.6710000000000003f, 0, 2.673f, 0, 2.6750000000000003f, 0, 2.677f, 0, 2.6790000000000003f, 0, 2.681f, 0, 2.6830000000000003f, 0, 2.685f, 0, 2.6870000000000003f, 0, 2.689f, 0, 2.691f, 0, 2.693f, 0, 2.695f, 0, 2.697f, 0, 2.699f, 0, 2.701f, 0, 2.703f, 0, 2.705f, 0, 2.707f, 0, 2.709f, 0, 2.711f, 0, 2.713f, 0, 2.715f, 0, 2.717f, 0, 2.719f, 0, 2.721f, 0, 2.723f, 0, 2.725f, 0, 2.727f, 0, 2.729f, 0, 2.731f, 0, 2.733f, 0, 2.735f, 0, 2.737f, 0, 2.739f, 0, 2.741f, 0, 2.743f, 0, 2.745f, 0, 2.747f, 0, 2.749f, 0, 2.751f, 0, 2.753f, 0, 2.755f, 0, 2.757f, 0, 2.759f, 0, 2.761f, 0, 2.763f, 0, 2.765f, 0, 2.767f, 0, 2.769f, 0, 2.771f, 0, 2.773f, 0, 2.775f, 0, 2.777f, 0, 2.779f, 0, 2.781f, 0, 2.783f, 0, 2.785f, 0, 2.787f, 0, 2.789f, 0, 2.791f, 0, 2.793f, 0, 2.795f, 0, 2.797f, 0, 2.799f, 0, 2.801f, 0, 2.803f, 0, 2.805f, 0, 2.807f, 0, 2.809f, 0, 2.811f, 0, 2.813f, 0, 2.815f, 0, 2.817f, 0, 2.819f, 0, 2.821f, 0, 2.823f, 0, 2.825f, 0, 2.827f, 0, 2.829f, 0, 2.831f, 0, 2.833f, 0, 2.835f, 0, 2.837f, 0, 2.839f, 0, 2.841f, 0, 2.843f, 0, 2.845f, 0, 2.847f, 0, 2.849f, 0, 2.851f, 0, 2.853f, 0, 2.855f, 0, 2.857f, 0, 2.859f, 0, 2.861f, 0, 2.863f, 0, 2.865f, 0, 2.867f, 0, 2.869f, 0, 2.871f, 0, 2.873f, 0, 2.875f, 0, 2.8770000000000002f, 0, 2.879f, 0, 2.8810000000000002f, 0, 2.883f, 0, 2.8850000000000002f, 0, 2.887f, 0, 2.8890000000000002f, 0, 2.891f, 0, 2.8930000000000002f, 0, 2.895f, 0, 2.8970000000000002f, 0, 2.899f, 0, 2.9010000000000002f, 0, 2.903f, 0, 2.9050000000000002f, 0, 2.907f, 0, 2.9090000000000003f, 0, 2.911f, 0, 2.9130000000000003f, 0, 2.915f, 0, 2.9170000000000003f, 0, 2.919f, 0, 2.9210000000000003f, 0, 2.923f, 0, 2.9250000000000003f, 0, 2.927f, 0, 2.9290000000000003f, 0, 2.931f, 0, 2.9330000000000003f, 0, 2.935f, 0, 2.9370000000000003f, 0, 2.939f, 0, 2.9410000000000003f, 0, 2.943f, 0, 2.945f, 0, 2.947f, 0, 2.949f, 0, 2.951f, 0, 2.953f, 0, 2.955f, 0, 2.957f, 0, 2.959f, 0, 2.961f, 0, 2.963f, 0, 2.965f, 0, 2.967f, 0, 2.969f, 0, 2.971f, 0, 2.973f, 0, 2.975f, 0, 2.977f, 0, 2.979f, 0, 2.981f, 0, 2.983f, 0, 2.985f, 0, 2.987f, 0, 2.989f, 0, 2.991f, 0, 2.993f, 0, 2.995f, 0, 2.997f, 0, 2.999f, 0, 3.001f, 0, 3.003f, 0, 3.005f, 0, 3.007f, 0, 3.009f, 0, 3.011f, 0, 3.013f, 0, 3.015f, 0, 3.017f, 0, 3.019f, 0, 3.021f, 0, 3.023f, 0, 3.025f, 0, 3.027f, 0, 3.029f, 0, 3.031f, 0, 3.033f, 0, 3.035f, 0, 3.037f, 0, 3.039f, 0, 3.041f, 0, 3.043f, 0, 3.045f, 0, 3.047f, 0, 3.049f, 0, 3.051f, 0, 3.053f, 0, 3.055f, 0, 3.057f, 0, 3.059f, 0, 3.061f, 0, 3.063f, 0, 3.065f, 0, 3.067f, 0, 3.069f, 0, 3.071f, 0, 3.073f, 0, 3.075f, 0, 3.077f, 0, 3.079f, 0, 3.081f, 0, 3.083f, 0, 3.085f, 0, 3.087f, 0, 3.089f, 0, 3.091f, 0, 3.093f, 0, 3.095f, 0, 3.097f, 0, 3.099f, 0, 3.101f, 0, 3.103f, 0, 3.105f, 0, 3.107f, 0, 3.109f, 0, 3.111f, 0, 3.113f, 0, 3.115f, 0, 3.117f, 0, 3.119f, 0, 3.121f, 0, 3.123f, 0, 3.125f, 0, 3.1270000000000002f, 0, 3.129f, 0, 3.1310000000000002f, 0, 3.133f, 0, 3.1350000000000002f, 0, 3.137f, 0, 3.1390000000000002f, 0, 3.141f, 0, 3.1430000000000002f, 0, 3.145f, 0, 3.1470000000000002f, 0, 3.149f, 0, 3.1510000000000002f, 0, 3.153f, 0, 3.1550000000000002f, 0, 3.157f, 0, 3.1590000000000003f, 0, 3.161f, 0, 3.1630000000000003f, 0, 3.165f, 0, 3.1670000000000003f, 0, 3.169f, 0, 3.1710000000000003f, 0, 3.173f, 0, 3.1750000000000003f, 0, 3.177f, 0, 3.1790000000000003f, 0, 3.181f, 0, 3.1830000000000003f, 0, 3.185f, 0, 3.1870000000000003f, 0, 3.189f, 0, 3.1910000000000003f, 0, 3.193f, 0, 3.1950000000000003f, 0, 3.197f, 0, 3.1990000000000003f, 0, 3.201f, 0, 3.203f, 0, 3.205f, 0, 3.207f, 0, 3.209f, 0, 3.211f, 0, 3.213f, 0, 3.215f, 0, 3.217f, 0, 3.219f, 0, 3.221f, 0, 3.223f, 0, 3.225f, 0, 3.227f, 0, 3.229f, 0, 3.231f, 0, 3.233f, 0, 3.235f, 0, 3.237f, 0, 3.239f, 0, 3.241f, 0, 3.243f, 0, 3.245f, 0, 3.247f, 0, 3.249f, 0, 3.251f, 0, 3.253f, 0, 3.255f, 0, 3.257f, 0, 3.259f, 0, 3.261f, 0, 3.263f, 0, 3.265f, 0, 3.267f, 0, 3.269f, 0, 3.271f, 0, 3.273f, 0, 3.275f, 0, 3.277f, 0, 3.279f, 0, 3.281f, 0, 3.283f, 0, 3.285f, 0, 3.287f, 0, 3.289f, 0, 3.291f, 0, 3.293f, 0, 3.295f, 0, 3.297f, 0, 3.299f, 0, 3.301f, 0, 3.303f, 0, 3.305f, 0, 3.307f, 0, 3.309f, 0, 3.311f, 0, 3.313f, 0, 3.315f, 0, 3.317f, 0, 3.319f, 0, 3.321f, 0, 3.323f, 0, 3.325f, 0, 3.327f, 0, 3.329f, 0, 3.331f, 0, 3.333f, 0, 3.335f, 0, 3.337f, 0, 3.339f, 0, 3.341f, 0, 3.343f, 0, 3.345f, 0, 3.347f, 0, 3.349f, 0, 3.351f, 0, 3.353f, 0, 3.355f, 0, 3.357f, 0, 3.359f, 0, 3.361f, 0, 3.363f, 0, 3.365f, 0, 3.367f, 0, 3.369f, 0, 3.371f, 0, 3.373f, 0, 3.375f, 0, 3.3770000000000002f, 0, 3.379f, 0, 3.3810000000000002f, 0, 3.383f, 0, 3.3850000000000002f, 0, 3.387f, 0, 3.3890000000000002f, 0, 3.391f, 0, 3.3930000000000002f, 0, 3.395f, 0, 3.3970000000000002f, 0, 3.399f, 0, 3.4010000000000002f, 0, 3.403f, 0, 3.4050000000000002f, 0, 3.407f, 0, 3.4090000000000003f, 0, 3.411f, 0, 3.4130000000000003f, 0, 3.415f, 0, 3.4170000000000003f, 0, 3.419f, 0, 3.4210000000000003f, 0, 3.423f, 0, 3.4250000000000003f, 0, 3.427f, 0, 3.4290000000000003f, 0, 3.431f, 0, 3.4330000000000003f, 0, 3.435f, 0, 3.4370000000000003f, 0, 3.439f, 0, 3.4410000000000003f, 0, 3.443f, 0, 3.4450000000000003f, 0, 3.447f, 0, 3.4490000000000003f, 0, 3.451f, 0, 3.4530000000000003f, 0, 3.455f, 0, 3.457f, 0, 3.459f, 0, 3.461f, 0, 3.463f, 0, 3.465f, 0, 3.467f, 0, 3.469f, 0, 3.471f, 0, 3.473f, 0, 3.475f, 0, 3.477f, 0, 3.479f, 0, 3.481f, 0, 3.483f, 0, 3.485f, 0, 3.487f, 0, 3.489f, 0, 3.491f, 0, 3.493f, 0, 3.495f, 0, 3.497f, 0, 3.499f, 0, 3.501f, 0, 3.503f, 0, 3.505f, 0, 3.507f, 0, 3.509f, 0, 3.511f, 0, 3.513f, 0, 3.515f, 0, 3.517f, 0, 3.519f, 0, 3.521f, 0, 3.523f, 0, 3.525f, 0, 3.527f, 0, 3.529f, 0, 3.531f, 0, 3.533f, 0, 3.535f, 0, 3.537f, 0, 3.539f, 0, 3.541f, 0, 3.543f, 0, 3.545f, 0, 3.547f, 0, 3.549f, 0, 3.551f, 0, 3.553f, 0, 3.555f, 0, 3.557f, 0, 3.559f, 0, 3.561f, 0, 3.563f, 0, 3.565f, 0, 3.567f, 0, 3.569f, 0, 3.571f, 0, 3.573f, 0, 3.575f, 0, 3.577f, 0, 3.579f, 0, 3.581f, 0, 3.583f, 0, 3.585f, 0, 3.587f, 0, 3.589f, 0, 3.591f, 0, 3.593f, 0, 3.595f, 0, 3.597f, 0, 3.599f, 0, 3.601f, 0, 3.603f, 0, 3.605f, 0, 3.607f, 0, 3.609f, 0, 3.611f, 0, 3.613f, 0, 3.615f, 0, 3.617f, 0, 3.619f, 0, 3.621f, 0, 3.623f, 0, 3.625f, 0, 3.6270000000000002f, 0, 3.629f, 0, 3.6310000000000002f, 0, 3.633f, 0, 3.6350000000000002f, 0, 3.637f, 0, 3.6390000000000002f, 0, 3.641f, 0, 3.6430000000000002f, 0, 3.645f, 0, 3.6470000000000002f, 0, 3.649f, 0, 3.6510000000000002f, 0, 3.653f, 0, 3.6550000000000002f, 0, 3.657f, 0, 3.6590000000000003f, 0, 3.661f, 0, 3.6630000000000003f, 0, 3.665f, 0, 3.6670000000000003f, 0, 3.669f, 0, 3.6710000000000003f, 0, 3.673f, 0, 3.6750000000000003f, 0, 3.677f, 0, 3.6790000000000003f, 0, 3.681f, 0, 3.6830000000000003f, 0, 3.685f, 0, 3.6870000000000003f, 0, 3.689f, 0, 3.6910000000000003f, 0, 3.693f, 0, 3.6950000000000003f, 0, 3.697f, 0, 3.6990000000000003f, 0, 3.701f, 0, 3.7030000000000003f, 0, 3.705f, 0, 3.7070000000000003f, 0, 3.709f, 0, 3.7110000000000003f, 0, 3.713f, 0, 3.715f, 0, 3.717f, 0, 3.719f, 0, 3.721f, 0, 3.723f, 0, 3.725f, 0, 3.727f, 0, 3.729f, 0, 3.731f, 0, 3.733f, 0, 3.735f, 0, 3.737f, 0, 3.739f, 0, 3.741f, 0, 3.743f, 0, 3.745f, 0, 3.747f, 0, 3.749f, 0, 3.751f, 0, 3.753f, 0, 3.755f, 0, 3.757f, 0, 3.759f, 0, 3.761f, 0, 3.763f, 0, 3.765f, 0, 3.767f, 0, 3.769f, 0, 3.771f, 0, 3.773f, 0, 3.775f, 0, 3.777f, 0, 3.779f, 0, 3.781f, 0, 3.783f, 0, 3.785f, 0, 3.787f, 0, 3.789f, 0, 3.791f, 0, 3.793f, 0, 3.795f, 0, 3.797f, 0, 3.799f, 0, 3.801f, 0, 3.803f, 0, 3.805f, 0, 3.807f, 0, 3.809f, 0, 3.811f, 0, 3.813f, 0, 3.815f, 0, 3.817f, 0, 3.819f, 0, 3.821f, 0, 3.823f, 0, 3.825f, 0, 3.827f, 0, 3.829f, 0, 3.831f, 0, 3.833f, 0, 3.835f, 0, 3.837f, 0, 3.839f, 0, 3.841f, 0, 3.843f, 0, 3.845f, 0, 3.847f, 0, 3.849f, 0, 3.851f, 0, 3.853f, 0, 3.855f, 0, 3.857f, 0, 3.859f, 0, 3.861f, 0, 3.863f, 0, 3.865f, 0, 3.867f, 0, 3.869f, 0, 3.871f, 0, 3.873f, 0, 3.875f, 0, 3.8770000000000002f, 0, 3.879f, 0, 3.8810000000000002f, 0, 3.883f, 0, 3.8850000000000002f, 0, 3.887f, 0, 3.8890000000000002f, 0, 3.891f, 0, 3.8930000000000002f, 0, 3.895f, 0, 3.8970000000000002f, 0, 3.899f, 0, 3.9010000000000002f, 0, 3.903f, 0, 3.9050000000000002f, 0, 3.907f, 0, 3.9090000000000003f, 0, 3.911f, 0, 3.9130000000000003f, 0, 3.915f, 0, 3.9170000000000003f, 0, 3.919f, 0, 3.9210000000000003f, 0, 3.923f, 0, 3.9250000000000003f, 0, 3.927f, 0, 3.9290000000000003f, 0, 3.931f, 0, 3.9330000000000003f, 0, 3.935f, 0, 3.9370000000000003f, 0, 3.939f, 0, 3.9410000000000003f, 0, 3.943f, 0, 3.9450000000000003f, 0, 3.947f, 0, 3.9490000000000003f, 0, 3.951f, 0, 3.9530000000000003f, 0, 3.955f, 0, 3.9570000000000003f, 0, 3.959f, 0, 3.9610000000000003f, 0, 3.963f, 0, 3.9650000000000003f, 0, 3.967f, 0, 3.969f, 0, 3.971f, 0, 3.973f, 0, 3.975f, 0, 3.977f, 0, 3.979f, 0, 3.981f, 0, 3.983f, 0, 3.985f, 0, 3.987f, 0, 3.989f, 0, 3.991f, 0, 3.993f, 0, 3.995f, 0, 3.997f, 0, 3.999f, 0, 4.001f, 0, 4.003f, 0, 4.005f, 0, 4.007f, 0, 4.009f, 0, 4.011f, 0, 4.013f, 0, 4.015f, 0, 4.017f, 0, 4.019f, 0, 4.021f, 0, 4.023f, 0, 4.025f, 0, 4.027f, 0, 4.029f, 0, 4.031f, 0, 4.033f, 0, 4.035f, 0, 4.037f, 0, 4.039f, 0, 4.041f, 0, 4.043f, 0, 4.045f, 0, 4.047f, 0, 4.049f, 0, 4.051f, 0, 4.053f, 0, 4.055f, 0, 4.057f, 0, 4.059f, 0, 4.061f, 0, 4.063f, 0, 4.065f, 0, 4.067f, 0, 4.069f, 0, 4.071f, 0, 4.073f, 0, 4.075f, 0, 4.077f, 0, 4.079f, 0, 4.081f, 0, 4.083f, 0, 4.085f, 0, 4.087f, 0, 4.089f, 0, 4.091f, 0, 4.093f, 0, 4.095f, 0, 4.097f, 0, 4.099f, 0, 4.101f, 0, 4.103f, 0, 4.105f, 0, 4.107f, 0, 4.109f, 0, 4.111f, 0, 4.113f, 0, 4.115f, 0, 4.117f, 0, 4.119f, 0, 4.121f, 0, 4.123f, 0, 4.125f, 0, 4.127f, 0, 4.1290000000000004f, 0, 4.131f, 0, 4.133f, 0, 4.135f, 0, 4.1370000000000005f, 0, 4.139f, 0, 4.141f, 0, 4.143f, 0, 4.1450000000000005f, 0, 4.147f, 0, 4.149f, 0, 4.151f, 0, 4.1530000000000005f, 0, 4.155f, 0, 4.157f, 0, 4.159f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/relu_float_1_relaxed.example.cpp b/nn/runtime/test/generated/examples/relu_float_1_relaxed.example.cpp
new file mode 100644
index 0000000..ea2ce20
--- /dev/null
+++ b/nn/runtime/test/generated/examples/relu_float_1_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: relu_float_1_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-10.0f, -0.5f, 0.5f, 10.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.0f, 0.0f, 0.5f, 10.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/reshape_relaxed.example.cpp b/nn/runtime/test/generated/examples/reshape_relaxed.example.cpp
new file mode 100644
index 0000000..c3371a9
--- /dev/null
+++ b/nn/runtime/test/generated/examples/reshape_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: reshape_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/reshape_weights_as_inputs_relaxed.example.cpp b/nn/runtime/test/generated/examples/reshape_weights_as_inputs_relaxed.example.cpp
new file mode 100644
index 0000000..e51bd4f
--- /dev/null
+++ b/nn/runtime/test/generated/examples/reshape_weights_as_inputs_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: reshape_weights_as_inputs_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9}}},
+  // int -> INT32 map
+  {{1, {-1}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/resize_bilinear_relaxed.example.cpp b/nn/runtime/test/generated/examples/resize_bilinear_relaxed.example.cpp
new file mode 100644
index 0000000..19d9120
--- /dev/null
+++ b/nn/runtime/test/generated/examples/resize_bilinear_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: resize_bilinear_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 1.0f, 2.0f, 2.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 1.0f, 1.0f, 1.666666667f, 1.666666667f, 1.666666667f, 2.0f, 2.0f, 2.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/rnn_relaxed.example.cpp b/nn/runtime/test/generated/examples/rnn_relaxed.example.cpp
new file mode 100644
index 0000000..553bc0e
--- /dev/null
+++ b/nn/runtime/test/generated/examples/rnn_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: rnn_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.23689353f, 0.285385f, 0.037029743f, -0.19858193f, -0.27569133f, 0.43773448f, 0.60379338f, 0.35562468f, 0.23689353f, 0.285385f, 0.037029743f, -0.19858193f, -0.27569133f, 0.43773448f, 0.60379338f, 0.35562468f}}, {1, {0.461459f, 0.153381f, 0.529743f, -0.00371218f, 0.676267f, -0.211346f, 0.317493f, 0.969689f, -0.343251f, 0.186423f, 0.398151f, 0.152399f, 0.448504f, 0.317662f, 0.523556f, -0.323514f, 0.480877f, 0.333113f, -0.757714f, -0.674487f, -0.643585f, 0.217766f, -0.0251462f, 0.79512f, -0.595574f, -0.422444f, 0.371572f, -0.452178f, -0.556069f, -0.482188f, -0.685456f, -0.727851f, 0.841829f, 0.551535f, -0.232336f, 0.729158f, -0.00294906f, -0.69754f, 0.766073f, -0.178424f, 0.369513f, -0.423241f, 0.548547f, -0.0152023f, -0.757482f, -0.85491f, 0.251331f, -0.989183f, 0.306261f, -0.340716f, 0.886103f, -0.0726757f, -0.723523f, -0.784303f, 0.0354295f, 0.566564f, -0.485469f, -0.620498f, 0.832546f, 0.697884f, -0.279115f, 0.294415f, -0.584313f, 0.548772f, 0.0648819f, 0.968726f, 0.723834f, -0.0080452f, -0.350386f, -0.272803f, 0.115121f, -0.412644f, -0.824713f, -0.992843f, -0.592904f, -0.417893f, 0.863791f, -0.423461f, -0.147601f, -0.770664f, -0.479006f, 0.654782f, 0.587314f, -0.639158f, 0.816969f, -0.337228f, 0.659878f, 0.73107f, 0.754768f, -0.337042f, 0.0960841f, 0.368357f, 0.244191f, -0.817703f, -0.211223f, 0.442012f, 0.37225f, -0.623598f, -0.405423f, 0.455101f, 0.673656f, -0.145345f, -0.511346f, -0.901675f, -0.81252f, -0.127006f, 0.809865f, -0.721884f, 0.636255f, 0.868989f, -0.347973f, -0.10179f, -0.777449f, 0.917274f, 0.819286f, 0.206218f, -0.00785118f, 0.167141f, 0.45872f, 0.972934f, -0.276798f, 0.837861f, 0.747958f, -0.0151566f, -0.330057f, -0.469077f, 0.277308f, 0.415818f}}, {2, {0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f}}, {3, {0.065691948f, -0.69055247f, 0.1107955f, -0.97084129f, -0.23957068f, -0.23566568f, -0.389184f, 0.47481549f, -0.4791103f, 0.29931796f, 0.10463274f, 0.83918178f, 0.37197268f, 0.61957061f, 0.3956964f, -0.37609905f}}, {4, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}},
+  // int -> INT32 map
+  {{5, {1}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}, {1, {0.496726f, 0, 0.965996f, 0, 0.0584254f, 0, 0, 0.12315f, 0, 0, 0.612266f, 0.456601f, 0, 0.52286f, 1.16099f, 0.0291232f, 0.496726f, 0, 0.965996f, 0, 0.0584254f, 0, 0, 0.12315f, 0, 0, 0.612266f, 0.456601f, 0, 0.52286f, 1.16099f, 0.0291232f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/rnn_state_relaxed.example.cpp b/nn/runtime/test/generated/examples/rnn_state_relaxed.example.cpp
new file mode 100644
index 0000000..9c73172
--- /dev/null
+++ b/nn/runtime/test/generated/examples/rnn_state_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: rnn_state_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.69424844f, -0.93421471f, -0.87287879f, 0.37144363f, -0.62476718f, 0.23791671f, 0.40060222f, 0.1356622f, -0.69424844f, -0.93421471f, -0.87287879f, 0.37144363f, -0.62476718f, 0.23791671f, 0.40060222f, 0.1356622f}}, {1, {0.461459f, 0.153381f, 0.529743f, -0.00371218f, 0.676267f, -0.211346f, 0.317493f, 0.969689f, -0.343251f, 0.186423f, 0.398151f, 0.152399f, 0.448504f, 0.317662f, 0.523556f, -0.323514f, 0.480877f, 0.333113f, -0.757714f, -0.674487f, -0.643585f, 0.217766f, -0.0251462f, 0.79512f, -0.595574f, -0.422444f, 0.371572f, -0.452178f, -0.556069f, -0.482188f, -0.685456f, -0.727851f, 0.841829f, 0.551535f, -0.232336f, 0.729158f, -0.00294906f, -0.69754f, 0.766073f, -0.178424f, 0.369513f, -0.423241f, 0.548547f, -0.0152023f, -0.757482f, -0.85491f, 0.251331f, -0.989183f, 0.306261f, -0.340716f, 0.886103f, -0.0726757f, -0.723523f, -0.784303f, 0.0354295f, 0.566564f, -0.485469f, -0.620498f, 0.832546f, 0.697884f, -0.279115f, 0.294415f, -0.584313f, 0.548772f, 0.0648819f, 0.968726f, 0.723834f, -0.0080452f, -0.350386f, -0.272803f, 0.115121f, -0.412644f, -0.824713f, -0.992843f, -0.592904f, -0.417893f, 0.863791f, -0.423461f, -0.147601f, -0.770664f, -0.479006f, 0.654782f, 0.587314f, -0.639158f, 0.816969f, -0.337228f, 0.659878f, 0.73107f, 0.754768f, -0.337042f, 0.0960841f, 0.368357f, 0.244191f, -0.817703f, -0.211223f, 0.442012f, 0.37225f, -0.623598f, -0.405423f, 0.455101f, 0.673656f, -0.145345f, -0.511346f, -0.901675f, -0.81252f, -0.127006f, 0.809865f, -0.721884f, 0.636255f, 0.868989f, -0.347973f, -0.10179f, -0.777449f, 0.917274f, 0.819286f, 0.206218f, -0.00785118f, 0.167141f, 0.45872f, 0.972934f, -0.276798f, 0.837861f, 0.747958f, -0.0151566f, -0.330057f, -0.469077f, 0.277308f, 0.415818f}}, {2, {0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1f}}, {3, {0.065691948f, -0.69055247f, 0.1107955f, -0.97084129f, -0.23957068f, -0.23566568f, -0.389184f, 0.47481549f, -0.4791103f, 0.29931796f, 0.10463274f, 0.83918178f, 0.37197268f, 0.61957061f, 0.3956964f, -0.37609905f}}, {4, {0.496726f, 0, 0.965996f, 0, 0.0584256f, 0, 0, 0.12315f, 0, 0, 0.612267f, 0.456601f, 0, 0.52286f, 1.16099f, 0.0291233f, 0.496726f, 0, 0.965996f, 0, 0.0584256f, 0, 0, 0.12315f, 0, 0, 0.612267f, 0.456601f, 0, 0.52286f, 1.16099f, 0.0291233f}}},
+  // int -> INT32 map
+  {{5, {1}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 0, 0.524902f, 0, 0, 0, 0, 1.02116f, 0, 1.35762f, 0, 0.356909f, 0.436415f, 0.0355731f, 0, 0, 0, 0, 0.524902f, 0, 0, 0, 0, 1.02116f, 0, 1.35762f, 0, 0.356909f, 0.436415f, 0.0355731f, 0, 0}}, {1, {0, 0, 0.524901f, 0, 0, 0, 0, 1.02116f, 0, 1.35762f, 0, 0.356909f, 0.436415f, 0.0355727f, 0, 0, 0, 0, 0.524901f, 0, 0, 0, 0, 1.02116f, 0, 1.35762f, 0, 0.356909f, 0.436415f, 0.0355727f, 0, 0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/softmax_float_1_relaxed.example.cpp b/nn/runtime/test/generated/examples/softmax_float_1_relaxed.example.cpp
new file mode 100644
index 0000000..0c2bacb
--- /dev/null
+++ b/nn/runtime/test/generated/examples/softmax_float_1_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: softmax_float_1_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 10.0f, 20.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.25f, 0.25f, 0.25f, 0.25f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/softmax_float_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/softmax_float_2_relaxed.example.cpp
new file mode 100644
index 0000000..7c8384c
--- /dev/null
+++ b/nn/runtime/test/generated/examples/softmax_float_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: softmax_float_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, -1.0f, -2.0f, -3.0f, -4.0f, -5.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.011656231f, 0.031684921f, 0.086128544f, 0.234121657f, 0.636408647f, 0.636408647f, 0.234121657f, 0.086128544f, 0.031684921f, 0.011656231f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/space_to_depth_float_1_relaxed.example.cpp b/nn/runtime/test/generated/examples/space_to_depth_float_1_relaxed.example.cpp
new file mode 100644
index 0000000..66e07ae
--- /dev/null
+++ b/nn/runtime/test/generated/examples/space_to_depth_float_1_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: space_to_depth_float_1_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/space_to_depth_float_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/space_to_depth_float_2_relaxed.example.cpp
new file mode 100644
index 0000000..5c432fe
--- /dev/null
+++ b/nn/runtime/test/generated/examples/space_to_depth_float_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: space_to_depth_float_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 5.0f, 6.0f, 3.0f, 4.0f, 7.0f, 8.0f, 9.0f, 10.0f, 13.0f, 14.0f, 11.0f, 12.0f, 15.0f, 16.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/space_to_depth_float_3_relaxed.example.cpp b/nn/runtime/test/generated/examples/space_to_depth_float_3_relaxed.example.cpp
new file mode 100644
index 0000000..ccc8a28
--- /dev/null
+++ b/nn/runtime/test/generated/examples/space_to_depth_float_3_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: space_to_depth_float_3_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {10, 20, 11, 21, 12, 22, 13, 23, 14, 24, 15, 25, 16, 26, 17, 27, 18, 28, 19, 29, 110, 210, 111, 211, 112, 212, 113, 213, 114, 214, 115, 215}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {10, 20, 11, 21, 14, 24, 15, 25, 12, 22, 13, 23, 16, 26, 17, 27, 18, 28, 19, 29, 112, 212, 113, 213, 110, 210, 111, 211, 114, 214, 115, 215}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/svdf2_relaxed.example.cpp b/nn/runtime/test/generated/examples/svdf2_relaxed.example.cpp
new file mode 100644
index 0000000..76d8bb4
--- /dev/null
+++ b/nn/runtime/test/generated/examples/svdf2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: svdf2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.12609188f, -0.46347019f, -0.89598465f, 0.35867718f, 0.36897406f, 0.73463392f}}, {1, {-0.31930989f, 0.0079667f, 0.39296314f, 0.37613347f, 0.12416199f, 0.15785322f, 0.27901134f, 0.3905206f, 0.21931258f, -0.36137494f, -0.10640851f, 0.31053296f, -0.36118156f, -0.0976817f, -0.36916667f, 0.22197971f, 0.15294972f, 0.38031587f, 0.27557442f, 0.39635518f, -0.21580373f, -0.06634006f, -0.02702999f, 0.27072677f}}, {2, {-0.31930989f, 0.37613347f, 0.27901134f, -0.36137494f, -0.36118156f, 0.22197971f, 0.27557442f, -0.06634006f, 0.0079667f, 0.12416199f, 0.3905206f, -0.10640851f, -0.0976817f, 0.15294972f, 0.39635518f, -0.02702999f, 0.39296314f, 0.15785322f, 0.21931258f, 0.31053296f, -0.36916667f, 0.38031587f, -0.21580373f, 0.27072677f, 0.23622236f, 0.34936687f, 0.18174365f, 0.35907319f, -0.17493086f, 0.324846f, -0.10781813f, 0.27201805f, 0.14324132f, -0.23681851f, -0.27115166f, -0.01580888f, -0.14943552f, 0.15465137f, 0.09784451f, -0.0337657f, -0.14884081f, 0.19931212f, -0.36002168f, 0.34663299f, -0.11405486f, 0.12672701f, 0.39463779f, -0.07886535f, -0.06384811f, 0.08249187f, -0.26816407f, -0.19905911f, 0.29211238f, 0.31264046f, -0.28664589f, 0.05698794f, 0.11613581f, 0.14078894f, 0.02187902f, -0.21781836f, -0.15567942f, 0.08693647f, -0.38256618f, 0.36580828f, -0.22922277f, -0.0226903f, 0.12878349f, -0.28122205f, -0.10850525f, -0.11955214f, 0.27179423f, -0.04710215f, 0.31069002f, 0.22672787f, 0.09580326f, 0.08682203f, 0.1258215f, 0.1851041f, 0.29228821f, 0.12366763f}}, {3, {}}, {4, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}},
+  // int -> INT32 map
+  {{5, {2}}, {6, {0}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{1, {-0.09623547f, -0.10193135f, 0.11083051f, -0.0347917f, 0.1141196f, 0.12965347f, -0.12652366f, 0.01007236f}}, {0, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/svdf_relaxed.example.cpp b/nn/runtime/test/generated/examples/svdf_relaxed.example.cpp
new file mode 100644
index 0000000..ec26015
--- /dev/null
+++ b/nn/runtime/test/generated/examples/svdf_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: svdf_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.12609188f, -0.46347019f, -0.89598465f, 0.12609188f, -0.46347019f, -0.89598465f}}, {1, {-0.31930989f, -0.36118156f, 0.0079667f, 0.37613347f, 0.22197971f, 0.12416199f, 0.27901134f, 0.27557442f, 0.3905206f, -0.36137494f, -0.06634006f, -0.10640851f}}, {2, {-0.31930989f, 0.37613347f, 0.27901134f, -0.36137494f, -0.36118156f, 0.22197971f, 0.27557442f, -0.06634006f, 0.0079667f, 0.12416199f, 0.3905206f, -0.10640851f, -0.0976817f, 0.15294972f, 0.39635518f, -0.02702999f, 0.39296314f, 0.15785322f, 0.21931258f, 0.31053296f, -0.36916667f, 0.38031587f, -0.21580373f, 0.27072677f, 0.23622236f, 0.34936687f, 0.18174365f, 0.35907319f, -0.17493086f, 0.324846f, -0.10781813f, 0.27201805f, 0.14324132f, -0.23681851f, -0.27115166f, -0.01580888f, -0.14943552f, 0.15465137f, 0.09784451f, -0.0337657f}}, {3, {}}, {4, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}},
+  // int -> INT32 map
+  {{5, {1}}, {6, {0}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{1, {0.014899f, -0.0517661f, -0.143725f, -0.00271883f, 0.014899f, -0.0517661f, -0.143725f, -0.00271883f}}, {0, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/svdf_state_relaxed.example.cpp b/nn/runtime/test/generated/examples/svdf_state_relaxed.example.cpp
new file mode 100644
index 0000000..e4d24b1
--- /dev/null
+++ b/nn/runtime/test/generated/examples/svdf_state_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: svdf_state_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.14278367f, -1.64410412f, -0.75222826f, 0.14278367f, -1.64410412f, -0.75222826f}}, {1, {-0.31930989f, -0.36118156f, 0.0079667f, 0.37613347f, 0.22197971f, 0.12416199f, 0.27901134f, 0.27557442f, 0.3905206f, -0.36137494f, -0.06634006f, -0.10640851f}}, {2, {-0.31930989f, 0.37613347f, 0.27901134f, -0.36137494f, -0.36118156f, 0.22197971f, 0.27557442f, -0.06634006f, 0.0079667f, 0.12416199f, 0.3905206f, -0.10640851f, -0.0976817f, 0.15294972f, 0.39635518f, -0.02702999f, 0.39296314f, 0.15785322f, 0.21931258f, 0.31053296f, -0.36916667f, 0.38031587f, -0.21580373f, 0.27072677f, 0.23622236f, 0.34936687f, 0.18174365f, 0.35907319f, -0.17493086f, 0.324846f, -0.10781813f, 0.27201805f, 0.14324132f, -0.23681851f, -0.27115166f, -0.01580888f, -0.14943552f, 0.15465137f, 0.09784451f, -0.0337657f}}, {3, {}}, {4, {0, 0, 0, 0, 0, 0, 0, 0, 0.119996f, 0, 0, 0, 0, 0, 0, 0, 0, 0, -0.166701f, 0, 0, 0, 0, 0, 0, 0, 0, 0, -0.44244f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.0805206f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.119996f, 0, 0, 0, 0, 0, 0, 0, 0, 0, -0.166701f, 0, 0, 0, 0, 0, 0, 0, 0, 0, -0.44244f, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.0805206f, 0}}},
+  // int -> INT32 map
+  {{5, {1}}, {6, {0}}},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{1, {0.068281f, -0.162217f, -0.152268f, 0.00323521f, 0.068281f, -0.162217f, -0.152268f, 0.00323521f}}, {0, {0, 0, 0, 0, 0, 0, 0, 0.119996f, 0.542235f, 0, 0, 0, 0, 0, 0, 0, 0, -0.166701f, -0.40465f, 0, 0, 0, 0, 0, 0, 0, 0, -0.44244f, -0.706995f, 0, 0, 0, 0, 0, 0, 0, 0, 0.0805206f, 0.137515f, 0, 0, 0, 0, 0, 0, 0, 0, 0.119996f, 0.542235f, 0, 0, 0, 0, 0, 0, 0, 0, -0.166701f, -0.40465f, 0, 0, 0, 0, 0, 0, 0, 0, -0.44244f, -0.706995f, 0, 0, 0, 0, 0, 0, 0, 0, 0.0805206f, 0.137515f, 0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/tanh_relaxed.example.cpp b/nn/runtime/test/generated/examples/tanh_relaxed.example.cpp
new file mode 100644
index 0000000..9c6f457
--- /dev/null
+++ b/nn/runtime/test/generated/examples/tanh_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: tanh_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-1, 0, 1, 10}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.761594156f, 0, 0.761594156f, 0.999999996f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/models/add_relaxed.model.cpp b/nn/runtime/test/generated/models/add_relaxed.model.cpp
new file mode 100644
index 0000000..0514c24
--- /dev/null
+++ b/nn/runtime/test/generated/models/add_relaxed.model.cpp
@@ -0,0 +1,26 @@
+// Generated file (from: add_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {2});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  auto act = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type0);
+  // Phase 2, operations
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_ADD, {op1, op2, act}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op2},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/avg_pool_float_1_relaxed.model.cpp b/nn/runtime/test/generated/models/avg_pool_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..92b9d08
--- /dev/null
+++ b/nn/runtime/test/generated/models/avg_pool_float_1_relaxed.model.cpp
@@ -0,0 +1,31 @@
+// Generated file (from: avg_pool_float_1_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto cons1 = model->addOperand(&type1);
+  auto pad0 = model->addOperand(&type1);
+  auto act = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type0);
+  // Phase 2, operations
+  static int32_t cons1_init[] = {1};
+  model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1);
+  static int32_t pad0_init[] = {0};
+  model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/avg_pool_float_2_relaxed.model.cpp b/nn/runtime/test/generated/models/avg_pool_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..bd81dbf
--- /dev/null
+++ b/nn/runtime/test/generated/models/avg_pool_float_2_relaxed.model.cpp
@@ -0,0 +1,35 @@
+// Generated file (from: avg_pool_float_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type2(Type::TENSOR_FLOAT32, {5, 11, 13, 3});
+  OperandType type0(Type::TENSOR_FLOAT32, {5, 52, 60, 3});
+  // Phase 1, operands
+  auto i0 = model->addOperand(&type0);
+  auto stride = model->addOperand(&type1);
+  auto filter = model->addOperand(&type1);
+  auto padding = model->addOperand(&type1);
+  auto activation = model->addOperand(&type1);
+  auto output = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t stride_init[] = {5};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  static int32_t filter_init[] = {100};
+  model->setOperandValue(filter, filter_init, sizeof(int32_t) * 1);
+  static int32_t padding_init[] = {50};
+  model->setOperandValue(padding, padding_init, sizeof(int32_t) * 1);
+  static int32_t activation_init[] = {0};
+  model->setOperandValue(activation, activation_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, activation}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {i0},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/avg_pool_float_3_relaxed.model.cpp b/nn/runtime/test/generated/models/avg_pool_float_3_relaxed.model.cpp
new file mode 100644
index 0000000..9df3ae6
--- /dev/null
+++ b/nn/runtime/test/generated/models/avg_pool_float_3_relaxed.model.cpp
@@ -0,0 +1,35 @@
+// Generated file (from: avg_pool_float_3_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 200, 180, 1});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 96, 86, 1});
+  // Phase 1, operands
+  auto i0 = model->addOperand(&type0);
+  auto stride = model->addOperand(&type1);
+  auto filter = model->addOperand(&type1);
+  auto padding = model->addOperand(&type1);
+  auto activation = model->addOperand(&type1);
+  auto output = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t stride_init[] = {2};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  static int32_t filter_init[] = {10};
+  model->setOperandValue(filter, filter_init, sizeof(int32_t) * 1);
+  static int32_t padding_init[] = {0};
+  model->setOperandValue(padding, padding_init, sizeof(int32_t) * 1);
+  static int32_t activation_init[] = {0};
+  model->setOperandValue(activation, activation_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, activation}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {i0},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/avg_pool_float_4_relaxed.model.cpp b/nn/runtime/test/generated/models/avg_pool_float_4_relaxed.model.cpp
new file mode 100644
index 0000000..e26884a
--- /dev/null
+++ b/nn/runtime/test/generated/models/avg_pool_float_4_relaxed.model.cpp
@@ -0,0 +1,35 @@
+// Generated file (from: avg_pool_float_4_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type2(Type::TENSOR_FLOAT32, {5, 11, 13, 3});
+  OperandType type0(Type::TENSOR_FLOAT32, {5, 52, 60, 3});
+  // Phase 1, operands
+  auto i0 = model->addOperand(&type0);
+  auto stride = model->addOperand(&type1);
+  auto filter = model->addOperand(&type1);
+  auto padding = model->addOperand(&type1);
+  auto relu6_activation = model->addOperand(&type1);
+  auto output = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t stride_init[] = {5};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  static int32_t filter_init[] = {100};
+  model->setOperandValue(filter, filter_init, sizeof(int32_t) * 1);
+  static int32_t padding_init[] = {50};
+  model->setOperandValue(padding, padding_init, sizeof(int32_t) * 1);
+  static int32_t relu6_activation_init[] = {3};
+  model->setOperandValue(relu6_activation, relu6_activation_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, relu6_activation}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {i0},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/concat_float_1_relaxed.model.cpp b/nn/runtime/test/generated/models/concat_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..83fdcbc
--- /dev/null
+++ b/nn/runtime/test/generated/models/concat_float_1_relaxed.model.cpp
@@ -0,0 +1,27 @@
+// Generated file (from: concat_float_1_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 3});
+  OperandType type2(Type::TENSOR_FLOAT32, {4, 3});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  auto axis0 = model->addOperand(&type1);
+  auto result = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t axis0_init[] = {0};
+  model->setOperandValue(axis0, axis0_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_CONCATENATION, {op1, op2, axis0}, {result});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op2},
+    {result});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/concat_float_2_relaxed.model.cpp b/nn/runtime/test/generated/models/concat_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..ec9dbbe
--- /dev/null
+++ b/nn/runtime/test/generated/models/concat_float_2_relaxed.model.cpp
@@ -0,0 +1,28 @@
+// Generated file (from: concat_float_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type1(Type::TENSOR_FLOAT32, {40, 230});
+  OperandType type0(Type::TENSOR_FLOAT32, {52, 230});
+  OperandType type3(Type::TENSOR_FLOAT32, {92, 230});
+  // Phase 1, operands
+  auto input1 = model->addOperand(&type0);
+  auto input2 = model->addOperand(&type1);
+  auto axis0 = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t axis0_init[] = {0};
+  model->setOperandValue(axis0, axis0_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_CONCATENATION, {input1, input2, axis0}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input1, input2},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/concat_float_3_relaxed.model.cpp b/nn/runtime/test/generated/models/concat_float_3_relaxed.model.cpp
new file mode 100644
index 0000000..7f0ac2d
--- /dev/null
+++ b/nn/runtime/test/generated/models/concat_float_3_relaxed.model.cpp
@@ -0,0 +1,28 @@
+// Generated file (from: concat_float_3_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type1(Type::TENSOR_FLOAT32, {212, 30});
+  OperandType type0(Type::TENSOR_FLOAT32, {212, 60});
+  OperandType type3(Type::TENSOR_FLOAT32, {212, 90});
+  // Phase 1, operands
+  auto input1 = model->addOperand(&type0);
+  auto input2 = model->addOperand(&type1);
+  auto axis1 = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t axis1_init[] = {1};
+  model->setOperandValue(axis1, axis1_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_CONCATENATION, {input1, input2, axis1}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input1, input2},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/conv_1_h3_w2_SAME_relaxed.model.cpp b/nn/runtime/test/generated/models/conv_1_h3_w2_SAME_relaxed.model.cpp
new file mode 100644
index 0000000..5e9e2ea
--- /dev/null
+++ b/nn/runtime/test/generated/models/conv_1_h3_w2_SAME_relaxed.model.cpp
@@ -0,0 +1,43 @@
+// Generated file (from: conv_1_h3_w2_SAME_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {1, 3, 2, 3});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 8, 8, 1});
+  OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3});
+  OperandType type4(Type::TENSOR_FLOAT32, {1});
+  // Phase 1, operands
+  auto b4 = model->addOperand(&type0);
+  auto b5 = model->addOperand(&type0);
+  auto b6 = model->addOperand(&type0);
+  auto b7 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  auto op0 = model->addOperand(&type3);
+  auto op1 = model->addOperand(&type4);
+  // Phase 2, operations
+  static int32_t b4_init[] = {1};
+  model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1);
+  static int32_t b5_init[] = {1};
+  model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1);
+  static int32_t b6_init[] = {1};
+  model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1);
+  static int32_t b7_init[] = {0};
+  model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1);
+  static float op0_init[] = {-0.966213f, -0.467474f, -0.82203f, -0.579455f, 0.0278809f, -0.79946f, -0.684259f, 0.563238f, 0.37289f, 0.738216f, 0.386045f, -0.917775f, 0.184325f, -0.270568f, 0.82236f, 0.0973683f, -0.941308f, -0.144706f};
+  model->setOperandValue(op0, op0_init, sizeof(float) * 18);
+  static float op1_init[] = {0.0f};
+  model->setOperandValue(op1, op1_init, sizeof(float) * 1);
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op2},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/conv_1_h3_w2_VALID_relaxed.model.cpp b/nn/runtime/test/generated/models/conv_1_h3_w2_VALID_relaxed.model.cpp
new file mode 100644
index 0000000..d6776da
--- /dev/null
+++ b/nn/runtime/test/generated/models/conv_1_h3_w2_VALID_relaxed.model.cpp
@@ -0,0 +1,43 @@
+// Generated file (from: conv_1_h3_w2_VALID_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {1, 3, 2, 3});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 6, 7, 1});
+  OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3});
+  OperandType type4(Type::TENSOR_FLOAT32, {1});
+  // Phase 1, operands
+  auto b4 = model->addOperand(&type0);
+  auto b5 = model->addOperand(&type0);
+  auto b6 = model->addOperand(&type0);
+  auto b7 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  auto op0 = model->addOperand(&type3);
+  auto op1 = model->addOperand(&type4);
+  // Phase 2, operations
+  static int32_t b4_init[] = {2};
+  model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1);
+  static int32_t b5_init[] = {1};
+  model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1);
+  static int32_t b6_init[] = {1};
+  model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1);
+  static int32_t b7_init[] = {0};
+  model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1);
+  static float op0_init[] = {-0.966213f, -0.467474f, -0.82203f, -0.579455f, 0.0278809f, -0.79946f, -0.684259f, 0.563238f, 0.37289f, 0.738216f, 0.386045f, -0.917775f, 0.184325f, -0.270568f, 0.82236f, 0.0973683f, -0.941308f, -0.144706f};
+  model->setOperandValue(op0, op0_init, sizeof(float) * 18);
+  static float op1_init[] = {0.0f};
+  model->setOperandValue(op1, op1_init, sizeof(float) * 1);
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op2},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/conv_3_h3_w2_SAME_relaxed.model.cpp b/nn/runtime/test/generated/models/conv_3_h3_w2_SAME_relaxed.model.cpp
new file mode 100644
index 0000000..f80407e
--- /dev/null
+++ b/nn/runtime/test/generated/models/conv_3_h3_w2_SAME_relaxed.model.cpp
@@ -0,0 +1,42 @@
+// Generated file (from: conv_3_h3_w2_SAME_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::INT32, {});
+  OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3});
+  OperandType type2(Type::TENSOR_FLOAT32, {3, 3, 2, 3});
+  OperandType type3(Type::TENSOR_FLOAT32, {3});
+  // Phase 1, operands
+  auto b4 = model->addOperand(&type0);
+  auto b5 = model->addOperand(&type0);
+  auto b6 = model->addOperand(&type0);
+  auto b7 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type1);
+  auto op0 = model->addOperand(&type2);
+  auto op1 = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t b4_init[] = {1};
+  model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1);
+  static int32_t b5_init[] = {1};
+  model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1);
+  static int32_t b6_init[] = {1};
+  model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1);
+  static int32_t b7_init[] = {0};
+  model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1);
+  static float op0_init[] = {-0.966213f, -0.579455f, -0.684259f, 0.738216f, 0.184325f, 0.0973683f, -0.176863f, -0.23936f, -0.000233404f, 0.055546f, -0.232658f, -0.316404f, -0.012904f, 0.320705f, -0.326657f, -0.919674f, 0.868081f, -0.824608f, -0.467474f, 0.0278809f, 0.563238f, 0.386045f, -0.270568f, -0.941308f, -0.779227f, -0.261492f, -0.774804f, -0.79665f, 0.22473f, -0.414312f, 0.685897f, -0.327792f, 0.77395f, -0.714578f, -0.972365f, 0.0696099f, -0.82203f, -0.79946f, 0.37289f, -0.917775f, 0.82236f, -0.144706f, -0.167188f, 0.268062f, 0.702641f, -0.412223f, 0.755759f, 0.721547f, -0.43637f, -0.274905f, -0.269165f, 0.16102f, 0.819857f, -0.312008f};
+  model->setOperandValue(op0, op0_init, sizeof(float) * 54);
+  static float op1_init[] = {0.0f, 0.0f, 0.0f};
+  model->setOperandValue(op1, op1_init, sizeof(float) * 3);
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op2},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/conv_3_h3_w2_VALID_relaxed.model.cpp b/nn/runtime/test/generated/models/conv_3_h3_w2_VALID_relaxed.model.cpp
new file mode 100644
index 0000000..7ecb597
--- /dev/null
+++ b/nn/runtime/test/generated/models/conv_3_h3_w2_VALID_relaxed.model.cpp
@@ -0,0 +1,43 @@
+// Generated file (from: conv_3_h3_w2_VALID_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::INT32, {});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 6, 7, 3});
+  OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3});
+  OperandType type3(Type::TENSOR_FLOAT32, {3, 3, 2, 3});
+  OperandType type4(Type::TENSOR_FLOAT32, {3});
+  // Phase 1, operands
+  auto b4 = model->addOperand(&type0);
+  auto b5 = model->addOperand(&type0);
+  auto b6 = model->addOperand(&type0);
+  auto b7 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  auto op0 = model->addOperand(&type3);
+  auto op1 = model->addOperand(&type4);
+  // Phase 2, operations
+  static int32_t b4_init[] = {2};
+  model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1);
+  static int32_t b5_init[] = {1};
+  model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1);
+  static int32_t b6_init[] = {1};
+  model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1);
+  static int32_t b7_init[] = {0};
+  model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1);
+  static float op0_init[] = {-0.966213f, -0.579455f, -0.684259f, 0.738216f, 0.184325f, 0.0973683f, -0.176863f, -0.23936f, -0.000233404f, 0.055546f, -0.232658f, -0.316404f, -0.012904f, 0.320705f, -0.326657f, -0.919674f, 0.868081f, -0.824608f, -0.467474f, 0.0278809f, 0.563238f, 0.386045f, -0.270568f, -0.941308f, -0.779227f, -0.261492f, -0.774804f, -0.79665f, 0.22473f, -0.414312f, 0.685897f, -0.327792f, 0.77395f, -0.714578f, -0.972365f, 0.0696099f, -0.82203f, -0.79946f, 0.37289f, -0.917775f, 0.82236f, -0.144706f, -0.167188f, 0.268062f, 0.702641f, -0.412223f, 0.755759f, 0.721547f, -0.43637f, -0.274905f, -0.269165f, 0.16102f, 0.819857f, -0.312008f};
+  model->setOperandValue(op0, op0_init, sizeof(float) * 54);
+  static float op1_init[] = {0.0f, 0.0f, 0.0f};
+  model->setOperandValue(op1, op1_init, sizeof(float) * 3);
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op2},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/conv_float_channels_relaxed.model.cpp b/nn/runtime/test/generated/models/conv_float_channels_relaxed.model.cpp
new file mode 100644
index 0000000..d1aec1f
--- /dev/null
+++ b/nn/runtime/test/generated/models/conv_float_channels_relaxed.model.cpp
@@ -0,0 +1,39 @@
+// Generated file (from: conv_float_channels_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type3(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 1, 1, 3});
+  OperandType type1(Type::TENSOR_FLOAT32, {3, 1, 1, 3});
+  OperandType type2(Type::TENSOR_FLOAT32, {3});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  auto pad0 = model->addOperand(&type3);
+  auto act = model->addOperand(&type3);
+  auto stride = model->addOperand(&type3);
+  auto op4 = model->addOperand(&type0);
+  // Phase 2, operations
+  static float op2_init[] = {1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f, 3.0f, 3.0f, 3.0f};
+  model->setOperandValue(op2, op2_init, sizeof(float) * 9);
+  static float op3_init[] = {0.0f, 0.0f, 0.0f};
+  model->setOperandValue(op3, op3_init, sizeof(float) * 3);
+  static int32_t pad0_init[] = {0};
+  model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  static int32_t stride_init[] = {1};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op4});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/conv_float_channels_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/models/conv_float_channels_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 0000000..0242f9a
--- /dev/null
+++ b/nn/runtime/test/generated/models/conv_float_channels_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,35 @@
+// Generated file (from: conv_float_channels_weights_as_inputs_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type3(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 1, 1, 3});
+  OperandType type1(Type::TENSOR_FLOAT32, {3, 1, 1, 3});
+  OperandType type2(Type::TENSOR_FLOAT32, {3});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  auto pad0 = model->addOperand(&type3);
+  auto act = model->addOperand(&type3);
+  auto stride = model->addOperand(&type3);
+  auto op4 = model->addOperand(&type0);
+  // Phase 2, operations
+  static int32_t pad0_init[] = {0};
+  model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  static int32_t stride_init[] = {1};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op2, op3},
+    {op4});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/conv_float_large_relaxed.model.cpp b/nn/runtime/test/generated/models/conv_float_large_relaxed.model.cpp
new file mode 100644
index 0000000..670df7d
--- /dev/null
+++ b/nn/runtime/test/generated/models/conv_float_large_relaxed.model.cpp
@@ -0,0 +1,39 @@
+// Generated file (from: conv_float_large_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type3(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 3, 3});
+  OperandType type1(Type::TENSOR_FLOAT32, {3, 1, 1, 3});
+  OperandType type2(Type::TENSOR_FLOAT32, {3});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  auto pad0 = model->addOperand(&type3);
+  auto act = model->addOperand(&type3);
+  auto stride = model->addOperand(&type3);
+  auto op4 = model->addOperand(&type0);
+  // Phase 2, operations
+  static float op2_init[] = {1.0f, 4.0f, 7.0f, 2.0f, 5.0f, 8.0f, 3.0f, 6.0f, 9.0f};
+  model->setOperandValue(op2, op2_init, sizeof(float) * 9);
+  static float op3_init[] = {0.0f, 0.0f, 0.0f};
+  model->setOperandValue(op3, op3_init, sizeof(float) * 3);
+  static int32_t pad0_init[] = {0};
+  model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  static int32_t stride_init[] = {1};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op4});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/conv_float_large_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/models/conv_float_large_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 0000000..1e01d04
--- /dev/null
+++ b/nn/runtime/test/generated/models/conv_float_large_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,35 @@
+// Generated file (from: conv_float_large_weights_as_inputs_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type3(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 3, 3});
+  OperandType type1(Type::TENSOR_FLOAT32, {3, 1, 1, 3});
+  OperandType type2(Type::TENSOR_FLOAT32, {3});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  auto pad0 = model->addOperand(&type3);
+  auto act = model->addOperand(&type3);
+  auto stride = model->addOperand(&type3);
+  auto op4 = model->addOperand(&type0);
+  // Phase 2, operations
+  static int32_t pad0_init[] = {0};
+  model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  static int32_t stride_init[] = {1};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op2, op3},
+    {op4});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/conv_float_relaxed.model.cpp b/nn/runtime/test/generated/models/conv_float_relaxed.model.cpp
new file mode 100644
index 0000000..e728eb5
--- /dev/null
+++ b/nn/runtime/test/generated/models/conv_float_relaxed.model.cpp
@@ -0,0 +1,39 @@
+// Generated file (from: conv_float_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type3(Type::INT32, {});
+  OperandType type1(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 3, 3, 1});
+  OperandType type2(Type::TENSOR_FLOAT32, {1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  auto pad0 = model->addOperand(&type3);
+  auto act = model->addOperand(&type3);
+  auto stride = model->addOperand(&type3);
+  auto op4 = model->addOperand(&type1);
+  // Phase 2, operations
+  static float op2_init[] = {0.25f, 0.25f, 0.25f, 0.25f};
+  model->setOperandValue(op2, op2_init, sizeof(float) * 4);
+  static float op3_init[] = {0.0f};
+  model->setOperandValue(op3, op3_init, sizeof(float) * 1);
+  static int32_t pad0_init[] = {0};
+  model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  static int32_t stride_init[] = {1};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op4});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/conv_float_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/models/conv_float_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 0000000..25cec50
--- /dev/null
+++ b/nn/runtime/test/generated/models/conv_float_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,35 @@
+// Generated file (from: conv_float_weights_as_inputs_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type3(Type::INT32, {});
+  OperandType type1(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 3, 3, 1});
+  OperandType type2(Type::TENSOR_FLOAT32, {1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  auto pad0 = model->addOperand(&type3);
+  auto act = model->addOperand(&type3);
+  auto stride = model->addOperand(&type3);
+  auto op4 = model->addOperand(&type1);
+  // Phase 2, operations
+  static int32_t pad0_init[] = {0};
+  model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  static int32_t stride_init[] = {1};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op2, op3},
+    {op4});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/depth_to_space_float_1_relaxed.model.cpp b/nn/runtime/test/generated/models/depth_to_space_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..e4443c1
--- /dev/null
+++ b/nn/runtime/test/generated/models/depth_to_space_float_1_relaxed.model.cpp
@@ -0,0 +1,26 @@
+// Generated file (from: depth_to_space_float_1_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 1, 1, 8});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 2, 2, 2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto block_size = model->addOperand(&type1);
+  auto output = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t block_size_init[] = {2};
+  model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_DEPTH_TO_SPACE, {input, block_size}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/depth_to_space_float_2_relaxed.model.cpp b/nn/runtime/test/generated/models/depth_to_space_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..988814f
--- /dev/null
+++ b/nn/runtime/test/generated/models/depth_to_space_float_2_relaxed.model.cpp
@@ -0,0 +1,26 @@
+// Generated file (from: depth_to_space_float_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 4});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 4, 4, 1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto block_size = model->addOperand(&type1);
+  auto output = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t block_size_init[] = {2};
+  model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_DEPTH_TO_SPACE, {input, block_size}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/depth_to_space_float_3_relaxed.model.cpp b/nn/runtime/test/generated/models/depth_to_space_float_3_relaxed.model.cpp
new file mode 100644
index 0000000..cc1ef9d
--- /dev/null
+++ b/nn/runtime/test/generated/models/depth_to_space_float_3_relaxed.model.cpp
@@ -0,0 +1,26 @@
+// Generated file (from: depth_to_space_float_3_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 8});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 4, 4, 2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto block_size = model->addOperand(&type1);
+  auto output = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t block_size_init[] = {2};
+  model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_DEPTH_TO_SPACE, {input, block_size}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/depthwise_conv2d_float_large_relaxed.model.cpp b/nn/runtime/test/generated/models/depthwise_conv2d_float_large_relaxed.model.cpp
new file mode 100644
index 0000000..7d31eae
--- /dev/null
+++ b/nn/runtime/test/generated/models/depthwise_conv2d_float_large_relaxed.model.cpp
@@ -0,0 +1,42 @@
+// Generated file (from: depthwise_conv2d_float_large_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {1, 1, 1, 2});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 2});
+  OperandType type1(Type::TENSOR_FLOAT32, {2});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  auto op3 = model->addOperand(&type1);
+  auto pad0 = model->addOperand(&type2);
+  auto act = model->addOperand(&type2);
+  auto stride = model->addOperand(&type2);
+  auto channelMultiplier = model->addOperand(&type2);
+  auto op4 = model->addOperand(&type3);
+  // Phase 2, operations
+  static float op2_init[] = {0.25f, 0.0f, 0.25f, 1.0f, 0.25f, 0.0f, 0.25f, 1.0f};
+  model->setOperandValue(op2, op2_init, sizeof(float) * 8);
+  static float op3_init[] = {100.0f, 200.0f};
+  model->setOperandValue(op3, op3_init, sizeof(float) * 2);
+  static int32_t pad0_init[] = {0};
+  model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  static int32_t stride_init[] = {1};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  static int32_t channelMultiplier_init[] = {1};
+  model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op4});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/depthwise_conv2d_float_large_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/models/depthwise_conv2d_float_large_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 0000000..e7e82e3
--- /dev/null
+++ b/nn/runtime/test/generated/models/depthwise_conv2d_float_large_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,38 @@
+// Generated file (from: depthwise_conv2d_float_large_weights_as_inputs_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {1, 1, 1, 2});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 2});
+  OperandType type1(Type::TENSOR_FLOAT32, {2});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  auto op3 = model->addOperand(&type1);
+  auto pad0 = model->addOperand(&type2);
+  auto act = model->addOperand(&type2);
+  auto stride = model->addOperand(&type2);
+  auto channelMultiplier = model->addOperand(&type2);
+  auto op4 = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t pad0_init[] = {0};
+  model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  static int32_t stride_init[] = {1};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  static int32_t channelMultiplier_init[] = {1};
+  model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op2, op3},
+    {op4});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/depthwise_conv_relaxed.model.cpp b/nn/runtime/test/generated/models/depthwise_conv_relaxed.model.cpp
new file mode 100644
index 0000000..7226dc4
--- /dev/null
+++ b/nn/runtime/test/generated/models/depthwise_conv_relaxed.model.cpp
@@ -0,0 +1,43 @@
+// Generated file (from: depthwise_conv_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::INT32, {});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 1, 1, 3});
+  OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3});
+  OperandType type3(Type::TENSOR_FLOAT32, {3});
+  // Phase 1, operands
+  auto b4 = model->addOperand(&type0);
+  auto b5 = model->addOperand(&type0);
+  auto b6 = model->addOperand(&type0);
+  auto b7 = model->addOperand(&type0);
+  auto b8 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type1);
+  auto op0 = model->addOperand(&type2);
+  auto op1 = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t b4_init[] = {1};
+  model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1);
+  static int32_t b5_init[] = {1};
+  model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1);
+  static int32_t b6_init[] = {1};
+  model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1);
+  static int32_t b7_init[] = {1};
+  model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1);
+  static int32_t b8_init[] = {0};
+  model->setOperandValue(b8, b8_init, sizeof(int32_t) * 1);
+  static float op0_init[] = {-0.966213f, -0.467474f, -0.82203f};
+  model->setOperandValue(op0, op0_init, sizeof(float) * 3);
+  static float op1_init[] = {0.0f, 0.0f, 0.0f};
+  model->setOperandValue(op1, op1_init, sizeof(float) * 3);
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op2},
+    {op3});
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/embedding_lookup_relaxed.model.cpp b/nn/runtime/test/generated/models/embedding_lookup_relaxed.model.cpp
new file mode 100644
index 0000000..cf5715c
--- /dev/null
+++ b/nn/runtime/test/generated/models/embedding_lookup_relaxed.model.cpp
@@ -0,0 +1,23 @@
+// Generated file (from: embedding_lookup_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::TENSOR_FLOAT32, {3, 2, 4});
+  OperandType type0(Type::TENSOR_INT32, {3});
+  // Phase 1, operands
+  auto index = model->addOperand(&type0);
+  auto value = model->addOperand(&type1);
+  auto output = model->addOperand(&type1);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_EMBEDDING_LOOKUP, {index, value}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {index, value},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/floor_relaxed.model.cpp b/nn/runtime/test/generated/models/floor_relaxed.model.cpp
new file mode 100644
index 0000000..d047198
--- /dev/null
+++ b/nn/runtime/test/generated/models/floor_relaxed.model.cpp
@@ -0,0 +1,21 @@
+// Generated file (from: floor_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 2});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_FLOOR, {op1}, {op2});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op2});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/fully_connected_float_relaxed.model.cpp b/nn/runtime/test/generated/models/fully_connected_float_relaxed.model.cpp
new file mode 100644
index 0000000..78526d6
--- /dev/null
+++ b/nn/runtime/test/generated/models/fully_connected_float_relaxed.model.cpp
@@ -0,0 +1,33 @@
+// Generated file (from: fully_connected_float_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type3(Type::INT32, {});
+  OperandType type1(Type::TENSOR_FLOAT32, {1, 1});
+  OperandType type2(Type::TENSOR_FLOAT32, {1});
+  OperandType type0(Type::TENSOR_FLOAT32, {3, 1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto b0 = model->addOperand(&type2);
+  auto op3 = model->addOperand(&type0);
+  auto act = model->addOperand(&type3);
+  // Phase 2, operations
+  static float op2_init[] = {2.0f};
+  model->setOperandValue(op2, op2_init, sizeof(float) * 1);
+  static float b0_init[] = {4.0f};
+  model->setOperandValue(b0, b0_init, sizeof(float) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/fully_connected_float_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/models/fully_connected_float_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 0000000..f095444
--- /dev/null
+++ b/nn/runtime/test/generated/models/fully_connected_float_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,29 @@
+// Generated file (from: fully_connected_float_weights_as_inputs_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type3(Type::INT32, {});
+  OperandType type1(Type::TENSOR_FLOAT32, {1, 1});
+  OperandType type2(Type::TENSOR_FLOAT32, {1});
+  OperandType type0(Type::TENSOR_FLOAT32, {3, 1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto b0 = model->addOperand(&type2);
+  auto op3 = model->addOperand(&type0);
+  auto act = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op2, b0},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/hashtable_lookup_float_relaxed.model.cpp b/nn/runtime/test/generated/models/hashtable_lookup_float_relaxed.model.cpp
new file mode 100644
index 0000000..aae1e03
--- /dev/null
+++ b/nn/runtime/test/generated/models/hashtable_lookup_float_relaxed.model.cpp
@@ -0,0 +1,28 @@
+// Generated file (from: hashtable_lookup_float_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::TENSOR_FLOAT32, {3, 2});
+  OperandType type3(Type::TENSOR_FLOAT32, {4, 2});
+  OperandType type1(Type::TENSOR_INT32, {3});
+  OperandType type0(Type::TENSOR_INT32, {4});
+  OperandType type4(Type::TENSOR_QUANT8_ASYMM, {4}, 1.f, 0);
+  // Phase 1, operands
+  auto lookup = model->addOperand(&type0);
+  auto key = model->addOperand(&type1);
+  auto value = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  auto hits = model->addOperand(&type4);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_HASHTABLE_LOOKUP, {lookup, key, value}, {output, hits});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {lookup, key, value},
+    {output, hits});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/l2_normalization_large_relaxed.model.cpp b/nn/runtime/test/generated/models/l2_normalization_large_relaxed.model.cpp
new file mode 100644
index 0000000..50969ea
--- /dev/null
+++ b/nn/runtime/test/generated/models/l2_normalization_large_relaxed.model.cpp
@@ -0,0 +1,21 @@
+// Generated file (from: l2_normalization_large_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 3});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_L2_NORMALIZATION, {op1}, {op2});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op2});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/l2_normalization_relaxed.model.cpp b/nn/runtime/test/generated/models/l2_normalization_relaxed.model.cpp
new file mode 100644
index 0000000..2bca831
--- /dev/null
+++ b/nn/runtime/test/generated/models/l2_normalization_relaxed.model.cpp
@@ -0,0 +1,21 @@
+// Generated file (from: l2_normalization_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 1, 1, 3});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_L2_NORMALIZATION, {op1}, {op2});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op2});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/l2_pool_float_relaxed.model.cpp b/nn/runtime/test/generated/models/l2_pool_float_relaxed.model.cpp
new file mode 100644
index 0000000..0b8efaa
--- /dev/null
+++ b/nn/runtime/test/generated/models/l2_pool_float_relaxed.model.cpp
@@ -0,0 +1,31 @@
+// Generated file (from: l2_pool_float_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto cons1 = model->addOperand(&type1);
+  auto pad0 = model->addOperand(&type1);
+  auto act = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type0);
+  // Phase 2, operations
+  static int32_t cons1_init[] = {1};
+  model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1);
+  static int32_t pad0_init[] = {0};
+  model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_L2_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/local_response_norm_float_1_relaxed.model.cpp b/nn/runtime/test/generated/models/local_response_norm_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..6f2f9b4
--- /dev/null
+++ b/nn/runtime/test/generated/models/local_response_norm_float_1_relaxed.model.cpp
@@ -0,0 +1,35 @@
+// Generated file (from: local_response_norm_float_1_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::FLOAT32, {});
+  OperandType type1(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 1, 1, 6});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto radius = model->addOperand(&type1);
+  auto bias = model->addOperand(&type2);
+  auto alpha = model->addOperand(&type2);
+  auto beta = model->addOperand(&type2);
+  auto output = model->addOperand(&type0);
+  // Phase 2, operations
+  static int32_t radius_init[] = {20};
+  model->setOperandValue(radius, radius_init, sizeof(int32_t) * 1);
+  static float bias_init[] = {9.0f};
+  model->setOperandValue(bias, bias_init, sizeof(float) * 1);
+  static float alpha_init[] = {4.0f};
+  model->setOperandValue(alpha, alpha_init, sizeof(float) * 1);
+  static float beta_init[] = {0.5f};
+  model->setOperandValue(beta, beta_init, sizeof(float) * 1);
+  model->addOperation(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/local_response_norm_float_2_relaxed.model.cpp b/nn/runtime/test/generated/models/local_response_norm_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..1e87939
--- /dev/null
+++ b/nn/runtime/test/generated/models/local_response_norm_float_2_relaxed.model.cpp
@@ -0,0 +1,35 @@
+// Generated file (from: local_response_norm_float_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::FLOAT32, {});
+  OperandType type1(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 1, 1, 6});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto radius = model->addOperand(&type1);
+  auto bias = model->addOperand(&type2);
+  auto alpha = model->addOperand(&type2);
+  auto beta = model->addOperand(&type2);
+  auto output = model->addOperand(&type0);
+  // Phase 2, operations
+  static int32_t radius_init[] = {20};
+  model->setOperandValue(radius, radius_init, sizeof(int32_t) * 1);
+  static float bias_init[] = {0.0f};
+  model->setOperandValue(bias, bias_init, sizeof(float) * 1);
+  static float alpha_init[] = {1.0f};
+  model->setOperandValue(alpha, alpha_init, sizeof(float) * 1);
+  static float beta_init[] = {0.5f};
+  model->setOperandValue(beta, beta_init, sizeof(float) * 1);
+  model->addOperation(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/local_response_norm_float_3_relaxed.model.cpp b/nn/runtime/test/generated/models/local_response_norm_float_3_relaxed.model.cpp
new file mode 100644
index 0000000..805d0de
--- /dev/null
+++ b/nn/runtime/test/generated/models/local_response_norm_float_3_relaxed.model.cpp
@@ -0,0 +1,35 @@
+// Generated file (from: local_response_norm_float_3_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::FLOAT32, {});
+  OperandType type1(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 1, 1, 6});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto radius = model->addOperand(&type1);
+  auto bias = model->addOperand(&type2);
+  auto alpha = model->addOperand(&type2);
+  auto beta = model->addOperand(&type2);
+  auto output = model->addOperand(&type0);
+  // Phase 2, operations
+  static int32_t radius_init[] = {20};
+  model->setOperandValue(radius, radius_init, sizeof(int32_t) * 1);
+  static float bias_init[] = {0.0f};
+  model->setOperandValue(bias, bias_init, sizeof(float) * 1);
+  static float alpha_init[] = {4.0f};
+  model->setOperandValue(alpha, alpha_init, sizeof(float) * 1);
+  static float beta_init[] = {0.5f};
+  model->setOperandValue(beta, beta_init, sizeof(float) * 1);
+  model->addOperation(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/local_response_norm_float_4_relaxed.model.cpp b/nn/runtime/test/generated/models/local_response_norm_float_4_relaxed.model.cpp
new file mode 100644
index 0000000..c5bd463
--- /dev/null
+++ b/nn/runtime/test/generated/models/local_response_norm_float_4_relaxed.model.cpp
@@ -0,0 +1,35 @@
+// Generated file (from: local_response_norm_float_4_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::FLOAT32, {});
+  OperandType type1(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 1, 1, 6});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto radius = model->addOperand(&type1);
+  auto bias = model->addOperand(&type2);
+  auto alpha = model->addOperand(&type2);
+  auto beta = model->addOperand(&type2);
+  auto output = model->addOperand(&type0);
+  // Phase 2, operations
+  static int32_t radius_init[] = {2};
+  model->setOperandValue(radius, radius_init, sizeof(int32_t) * 1);
+  static float bias_init[] = {9.0f};
+  model->setOperandValue(bias, bias_init, sizeof(float) * 1);
+  static float alpha_init[] = {4.0f};
+  model->setOperandValue(alpha, alpha_init, sizeof(float) * 1);
+  static float beta_init[] = {0.5f};
+  model->setOperandValue(beta, beta_init, sizeof(float) * 1);
+  model->addOperation(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/logistic_float_1_relaxed.model.cpp b/nn/runtime/test/generated/models/logistic_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..207c2fa
--- /dev/null
+++ b/nn/runtime/test/generated/models/logistic_float_1_relaxed.model.cpp
@@ -0,0 +1,21 @@
+// Generated file (from: logistic_float_1_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op3 = model->addOperand(&type0);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_LOGISTIC, {op1}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/logistic_float_2_relaxed.model.cpp b/nn/runtime/test/generated/models/logistic_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..6984cd7
--- /dev/null
+++ b/nn/runtime/test/generated/models/logistic_float_2_relaxed.model.cpp
@@ -0,0 +1,21 @@
+// Generated file (from: logistic_float_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 32, 40, 2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto output = model->addOperand(&type0);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_LOGISTIC, {input}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/lsh_projection_2_relaxed.model.cpp b/nn/runtime/test/generated/models/lsh_projection_2_relaxed.model.cpp
new file mode 100644
index 0000000..75f0064
--- /dev/null
+++ b/nn/runtime/test/generated/models/lsh_projection_2_relaxed.model.cpp
@@ -0,0 +1,32 @@
+// Generated file (from: lsh_projection_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type3(Type::INT32, {});
+  OperandType type2(Type::TENSOR_FLOAT32, {3});
+  OperandType type0(Type::TENSOR_FLOAT32, {4, 2});
+  OperandType type1(Type::TENSOR_INT32, {3, 2});
+  OperandType type4(Type::TENSOR_INT32, {4});
+  // Phase 1, operands
+  auto hash = model->addOperand(&type0);
+  auto lookup = model->addOperand(&type1);
+  auto weight = model->addOperand(&type2);
+  auto type_param = model->addOperand(&type3);
+  auto output = model->addOperand(&type4);
+  // Phase 2, operations
+  static float hash_init[] = {0.123f, 0.456f, -0.321f, -0.654f, 1.234f, 5.678f, -4.321f, -8.765f};
+  model->setOperandValue(hash, hash_init, sizeof(float) * 8);
+  static int32_t type_param_init[] = {1};
+  model->setOperandValue(type_param, type_param_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_LSH_PROJECTION, {hash, lookup, weight, type_param}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {lookup, weight},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/lsh_projection_relaxed.model.cpp b/nn/runtime/test/generated/models/lsh_projection_relaxed.model.cpp
new file mode 100644
index 0000000..5ac3f49
--- /dev/null
+++ b/nn/runtime/test/generated/models/lsh_projection_relaxed.model.cpp
@@ -0,0 +1,32 @@
+// Generated file (from: lsh_projection_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type3(Type::INT32, {});
+  OperandType type2(Type::TENSOR_FLOAT32, {3});
+  OperandType type0(Type::TENSOR_FLOAT32, {4, 2});
+  OperandType type1(Type::TENSOR_INT32, {3, 2});
+  OperandType type4(Type::TENSOR_INT32, {8});
+  // Phase 1, operands
+  auto hash = model->addOperand(&type0);
+  auto lookup = model->addOperand(&type1);
+  auto weight = model->addOperand(&type2);
+  auto type_param = model->addOperand(&type3);
+  auto output = model->addOperand(&type4);
+  // Phase 2, operations
+  static float hash_init[] = {0.123f, 0.456f, -0.321f, -0.654f, 1.234f, 5.678f, -4.321f, -8.765f};
+  model->setOperandValue(hash, hash_init, sizeof(float) * 8);
+  static int32_t type_param_init[] = {2};
+  model->setOperandValue(type_param, type_param_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_LSH_PROJECTION, {hash, lookup, weight, type_param}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {lookup, weight},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/lsh_projection_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/models/lsh_projection_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 0000000..07335bc
--- /dev/null
+++ b/nn/runtime/test/generated/models/lsh_projection_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,28 @@
+// Generated file (from: lsh_projection_weights_as_inputs_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::TENSOR_FLOAT32, {3});
+  OperandType type0(Type::TENSOR_FLOAT32, {4, 2});
+  OperandType type3(Type::TENSOR_INT32, {1});
+  OperandType type1(Type::TENSOR_INT32, {3, 2});
+  OperandType type4(Type::TENSOR_INT32, {8});
+  // Phase 1, operands
+  auto hash = model->addOperand(&type0);
+  auto lookup = model->addOperand(&type1);
+  auto weight = model->addOperand(&type2);
+  auto type_param = model->addOperand(&type3);
+  auto output = model->addOperand(&type4);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_LSH_PROJECTION, {hash, lookup, weight, type_param}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {hash, lookup, weight, type_param},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/lstm2_relaxed.model.cpp b/nn/runtime/test/generated/models/lstm2_relaxed.model.cpp
new file mode 100644
index 0000000..c5a5e1a
--- /dev/null
+++ b/nn/runtime/test/generated/models/lstm2_relaxed.model.cpp
@@ -0,0 +1,55 @@
+// Generated file (from: lstm2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type5(Type::TENSOR_FLOAT32, {0,0});
+  OperandType type3(Type::TENSOR_FLOAT32, {0});
+  OperandType type9(Type::TENSOR_FLOAT32, {1, 12});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2});
+  OperandType type6(Type::TENSOR_FLOAT32, {1, 4});
+  OperandType type8(Type::TENSOR_FLOAT32, {1});
+  OperandType type1(Type::TENSOR_FLOAT32, {4, 2});
+  OperandType type2(Type::TENSOR_FLOAT32, {4, 4});
+  OperandType type4(Type::TENSOR_FLOAT32, {4});
+  OperandType type7(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto input_to_input_weights = model->addOperand(&type1);
+  auto input_to_forget_weights = model->addOperand(&type1);
+  auto input_to_cell_weights = model->addOperand(&type1);
+  auto input_to_output_weights = model->addOperand(&type1);
+  auto recurrent_to_intput_weights = model->addOperand(&type2);
+  auto recurrent_to_forget_weights = model->addOperand(&type2);
+  auto recurrent_to_cell_weights = model->addOperand(&type2);
+  auto recurrent_to_output_weights = model->addOperand(&type2);
+  auto cell_to_input_weights = model->addOperand(&type3);
+  auto cell_to_forget_weights = model->addOperand(&type4);
+  auto cell_to_output_weights = model->addOperand(&type4);
+  auto input_gate_bias = model->addOperand(&type4);
+  auto forget_gate_bias = model->addOperand(&type4);
+  auto cell_gate_bias = model->addOperand(&type4);
+  auto output_gate_bias = model->addOperand(&type4);
+  auto projection_weights = model->addOperand(&type5);
+  auto projection_bias = model->addOperand(&type3);
+  auto output_state_in = model->addOperand(&type6);
+  auto cell_state_in = model->addOperand(&type6);
+  auto activation_param = model->addOperand(&type7);
+  auto cell_clip_param = model->addOperand(&type8);
+  auto proj_clip_param = model->addOperand(&type8);
+  auto scratch_buffer = model->addOperand(&type9);
+  auto output_state_out = model->addOperand(&type6);
+  auto cell_state_out = model->addOperand(&type6);
+  auto output = model->addOperand(&type6);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_LSTM, {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param}, {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param},
+    {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/lstm2_state2_relaxed.model.cpp b/nn/runtime/test/generated/models/lstm2_state2_relaxed.model.cpp
new file mode 100644
index 0000000..7216fb8
--- /dev/null
+++ b/nn/runtime/test/generated/models/lstm2_state2_relaxed.model.cpp
@@ -0,0 +1,55 @@
+// Generated file (from: lstm2_state2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type5(Type::TENSOR_FLOAT32, {0,0});
+  OperandType type3(Type::TENSOR_FLOAT32, {0});
+  OperandType type9(Type::TENSOR_FLOAT32, {1, 12});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2});
+  OperandType type6(Type::TENSOR_FLOAT32, {1, 4});
+  OperandType type8(Type::TENSOR_FLOAT32, {1});
+  OperandType type1(Type::TENSOR_FLOAT32, {4, 2});
+  OperandType type2(Type::TENSOR_FLOAT32, {4, 4});
+  OperandType type4(Type::TENSOR_FLOAT32, {4});
+  OperandType type7(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto input_to_input_weights = model->addOperand(&type1);
+  auto input_to_forget_weights = model->addOperand(&type1);
+  auto input_to_cell_weights = model->addOperand(&type1);
+  auto input_to_output_weights = model->addOperand(&type1);
+  auto recurrent_to_intput_weights = model->addOperand(&type2);
+  auto recurrent_to_forget_weights = model->addOperand(&type2);
+  auto recurrent_to_cell_weights = model->addOperand(&type2);
+  auto recurrent_to_output_weights = model->addOperand(&type2);
+  auto cell_to_input_weights = model->addOperand(&type3);
+  auto cell_to_forget_weights = model->addOperand(&type4);
+  auto cell_to_output_weights = model->addOperand(&type4);
+  auto input_gate_bias = model->addOperand(&type4);
+  auto forget_gate_bias = model->addOperand(&type4);
+  auto cell_gate_bias = model->addOperand(&type4);
+  auto output_gate_bias = model->addOperand(&type4);
+  auto projection_weights = model->addOperand(&type5);
+  auto projection_bias = model->addOperand(&type3);
+  auto output_state_in = model->addOperand(&type6);
+  auto cell_state_in = model->addOperand(&type6);
+  auto activation_param = model->addOperand(&type7);
+  auto cell_clip_param = model->addOperand(&type8);
+  auto proj_clip_param = model->addOperand(&type8);
+  auto scratch_buffer = model->addOperand(&type9);
+  auto output_state_out = model->addOperand(&type6);
+  auto cell_state_out = model->addOperand(&type6);
+  auto output = model->addOperand(&type6);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_LSTM, {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param}, {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param},
+    {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {1, 2, 0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/lstm2_state_relaxed.model.cpp b/nn/runtime/test/generated/models/lstm2_state_relaxed.model.cpp
new file mode 100644
index 0000000..5fbfcc1
--- /dev/null
+++ b/nn/runtime/test/generated/models/lstm2_state_relaxed.model.cpp
@@ -0,0 +1,55 @@
+// Generated file (from: lstm2_state_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type5(Type::TENSOR_FLOAT32, {0,0});
+  OperandType type3(Type::TENSOR_FLOAT32, {0});
+  OperandType type9(Type::TENSOR_FLOAT32, {1, 12});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2});
+  OperandType type6(Type::TENSOR_FLOAT32, {1, 4});
+  OperandType type8(Type::TENSOR_FLOAT32, {1});
+  OperandType type1(Type::TENSOR_FLOAT32, {4, 2});
+  OperandType type2(Type::TENSOR_FLOAT32, {4, 4});
+  OperandType type4(Type::TENSOR_FLOAT32, {4});
+  OperandType type7(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto input_to_input_weights = model->addOperand(&type1);
+  auto input_to_forget_weights = model->addOperand(&type1);
+  auto input_to_cell_weights = model->addOperand(&type1);
+  auto input_to_output_weights = model->addOperand(&type1);
+  auto recurrent_to_intput_weights = model->addOperand(&type2);
+  auto recurrent_to_forget_weights = model->addOperand(&type2);
+  auto recurrent_to_cell_weights = model->addOperand(&type2);
+  auto recurrent_to_output_weights = model->addOperand(&type2);
+  auto cell_to_input_weights = model->addOperand(&type3);
+  auto cell_to_forget_weights = model->addOperand(&type4);
+  auto cell_to_output_weights = model->addOperand(&type4);
+  auto input_gate_bias = model->addOperand(&type4);
+  auto forget_gate_bias = model->addOperand(&type4);
+  auto cell_gate_bias = model->addOperand(&type4);
+  auto output_gate_bias = model->addOperand(&type4);
+  auto projection_weights = model->addOperand(&type5);
+  auto projection_bias = model->addOperand(&type3);
+  auto output_state_in = model->addOperand(&type6);
+  auto cell_state_in = model->addOperand(&type6);
+  auto activation_param = model->addOperand(&type7);
+  auto cell_clip_param = model->addOperand(&type8);
+  auto proj_clip_param = model->addOperand(&type8);
+  auto scratch_buffer = model->addOperand(&type9);
+  auto output_state_out = model->addOperand(&type6);
+  auto cell_state_out = model->addOperand(&type6);
+  auto output = model->addOperand(&type6);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_LSTM, {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param}, {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param},
+    {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/lstm3_relaxed.model.cpp b/nn/runtime/test/generated/models/lstm3_relaxed.model.cpp
new file mode 100644
index 0000000..55e365e
--- /dev/null
+++ b/nn/runtime/test/generated/models/lstm3_relaxed.model.cpp
@@ -0,0 +1,56 @@
+// Generated file (from: lstm3_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type5(Type::TENSOR_FLOAT32, {0});
+  OperandType type4(Type::TENSOR_FLOAT32, {16,20});
+  OperandType type9(Type::TENSOR_FLOAT32, {1});
+  OperandType type6(Type::TENSOR_FLOAT32, {2, 16});
+  OperandType type7(Type::TENSOR_FLOAT32, {2, 20});
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 5});
+  OperandType type10(Type::TENSOR_FLOAT32, {2, 80});
+  OperandType type2(Type::TENSOR_FLOAT32, {20, 16});
+  OperandType type1(Type::TENSOR_FLOAT32, {20, 5});
+  OperandType type3(Type::TENSOR_FLOAT32, {20});
+  OperandType type8(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto input_to_input_weights = model->addOperand(&type1);
+  auto input_to_forget_weights = model->addOperand(&type1);
+  auto input_to_cell_weights = model->addOperand(&type1);
+  auto input_to_output_weights = model->addOperand(&type1);
+  auto recurrent_to_intput_weights = model->addOperand(&type2);
+  auto recurrent_to_forget_weights = model->addOperand(&type2);
+  auto recurrent_to_cell_weights = model->addOperand(&type2);
+  auto recurrent_to_output_weights = model->addOperand(&type2);
+  auto cell_to_input_weights = model->addOperand(&type3);
+  auto cell_to_forget_weights = model->addOperand(&type3);
+  auto cell_to_output_weights = model->addOperand(&type3);
+  auto input_gate_bias = model->addOperand(&type3);
+  auto forget_gate_bias = model->addOperand(&type3);
+  auto cell_gate_bias = model->addOperand(&type3);
+  auto output_gate_bias = model->addOperand(&type3);
+  auto projection_weights = model->addOperand(&type4);
+  auto projection_bias = model->addOperand(&type5);
+  auto output_state_in = model->addOperand(&type6);
+  auto cell_state_in = model->addOperand(&type7);
+  auto activation_param = model->addOperand(&type8);
+  auto cell_clip_param = model->addOperand(&type9);
+  auto proj_clip_param = model->addOperand(&type9);
+  auto scratch_buffer = model->addOperand(&type10);
+  auto output_state_out = model->addOperand(&type6);
+  auto cell_state_out = model->addOperand(&type7);
+  auto output = model->addOperand(&type6);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_LSTM, {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param}, {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param},
+    {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/lstm3_state2_relaxed.model.cpp b/nn/runtime/test/generated/models/lstm3_state2_relaxed.model.cpp
new file mode 100644
index 0000000..0e8ee70
--- /dev/null
+++ b/nn/runtime/test/generated/models/lstm3_state2_relaxed.model.cpp
@@ -0,0 +1,56 @@
+// Generated file (from: lstm3_state2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type5(Type::TENSOR_FLOAT32, {0});
+  OperandType type4(Type::TENSOR_FLOAT32, {16,20});
+  OperandType type9(Type::TENSOR_FLOAT32, {1});
+  OperandType type6(Type::TENSOR_FLOAT32, {2, 16});
+  OperandType type7(Type::TENSOR_FLOAT32, {2, 20});
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 5});
+  OperandType type10(Type::TENSOR_FLOAT32, {2, 80});
+  OperandType type2(Type::TENSOR_FLOAT32, {20, 16});
+  OperandType type1(Type::TENSOR_FLOAT32, {20, 5});
+  OperandType type3(Type::TENSOR_FLOAT32, {20});
+  OperandType type8(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto input_to_input_weights = model->addOperand(&type1);
+  auto input_to_forget_weights = model->addOperand(&type1);
+  auto input_to_cell_weights = model->addOperand(&type1);
+  auto input_to_output_weights = model->addOperand(&type1);
+  auto recurrent_to_intput_weights = model->addOperand(&type2);
+  auto recurrent_to_forget_weights = model->addOperand(&type2);
+  auto recurrent_to_cell_weights = model->addOperand(&type2);
+  auto recurrent_to_output_weights = model->addOperand(&type2);
+  auto cell_to_input_weights = model->addOperand(&type3);
+  auto cell_to_forget_weights = model->addOperand(&type3);
+  auto cell_to_output_weights = model->addOperand(&type3);
+  auto input_gate_bias = model->addOperand(&type3);
+  auto forget_gate_bias = model->addOperand(&type3);
+  auto cell_gate_bias = model->addOperand(&type3);
+  auto output_gate_bias = model->addOperand(&type3);
+  auto projection_weights = model->addOperand(&type4);
+  auto projection_bias = model->addOperand(&type5);
+  auto output_state_in = model->addOperand(&type6);
+  auto cell_state_in = model->addOperand(&type7);
+  auto activation_param = model->addOperand(&type8);
+  auto cell_clip_param = model->addOperand(&type9);
+  auto proj_clip_param = model->addOperand(&type9);
+  auto scratch_buffer = model->addOperand(&type10);
+  auto output_state_out = model->addOperand(&type6);
+  auto cell_state_out = model->addOperand(&type7);
+  auto output = model->addOperand(&type6);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_LSTM, {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param}, {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param},
+    {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/lstm3_state3_relaxed.model.cpp b/nn/runtime/test/generated/models/lstm3_state3_relaxed.model.cpp
new file mode 100644
index 0000000..462a86f
--- /dev/null
+++ b/nn/runtime/test/generated/models/lstm3_state3_relaxed.model.cpp
@@ -0,0 +1,56 @@
+// Generated file (from: lstm3_state3_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type5(Type::TENSOR_FLOAT32, {0});
+  OperandType type4(Type::TENSOR_FLOAT32, {16,20});
+  OperandType type9(Type::TENSOR_FLOAT32, {1});
+  OperandType type6(Type::TENSOR_FLOAT32, {2, 16});
+  OperandType type7(Type::TENSOR_FLOAT32, {2, 20});
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 5});
+  OperandType type10(Type::TENSOR_FLOAT32, {2, 80});
+  OperandType type2(Type::TENSOR_FLOAT32, {20, 16});
+  OperandType type1(Type::TENSOR_FLOAT32, {20, 5});
+  OperandType type3(Type::TENSOR_FLOAT32, {20});
+  OperandType type8(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto input_to_input_weights = model->addOperand(&type1);
+  auto input_to_forget_weights = model->addOperand(&type1);
+  auto input_to_cell_weights = model->addOperand(&type1);
+  auto input_to_output_weights = model->addOperand(&type1);
+  auto recurrent_to_intput_weights = model->addOperand(&type2);
+  auto recurrent_to_forget_weights = model->addOperand(&type2);
+  auto recurrent_to_cell_weights = model->addOperand(&type2);
+  auto recurrent_to_output_weights = model->addOperand(&type2);
+  auto cell_to_input_weights = model->addOperand(&type3);
+  auto cell_to_forget_weights = model->addOperand(&type3);
+  auto cell_to_output_weights = model->addOperand(&type3);
+  auto input_gate_bias = model->addOperand(&type3);
+  auto forget_gate_bias = model->addOperand(&type3);
+  auto cell_gate_bias = model->addOperand(&type3);
+  auto output_gate_bias = model->addOperand(&type3);
+  auto projection_weights = model->addOperand(&type4);
+  auto projection_bias = model->addOperand(&type5);
+  auto output_state_in = model->addOperand(&type6);
+  auto cell_state_in = model->addOperand(&type7);
+  auto activation_param = model->addOperand(&type8);
+  auto cell_clip_param = model->addOperand(&type9);
+  auto proj_clip_param = model->addOperand(&type9);
+  auto scratch_buffer = model->addOperand(&type10);
+  auto output_state_out = model->addOperand(&type6);
+  auto cell_state_out = model->addOperand(&type7);
+  auto output = model->addOperand(&type6);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_LSTM, {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param}, {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param},
+    {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {1, 2, 0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/lstm3_state_relaxed.model.cpp b/nn/runtime/test/generated/models/lstm3_state_relaxed.model.cpp
new file mode 100644
index 0000000..aa31514
--- /dev/null
+++ b/nn/runtime/test/generated/models/lstm3_state_relaxed.model.cpp
@@ -0,0 +1,56 @@
+// Generated file (from: lstm3_state_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type5(Type::TENSOR_FLOAT32, {0});
+  OperandType type4(Type::TENSOR_FLOAT32, {16,20});
+  OperandType type9(Type::TENSOR_FLOAT32, {1});
+  OperandType type6(Type::TENSOR_FLOAT32, {2, 16});
+  OperandType type7(Type::TENSOR_FLOAT32, {2, 20});
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 5});
+  OperandType type10(Type::TENSOR_FLOAT32, {2, 80});
+  OperandType type2(Type::TENSOR_FLOAT32, {20, 16});
+  OperandType type1(Type::TENSOR_FLOAT32, {20, 5});
+  OperandType type3(Type::TENSOR_FLOAT32, {20});
+  OperandType type8(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto input_to_input_weights = model->addOperand(&type1);
+  auto input_to_forget_weights = model->addOperand(&type1);
+  auto input_to_cell_weights = model->addOperand(&type1);
+  auto input_to_output_weights = model->addOperand(&type1);
+  auto recurrent_to_intput_weights = model->addOperand(&type2);
+  auto recurrent_to_forget_weights = model->addOperand(&type2);
+  auto recurrent_to_cell_weights = model->addOperand(&type2);
+  auto recurrent_to_output_weights = model->addOperand(&type2);
+  auto cell_to_input_weights = model->addOperand(&type3);
+  auto cell_to_forget_weights = model->addOperand(&type3);
+  auto cell_to_output_weights = model->addOperand(&type3);
+  auto input_gate_bias = model->addOperand(&type3);
+  auto forget_gate_bias = model->addOperand(&type3);
+  auto cell_gate_bias = model->addOperand(&type3);
+  auto output_gate_bias = model->addOperand(&type3);
+  auto projection_weights = model->addOperand(&type4);
+  auto projection_bias = model->addOperand(&type5);
+  auto output_state_in = model->addOperand(&type6);
+  auto cell_state_in = model->addOperand(&type7);
+  auto activation_param = model->addOperand(&type8);
+  auto cell_clip_param = model->addOperand(&type9);
+  auto proj_clip_param = model->addOperand(&type9);
+  auto scratch_buffer = model->addOperand(&type10);
+  auto output_state_out = model->addOperand(&type6);
+  auto cell_state_out = model->addOperand(&type7);
+  auto output = model->addOperand(&type6);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_LSTM, {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param}, {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param},
+    {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/lstm_relaxed.model.cpp b/nn/runtime/test/generated/models/lstm_relaxed.model.cpp
new file mode 100644
index 0000000..4419621
--- /dev/null
+++ b/nn/runtime/test/generated/models/lstm_relaxed.model.cpp
@@ -0,0 +1,55 @@
+// Generated file (from: lstm_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type5(Type::TENSOR_FLOAT32, {0,0});
+  OperandType type3(Type::TENSOR_FLOAT32, {0});
+  OperandType type9(Type::TENSOR_FLOAT32, {1, 16});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2});
+  OperandType type6(Type::TENSOR_FLOAT32, {1, 4});
+  OperandType type8(Type::TENSOR_FLOAT32, {1});
+  OperandType type1(Type::TENSOR_FLOAT32, {4, 2});
+  OperandType type2(Type::TENSOR_FLOAT32, {4, 4});
+  OperandType type4(Type::TENSOR_FLOAT32, {4});
+  OperandType type7(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto input_to_input_weights = model->addOperand(&type1);
+  auto input_to_forget_weights = model->addOperand(&type1);
+  auto input_to_cell_weights = model->addOperand(&type1);
+  auto input_to_output_weights = model->addOperand(&type1);
+  auto recurrent_to_intput_weights = model->addOperand(&type2);
+  auto recurrent_to_forget_weights = model->addOperand(&type2);
+  auto recurrent_to_cell_weights = model->addOperand(&type2);
+  auto recurrent_to_output_weights = model->addOperand(&type2);
+  auto cell_to_input_weights = model->addOperand(&type3);
+  auto cell_to_forget_weights = model->addOperand(&type3);
+  auto cell_to_output_weights = model->addOperand(&type3);
+  auto input_gate_bias = model->addOperand(&type4);
+  auto forget_gate_bias = model->addOperand(&type4);
+  auto cell_gate_bias = model->addOperand(&type4);
+  auto output_gate_bias = model->addOperand(&type4);
+  auto projection_weights = model->addOperand(&type5);
+  auto projection_bias = model->addOperand(&type3);
+  auto output_state_in = model->addOperand(&type6);
+  auto cell_state_in = model->addOperand(&type6);
+  auto activation_param = model->addOperand(&type7);
+  auto cell_clip_param = model->addOperand(&type8);
+  auto proj_clip_param = model->addOperand(&type8);
+  auto scratch_buffer = model->addOperand(&type9);
+  auto output_state_out = model->addOperand(&type6);
+  auto cell_state_out = model->addOperand(&type6);
+  auto output = model->addOperand(&type6);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_LSTM, {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param}, {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param},
+    {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/lstm_state2_relaxed.model.cpp b/nn/runtime/test/generated/models/lstm_state2_relaxed.model.cpp
new file mode 100644
index 0000000..04e164c
--- /dev/null
+++ b/nn/runtime/test/generated/models/lstm_state2_relaxed.model.cpp
@@ -0,0 +1,55 @@
+// Generated file (from: lstm_state2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type5(Type::TENSOR_FLOAT32, {0,0});
+  OperandType type3(Type::TENSOR_FLOAT32, {0});
+  OperandType type9(Type::TENSOR_FLOAT32, {1, 16});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2});
+  OperandType type6(Type::TENSOR_FLOAT32, {1, 4});
+  OperandType type8(Type::TENSOR_FLOAT32, {1});
+  OperandType type1(Type::TENSOR_FLOAT32, {4, 2});
+  OperandType type2(Type::TENSOR_FLOAT32, {4, 4});
+  OperandType type4(Type::TENSOR_FLOAT32, {4});
+  OperandType type7(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto input_to_input_weights = model->addOperand(&type1);
+  auto input_to_forget_weights = model->addOperand(&type1);
+  auto input_to_cell_weights = model->addOperand(&type1);
+  auto input_to_output_weights = model->addOperand(&type1);
+  auto recurrent_to_intput_weights = model->addOperand(&type2);
+  auto recurrent_to_forget_weights = model->addOperand(&type2);
+  auto recurrent_to_cell_weights = model->addOperand(&type2);
+  auto recurrent_to_output_weights = model->addOperand(&type2);
+  auto cell_to_input_weights = model->addOperand(&type3);
+  auto cell_to_forget_weights = model->addOperand(&type3);
+  auto cell_to_output_weights = model->addOperand(&type3);
+  auto input_gate_bias = model->addOperand(&type4);
+  auto forget_gate_bias = model->addOperand(&type4);
+  auto cell_gate_bias = model->addOperand(&type4);
+  auto output_gate_bias = model->addOperand(&type4);
+  auto projection_weights = model->addOperand(&type5);
+  auto projection_bias = model->addOperand(&type3);
+  auto output_state_in = model->addOperand(&type6);
+  auto cell_state_in = model->addOperand(&type6);
+  auto activation_param = model->addOperand(&type7);
+  auto cell_clip_param = model->addOperand(&type8);
+  auto proj_clip_param = model->addOperand(&type8);
+  auto scratch_buffer = model->addOperand(&type9);
+  auto output_state_out = model->addOperand(&type6);
+  auto cell_state_out = model->addOperand(&type6);
+  auto output = model->addOperand(&type6);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_LSTM, {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param}, {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param},
+    {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {1, 2, 0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/lstm_state_relaxed.model.cpp b/nn/runtime/test/generated/models/lstm_state_relaxed.model.cpp
new file mode 100644
index 0000000..f237f47
--- /dev/null
+++ b/nn/runtime/test/generated/models/lstm_state_relaxed.model.cpp
@@ -0,0 +1,55 @@
+// Generated file (from: lstm_state_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type5(Type::TENSOR_FLOAT32, {0,0});
+  OperandType type3(Type::TENSOR_FLOAT32, {0});
+  OperandType type9(Type::TENSOR_FLOAT32, {1, 16});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2});
+  OperandType type6(Type::TENSOR_FLOAT32, {1, 4});
+  OperandType type8(Type::TENSOR_FLOAT32, {1});
+  OperandType type1(Type::TENSOR_FLOAT32, {4, 2});
+  OperandType type2(Type::TENSOR_FLOAT32, {4, 4});
+  OperandType type4(Type::TENSOR_FLOAT32, {4});
+  OperandType type7(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto input_to_input_weights = model->addOperand(&type1);
+  auto input_to_forget_weights = model->addOperand(&type1);
+  auto input_to_cell_weights = model->addOperand(&type1);
+  auto input_to_output_weights = model->addOperand(&type1);
+  auto recurrent_to_intput_weights = model->addOperand(&type2);
+  auto recurrent_to_forget_weights = model->addOperand(&type2);
+  auto recurrent_to_cell_weights = model->addOperand(&type2);
+  auto recurrent_to_output_weights = model->addOperand(&type2);
+  auto cell_to_input_weights = model->addOperand(&type3);
+  auto cell_to_forget_weights = model->addOperand(&type3);
+  auto cell_to_output_weights = model->addOperand(&type3);
+  auto input_gate_bias = model->addOperand(&type4);
+  auto forget_gate_bias = model->addOperand(&type4);
+  auto cell_gate_bias = model->addOperand(&type4);
+  auto output_gate_bias = model->addOperand(&type4);
+  auto projection_weights = model->addOperand(&type5);
+  auto projection_bias = model->addOperand(&type3);
+  auto output_state_in = model->addOperand(&type6);
+  auto cell_state_in = model->addOperand(&type6);
+  auto activation_param = model->addOperand(&type7);
+  auto cell_clip_param = model->addOperand(&type8);
+  auto proj_clip_param = model->addOperand(&type8);
+  auto scratch_buffer = model->addOperand(&type9);
+  auto output_state_out = model->addOperand(&type6);
+  auto cell_state_out = model->addOperand(&type6);
+  auto output = model->addOperand(&type6);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_LSTM, {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param}, {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param},
+    {scratch_buffer, output_state_out, cell_state_out, output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/max_pool_float_1_relaxed.model.cpp b/nn/runtime/test/generated/models/max_pool_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..22f5484
--- /dev/null
+++ b/nn/runtime/test/generated/models/max_pool_float_1_relaxed.model.cpp
@@ -0,0 +1,31 @@
+// Generated file (from: max_pool_float_1_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto cons1 = model->addOperand(&type1);
+  auto pad0 = model->addOperand(&type1);
+  auto act = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type0);
+  // Phase 2, operations
+  static int32_t cons1_init[] = {1};
+  model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1);
+  static int32_t pad0_init[] = {0};
+  model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/max_pool_float_2_relaxed.model.cpp b/nn/runtime/test/generated/models/max_pool_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..db2e907
--- /dev/null
+++ b/nn/runtime/test/generated/models/max_pool_float_2_relaxed.model.cpp
@@ -0,0 +1,35 @@
+// Generated file (from: max_pool_float_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type2(Type::TENSOR_FLOAT32, {5, 2, 3, 3});
+  OperandType type0(Type::TENSOR_FLOAT32, {5, 50, 70, 3});
+  // Phase 1, operands
+  auto i0 = model->addOperand(&type0);
+  auto stride = model->addOperand(&type1);
+  auto filter = model->addOperand(&type1);
+  auto padding = model->addOperand(&type1);
+  auto activation = model->addOperand(&type1);
+  auto output = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t stride_init[] = {20};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  static int32_t filter_init[] = {20};
+  model->setOperandValue(filter, filter_init, sizeof(int32_t) * 1);
+  static int32_t padding_init[] = {0};
+  model->setOperandValue(padding, padding_init, sizeof(int32_t) * 1);
+  static int32_t activation_init[] = {0};
+  model->setOperandValue(activation, activation_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_MAX_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, activation}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {i0},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/max_pool_float_3_relaxed.model.cpp b/nn/runtime/test/generated/models/max_pool_float_3_relaxed.model.cpp
new file mode 100644
index 0000000..0a78f0c
--- /dev/null
+++ b/nn/runtime/test/generated/models/max_pool_float_3_relaxed.model.cpp
@@ -0,0 +1,35 @@
+// Generated file (from: max_pool_float_3_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type2(Type::TENSOR_FLOAT32, {5, 2, 3, 3});
+  OperandType type0(Type::TENSOR_FLOAT32, {5, 50, 70, 3});
+  // Phase 1, operands
+  auto i0 = model->addOperand(&type0);
+  auto stride = model->addOperand(&type1);
+  auto filter = model->addOperand(&type1);
+  auto padding = model->addOperand(&type1);
+  auto relu6_activation = model->addOperand(&type1);
+  auto output = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t stride_init[] = {20};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  static int32_t filter_init[] = {20};
+  model->setOperandValue(filter, filter_init, sizeof(int32_t) * 1);
+  static int32_t padding_init[] = {0};
+  model->setOperandValue(padding, padding_init, sizeof(int32_t) * 1);
+  static int32_t relu6_activation_init[] = {3};
+  model->setOperandValue(relu6_activation, relu6_activation_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_MAX_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, relu6_activation}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {i0},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/mobilenet_224_gender_basic_fixed.model.cpp b/nn/runtime/test/generated/models/mobilenet_224_gender_basic_fixed.model.cpp
index 9e0fcd5..e20b010 100644
--- a/nn/runtime/test/generated/models/mobilenet_224_gender_basic_fixed.model.cpp
+++ b/nn/runtime/test/generated/models/mobilenet_224_gender_basic_fixed.model.cpp
@@ -625,11 +625,11 @@
   model->setOperandValue(op79, op79_init, sizeof(float) * 128);
   static float op80_init[] = {0.143542f, -0.139317f, -0.0557127f, 0.00193462f, -0.0166539f, 0.216436f, 0.0694379f, 0.0774276f, -0.061387f, 0.193228f, -0.0234282f, 0.0303868f, -0.10475f, 0.225842f, -0.0953071f, 0.0518284f, -0.177148f, 0.0706816f, -0.116163f, 0.23116f, 0.0276252f, 0.361075f, 0.114999f, -0.179934f, 0.0362276f, 0.098386f, 0.160729f, -0.203046f, -0.0214891f, -0.0217361f, -0.0319598f, -0.0163527f, 0.0405451f, -0.0441358f, -0.0010904f, -0.219479f, -0.0129676f, 0.0840713f, -0.334326f, -0.275725f, 0.00787852f, 0.102421f, 0.0265449f, -0.0439835f, -0.160807f, 0.128618f, 0.00937286f, 0.0634051f, 0.17013f, -0.149011f, -0.148228f, -0.185353f, -0.230108f, 0.0953904f, -0.0328099f, 0.08806f, 0.164153f, -0.155663f, 0.00662038f, 0.106636f, -0.110083f, -0.123108f, -0.0422361f, 0.00699063f, 0.0286107f, 0.0872556f, 0.0372735f, 0.129417f, 0.0114595f, 0.127069f, 0.0845895f, -0.103232f, -0.084375f, 0.0507973f, 0.0924024f, -0.0443189f, -0.0373084f, -0.0547004f, -0.107631f, -0.0137342f, -0.0308677f, 0.0818465f, 0.0348359f, -0.108934f, -0.0827724f, 0.0323507f, 0.0412687f, 0.0808453f, -0.051265f, 0.0951301f, -0.144128f, 0.0754425f, -0.127725f, 0.0168919f, -0.0751399f, -0.0739095f, 0.00380989f, -0.118355f, 0.131179f, 0.123024f, 0.13949f, -0.0452833f, 0.0908636f, -0.044923f, 0.0656833f, 0.154517f, -0.0803701f, -0.0962871f, 0.0389703f, 0.208096f, -0.0663933f, -0.131471f, -0.0790224f, 0.101245f, 0.0744562f, 0.210848f, -0.0880954f, 0.28261f, -0.0400531f, -0.0429046f, 0.115284f, 0.0810933f, -0.0732279f, -0.0363539f, 0.0390622f, 0.194268f, -0.125276f, 0.0660326f, -0.0191896f, -0.107549f, -0.068292f, 0.0296083f, -0.148026f, 0.00504009f, 0.136341f, 0.0185907f, 0.0354229f, 0.0570693f, -0.0652823f, 0.053643f, -0.226353f, -0.0586207f, 0.102557f, -0.0804407f, -0.0549814f, -0.0189678f, 0.0337161f, -0.240366f, -0.0152426f, -0.032301f, 0.0503872f, -0.00353695f, 0.0145041f, -0.0507668f, 0.0484236f, 0.0752401f, 0.131723f, 0.137027f, 0.0677545f, 0.149137f, -0.136712f, -0.047893f, -0.196069f, 0.000413097f, 0.0625105f, 0.0322905f, 0.053051f, -0.0330334f, 0.00132125f, 0.113487f, -0.120027f, 0.101515f, -0.0197327f, -0.0517467f, -0.11808f, 0.0443416f, 0.0221126f, 0.114449f, -0.0283071f, -0.139215f, 0.0598481f, 0.100257f, 0.0225039f, 0.0457186f, 0.0902391f, -0.0631196f, 0.0257833f, 0.112569f, -0.19343f, -0.0384445f, 0.0758919f, -0.0712537f, 0.00513168f, 0.151857f, -0.142854f, -0.0268036f, 0.0715712f, -0.0574248f, -0.03567f, -0.166058f, 0.0211768f, -0.119797f, -0.11925f, -0.0453431f, 0.0293065f, 0.120933f, 0.00402085f, 0.109672f, 0.134472f, 0.195219f, 0.180352f, -0.0515071f, -0.0545261f, 0.0322048f, 0.012976f, 0.0343293f, -0.0513619f, -0.0167084f, -0.160956f, -0.0328522f, -0.0399779f, 0.114662f, -0.0672433f, 0.125241f, -0.102642f, 0.0559623f, 0.13515f, 0.066221f, 0.0132642f, 0.0813321f, -0.0672475f, -0.0972056f, 0.0324055f, 0.0954416f, 0.0394797f, -0.0865308f, 0.0588531f, 0.0190956f, 0.102544f, 0.0641314f, 0.05755f, 0.114106f, 0.0457606f, -0.0910149f, -0.143913f, 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-0.162612f, -0.150023f, -0.0716221f, 0.259024f, 0.0160795f, 0.0360771f, 0.0459445f, 0.0688876f, 0.0756439f, -0.0865408f, 0.127239f, -0.0440397f, -0.011109f, 0.00759728f, 0.355613f, -0.0127272f, 0.151964f, 0.116613f, 0.0114587f, -0.128119f, -0.0993558f, -0.0549541f, -0.00706599f, 0.0289976f, 0.125323f, -0.053071f, 0.0550674f, -0.0443678f, -0.0726763f, -0.0886086f, -0.116334f, -0.0209192f, 0.063885f, 0.077968f, -0.104398f, -0.179266f, -0.194832f, -0.0639122f, -0.0518158f, 0.256032f, -0.108148f, -0.137127f, -0.104448f, 0.033398f, -0.0646876f, 0.0763196f, -0.0495609f, -0.100906f, -0.134571f, -0.161793f, 0.153519f, 0.149706f, -0.222311f, 0.0359835f, -0.00287598f, -0.160517f, 0.00736621f, 0.039841f, -0.000592701f, -0.056578f, 0.131453f, 0.0138361f, -0.134636f, -0.06908f, -0.0854272f, 0.0779619f, -0.0139243f, -0.0182492f, -0.0930189f, -0.00353997f, 0.0685898f, -0.0102112f, 0.0606511f, 0.063219f, -0.0267228f, 0.00053972f, -0.181391f, 0.0220468f, 0.202779f, 0.228042f, -0.191374f, -0.0386773f, -0.0833115f, 0.132745f, -0.0764369f, -0.0667909f, 0.0471235f, -0.0951605f, 0.0251998f, 0.109606f, -0.0551212f, 0.0423476f, -0.0914923f, 0.104139f, -0.166891f, -0.144794f, 0.00263478f, 0.0549706f, -0.0192015f, -0.094959f, -0.0470626f};
   model->setOperandValue(op80, op80_init, sizeof(float) * 16384);
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op86, op2, op1, b87, b88, b89, b90}, {op0});
   static float op83_init[] = {-0.0293549f, -0.0835053f, -0.228576f, -0.0980885f, -0.0370638f, -0.195879f, -0.0452258f, 0.0371641f, -0.0585841f, -0.0984154f, -0.141293f};
   model->setOperandValue(op83, op83_init, sizeof(float) * 11);
   static float op84_init[] = {0.0984852f, 0.672424f, 0.392549f, -0.262182f, 0.303914f, -0.0118188f, 0.027943f, 0.0164078f, 0.200583f, -0.808626f, 0.234772f, -0.0253635f, -0.198519f, -0.176824f, -0.580674f, 0.0681573f, -0.0134279f, 0.172173f, -0.284882f, -0.0895141f, 0.0142356f, -0.0479431f, 0.0736678f, 0.00298977f, 0.152355f, -0.0370715f, 0.463201f, 0.0146613f, 0.0971624f, -0.0791196f, 0.556621f, -0.00950762f, 0.0160531f, 0.091037f, 0.376353f, -0.0996081f, -0.0418334f, -0.427482f, -0.202679f, -0.197079f, 0.021873f, -0.105617f, 0.36447f, 0.389277f, 0.0429815f, 0.0480496f, -0.170086f, -0.191548f, -0.237921f, 0.155838f, -0.100796f, 0.0539355f, 0.103154f, 0.0441985f, -0.20672f, 0.358565f, -0.105794f, -0.635905f, 0.193301f, 0.112419f, -0.184668f, 0.157954f, -0.301095f, -0.153072f, -0.0535615f, -0.0661999f, -0.197056f, -0.0835003f, -0.074932f, -0.111766f, -0.356266f, 0.649165f, -0.0527003f, -0.0597135f, 0.109839f, -0.270809f, 0.0333183f, -0.211454f, 0.0594729f, -0.166949f, 0.21057f, 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-0.182135f, 0.112932f, -0.32439f, 0.294457f, -0.0818895f, 0.0914322f, 0.185025f, 0.0543957f, -0.0167575f, 0.504046f, -0.0647153f, -0.166975f, 0.0248059f, 0.0379442f, 0.0980366f, -0.178135f, 0.143822f, 0.45732f, -0.0912428f, -0.179338f, 0.349726f, -0.0596313f, -0.299861f, 0.112567f, 0.0666395f, 0.345303f, 0.164124f, -0.00265316f, -0.0732412f, 0.348079f, -0.249414f, 0.0465329f, 0.0693596f, 0.0799214f, 0.000123214f, 0.180679f, 0.0912923f, -0.300121f, -0.288428f, 0.150135f, 0.112936f, 0.104813f, -0.0555879f, -0.00205972f, -0.0251151f, -0.0788264f, -0.016778f, -0.110796f, -0.083048f, -0.212734f, 0.288568f, -0.114228f, -0.113358f, 0.110789f, 0.118645f, 0.133466f, -0.0298552f, -0.241374f, 0.157257f, 0.0861554f, -0.0909277f, 0.00156177f, 0.106539f, -0.209104f, -0.106974f, 0.0203283f, -0.18111f, -0.311602f, -0.00371812f, 0.0711113f, -0.206721f, 0.286076f, 0.139713f, 0.116621f, 0.182792f, 0.0246107f, -0.17972f, 0.041917f, 0.0724635f, 0.266344f, 0.0989191f, 0.0723898f, 0.0257298f, 0.104898f, 0.0681826f, -0.0704781f, 0.00212139f, -0.363547f, 0.0274255f, -0.106295f, -0.363965f, 0.127051f, -0.0575343f, -0.200952f, -0.0666189f, -0.139465f, -0.0171747f, 0.253794f, -0.258602f, -0.166356f, -0.107649f, 0.267331f, 0.104521f, -0.020921f, -0.0780469f, 0.125002f, 0.0202556f, -0.0899181f, -0.126559f, -0.297855f, 0.121539f, -0.0671643f, -0.0444782f, 0.334408f, 0.0882725f, -0.0879492f, -0.00277655f, -0.0616985f, 0.0564236f, -0.11618f, -0.22836f, 0.112953f, 0.176082f, 0.09988f, -0.00635589f, -0.114234f, 0.241135f, 0.0966775f, -0.0961065f, 0.137214f, -0.0832349f, -0.54299f, -0.2335f, -0.033801f, -0.11505f, -0.366386f, -0.238099f, -0.0951656f, 0.263106f, 0.129292f, -0.14762f, 0.0700404f, 0.0195349f, -0.286227f, -0.273371f, 0.0587288f, -0.257152f, -0.136248f, -0.13336f, -0.248086f, 0.273973f, -0.302625f, -0.085841f, -0.0839808f, -0.130464f, 0.252972f, -0.0415149f, -0.0695038f, -0.091557f, -0.262375f, -0.0645785f, 0.188566f, -0.202261f, -0.112712f, 0.00631479f, 0.0132917f, -0.0130675f, -0.302285f, 0.0556928f, -0.0211812f, -0.0555546f, 0.0291112f, 0.168815f, 0.143654f, -0.00564186f, -0.0614248f, -0.0939664f, 0.0959667f, -0.209823f, -0.103889f, -0.206011f, -0.0394793f, 0.0545815f, -0.0348762f, -0.132075f, -0.0489917f, -0.177563f, -0.164591f, -0.0174372f, -0.276844f, -0.132214f, -0.236278f, -0.0614254f, -0.230962f, -0.409367f, -0.08959f, 0.182197f, -0.341314f, -0.0645579f, -0.0161434f, -0.166644f, -0.0784324f, -0.387537f, 0.236617f, -0.115318f, -0.11315f, -0.109817f, -0.0949309f, -0.253715f, -0.254404f, -0.0876592f, -0.243118f, -0.219172f, 0.0341202f, 0.0203343f, 0.0435131f, -0.0266338f, 0.140304f, -0.20669f, -0.130739f, 0.0213059f, 0.182793f, -0.0711616f, -0.165651f, -0.212373f, -0.0972764f, -0.284464f, -0.0834676f, -0.129573f, -0.133945f, 0.0684521f, -0.133913f, 0.165726f, -0.176839f, -0.0940447f, -0.145421f, -0.0471074f, 0.00950449f, 0.0308656f, -0.00761046f, -0.19397f, -0.161623f, 0.10975f, -0.0398157f, 0.00168868f, 0.0626417f, -0.118388f, -0.134741f, -0.243707f, 0.146451f, -0.165854f, 0.0585878f, 0.0269307f, 0.163195f, -0.197056f, 0.0438799f, -0.152668f, -0.178631f, -0.167278f, 0.0258257f, -0.22958f, -0.101918f, 0.0360034f, -0.165612f, -0.112482f, -0.419959f, -0.369384f, 0.0468117f, 0.202511f, 0.161559f, 0.0360435f, -0.211843f, 0.0480519f, -0.252478f, -0.0951382f, 0.100791f, -0.379245f, -0.129869f, -0.036501f, 0.0685223f, 0.0247177f, -0.0751386f, -0.12451f, 0.244585f, -0.0103249f, -0.346383f, -0.300614f, 0.230366f, -0.187795f, -0.0326416f, 0.0735751f, -0.0136039f, -0.0219528f, 0.0629145f, -0.0308739f, -0.101514f, -0.169444f, 0.058706f, -0.133274f, -0.200294f, -0.372511f, -0.214898f, -0.184366f, 0.253648f, -0.0362453f, 0.0618937f, 0.0838244f, -0.0386255f, 0.129191f, -0.147435f, -0.180809f, -0.0797491f, -0.286544f, -0.273005f, 0.116222f, -0.255255f, -0.0504643f, -0.0567216f, -0.0204081f, 0.206331f, -0.225266f, -0.211665f, -0.259216f, -0.0676753f, -0.176153f, 0.285802f, -0.00560349f, -0.0253936f, -0.182537f, -0.344487f, -0.341246f, -0.171879f, 0.24462f, 0.015354f, -0.0255803f, -0.0855239f, -0.151488f, -0.0329621f, 0.311794f, 0.0889872f, -0.142655f, -0.00124048f, 0.0175189f, 0.0459686f, 0.279491f, -0.237445f, 0.0570048f, -0.00665275f, -0.0558817f, 0.0731352f, 0.0291331f, 0.0918153f, 0.0276626f, -0.135103f, -0.303909f, 0.0283329f, -0.203482f, -0.0849922f, -0.284485f, -0.214908f, 0.0836636f, -0.219738f, 0.136157f, 0.0332432f, -0.143305f, 0.0283252f, -0.178703f, -0.0742534f, -0.153174f, 0.02235f, -0.0753622f, -0.210102f, -0.0915751f, -0.0189732f, -0.239039f, -0.135349f, -0.104589f, -0.0658414f, -0.183206f, -0.123006f, 0.0835748f, -0.0703047f, -0.207461f, -0.274129f, -0.225327f, -0.113485f, 0.13316f, 0.0295303f, -0.0958281f};
   model->setOperandValue(op84, op84_init, sizeof(float) * 2816);
-  model->addOperation(ANEURALNETWORKS_CONV_2D, {op86, op2, op1, b87, b88, b89, b90}, {op0});
   model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op0, op29, op28, b91, b92, b93, b94, b95}, {op27});
   model->addOperation(ANEURALNETWORKS_CONV_2D, {op27, op32, op31, b96, b97, b98, b99}, {op30});
   model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op30, op35, op34, b100, b101, b102, b103, b104}, {op33});
diff --git a/nn/runtime/test/generated/models/mobilenet_224_gender_basic_fixed_relaxed.model.cpp b/nn/runtime/test/generated/models/mobilenet_224_gender_basic_fixed_relaxed.model.cpp
new file mode 100644
index 0000000..07e3bdb
--- /dev/null
+++ b/nn/runtime/test/generated/models/mobilenet_224_gender_basic_fixed_relaxed.model.cpp
@@ -0,0 +1,674 @@
+// Generated file (from: mobilenet_224_gender_basic_fixed_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::INT32, {});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 1, 1, 11});
+  OperandType type32(Type::TENSOR_FLOAT32, {1, 1, 1, 256});
+  OperandType type3(Type::TENSOR_FLOAT32, {1, 112, 112, 16});
+  OperandType type6(Type::TENSOR_FLOAT32, {1, 14, 14, 128});
+  OperandType type30(Type::TENSOR_FLOAT32, {1, 14, 14, 64});
+  OperandType type1(Type::TENSOR_FLOAT32, {1, 224, 224, 3});
+  OperandType type24(Type::TENSOR_FLOAT32, {1, 28, 28, 32});
+  OperandType type25(Type::TENSOR_FLOAT32, {1, 28, 28, 64});
+  OperandType type8(Type::TENSOR_FLOAT32, {1, 3, 3, 128});
+  OperandType type16(Type::TENSOR_FLOAT32, {1, 3, 3, 16});
+  OperandType type14(Type::TENSOR_FLOAT32, {1, 3, 3, 256});
+  OperandType type22(Type::TENSOR_FLOAT32, {1, 3, 3, 32});
+  OperandType type28(Type::TENSOR_FLOAT32, {1, 3, 3, 64});
+  OperandType type18(Type::TENSOR_FLOAT32, {1, 56, 56, 16});
+  OperandType type19(Type::TENSOR_FLOAT32, {1, 56, 56, 32});
+  OperandType type10(Type::TENSOR_FLOAT32, {1, 7, 7, 128});
+  OperandType type11(Type::TENSOR_FLOAT32, {1, 7, 7, 256});
+  OperandType type34(Type::TENSOR_FLOAT32, {11, 1, 1, 256});
+  OperandType type33(Type::TENSOR_FLOAT32, {11});
+  OperandType type9(Type::TENSOR_FLOAT32, {128, 1, 1, 128});
+  OperandType type31(Type::TENSOR_FLOAT32, {128, 1, 1, 64});
+  OperandType type7(Type::TENSOR_FLOAT32, {128});
+  OperandType type17(Type::TENSOR_FLOAT32, {16, 1, 1, 16});
+  OperandType type5(Type::TENSOR_FLOAT32, {16, 3, 3, 3});
+  OperandType type4(Type::TENSOR_FLOAT32, {16});
+  OperandType type13(Type::TENSOR_FLOAT32, {256, 1, 1, 128});
+  OperandType type15(Type::TENSOR_FLOAT32, {256, 1, 1, 256});
+  OperandType type12(Type::TENSOR_FLOAT32, {256});
+  OperandType type21(Type::TENSOR_FLOAT32, {32, 1, 1, 16});
+  OperandType type23(Type::TENSOR_FLOAT32, {32, 1, 1, 32});
+  OperandType type20(Type::TENSOR_FLOAT32, {32});
+  OperandType type27(Type::TENSOR_FLOAT32, {64, 1, 1, 32});
+  OperandType type29(Type::TENSOR_FLOAT32, {64, 1, 1, 64});
+  OperandType type26(Type::TENSOR_FLOAT32, {64});
+  // Phase 1, operands
+  auto b87 = model->addOperand(&type0);
+  auto b88 = model->addOperand(&type0);
+  auto b89 = model->addOperand(&type0);
+  auto b90 = model->addOperand(&type0);
+  auto b91 = model->addOperand(&type0);
+  auto b92 = model->addOperand(&type0);
+  auto b93 = model->addOperand(&type0);
+  auto b94 = model->addOperand(&type0);
+  auto b95 = model->addOperand(&type0);
+  auto b96 = model->addOperand(&type0);
+  auto b97 = model->addOperand(&type0);
+  auto b98 = model->addOperand(&type0);
+  auto b99 = model->addOperand(&type0);
+  auto b100 = model->addOperand(&type0);
+  auto b101 = model->addOperand(&type0);
+  auto b102 = model->addOperand(&type0);
+  auto b103 = model->addOperand(&type0);
+  auto b104 = model->addOperand(&type0);
+  auto b105 = model->addOperand(&type0);
+  auto b106 = model->addOperand(&type0);
+  auto b107 = model->addOperand(&type0);
+  auto b108 = model->addOperand(&type0);
+  auto b109 = model->addOperand(&type0);
+  auto b110 = model->addOperand(&type0);
+  auto b111 = model->addOperand(&type0);
+  auto b112 = model->addOperand(&type0);
+  auto b113 = model->addOperand(&type0);
+  auto b114 = model->addOperand(&type0);
+  auto b115 = model->addOperand(&type0);
+  auto b116 = model->addOperand(&type0);
+  auto b117 = model->addOperand(&type0);
+  auto b118 = model->addOperand(&type0);
+  auto b119 = model->addOperand(&type0);
+  auto b120 = model->addOperand(&type0);
+  auto b121 = model->addOperand(&type0);
+  auto b122 = model->addOperand(&type0);
+  auto b123 = model->addOperand(&type0);
+  auto b124 = model->addOperand(&type0);
+  auto b125 = model->addOperand(&type0);
+  auto b126 = model->addOperand(&type0);
+  auto b127 = model->addOperand(&type0);
+  auto b128 = model->addOperand(&type0);
+  auto b129 = model->addOperand(&type0);
+  auto b130 = model->addOperand(&type0);
+  auto b131 = model->addOperand(&type0);
+  auto b132 = model->addOperand(&type0);
+  auto b133 = model->addOperand(&type0);
+  auto b134 = model->addOperand(&type0);
+  auto b135 = model->addOperand(&type0);
+  auto b136 = model->addOperand(&type0);
+  auto b137 = model->addOperand(&type0);
+  auto b138 = model->addOperand(&type0);
+  auto b139 = model->addOperand(&type0);
+  auto b140 = model->addOperand(&type0);
+  auto b141 = model->addOperand(&type0);
+  auto b142 = model->addOperand(&type0);
+  auto b143 = model->addOperand(&type0);
+  auto b144 = model->addOperand(&type0);
+  auto b145 = model->addOperand(&type0);
+  auto b146 = model->addOperand(&type0);
+  auto b147 = model->addOperand(&type0);
+  auto b148 = model->addOperand(&type0);
+  auto b149 = model->addOperand(&type0);
+  auto b150 = model->addOperand(&type0);
+  auto b151 = model->addOperand(&type0);
+  auto b152 = model->addOperand(&type0);
+  auto b153 = model->addOperand(&type0);
+  auto b154 = model->addOperand(&type0);
+  auto b155 = model->addOperand(&type0);
+  auto b156 = model->addOperand(&type0);
+  auto b157 = model->addOperand(&type0);
+  auto b158 = model->addOperand(&type0);
+  auto b159 = model->addOperand(&type0);
+  auto b160 = model->addOperand(&type0);
+  auto b161 = model->addOperand(&type0);
+  auto b162 = model->addOperand(&type0);
+  auto b163 = model->addOperand(&type0);
+  auto b164 = model->addOperand(&type0);
+  auto b165 = model->addOperand(&type0);
+  auto b166 = model->addOperand(&type0);
+  auto b167 = model->addOperand(&type0);
+  auto b168 = model->addOperand(&type0);
+  auto b169 = model->addOperand(&type0);
+  auto b170 = model->addOperand(&type0);
+  auto b171 = model->addOperand(&type0);
+  auto b172 = model->addOperand(&type0);
+  auto b173 = model->addOperand(&type0);
+  auto b174 = model->addOperand(&type0);
+  auto b175 = model->addOperand(&type0);
+  auto b176 = model->addOperand(&type0);
+  auto b177 = model->addOperand(&type0);
+  auto b178 = model->addOperand(&type0);
+  auto b179 = model->addOperand(&type0);
+  auto b180 = model->addOperand(&type0);
+  auto b181 = model->addOperand(&type0);
+  auto b182 = model->addOperand(&type0);
+  auto b183 = model->addOperand(&type0);
+  auto b184 = model->addOperand(&type0);
+  auto b185 = model->addOperand(&type0);
+  auto b186 = model->addOperand(&type0);
+  auto b187 = model->addOperand(&type0);
+  auto b188 = model->addOperand(&type0);
+  auto b189 = model->addOperand(&type0);
+  auto b190 = model->addOperand(&type0);
+  auto b191 = model->addOperand(&type0);
+  auto b192 = model->addOperand(&type0);
+  auto b193 = model->addOperand(&type0);
+  auto b194 = model->addOperand(&type0);
+  auto b195 = model->addOperand(&type0);
+  auto b196 = model->addOperand(&type0);
+  auto b197 = model->addOperand(&type0);
+  auto b198 = model->addOperand(&type0);
+  auto b199 = model->addOperand(&type0);
+  auto b200 = model->addOperand(&type0);
+  auto b201 = model->addOperand(&type0);
+  auto b202 = model->addOperand(&type0);
+  auto b203 = model->addOperand(&type0);
+  auto b204 = model->addOperand(&type0);
+  auto b205 = model->addOperand(&type0);
+  auto b206 = model->addOperand(&type0);
+  auto b207 = model->addOperand(&type0);
+  auto b208 = model->addOperand(&type0);
+  auto b209 = model->addOperand(&type0);
+  auto b210 = model->addOperand(&type0);
+  auto b211 = model->addOperand(&type0);
+  auto b212 = model->addOperand(&type0);
+  auto b213 = model->addOperand(&type0);
+  auto b214 = model->addOperand(&type0);
+  auto b215 = model->addOperand(&type0);
+  auto b216 = model->addOperand(&type0);
+  auto b217 = model->addOperand(&type0);
+  auto op86 = model->addOperand(&type1);
+  auto op85 = model->addOperand(&type2);
+  auto op0 = model->addOperand(&type3);
+  auto op1 = model->addOperand(&type4);
+  auto op2 = model->addOperand(&type5);
+  auto op3 = model->addOperand(&type6);
+  auto op4 = model->addOperand(&type7);
+  auto op5 = model->addOperand(&type8);
+  auto op6 = model->addOperand(&type6);
+  auto op7 = model->addOperand(&type7);
+  auto op8 = model->addOperand(&type9);
+  auto op9 = model->addOperand(&type6);
+  auto op10 = model->addOperand(&type7);
+  auto op11 = model->addOperand(&type8);
+  auto op12 = model->addOperand(&type6);
+  auto op13 = model->addOperand(&type7);
+  auto op14 = model->addOperand(&type9);
+  auto op15 = model->addOperand(&type10);
+  auto op16 = model->addOperand(&type7);
+  auto op17 = model->addOperand(&type8);
+  auto op18 = model->addOperand(&type11);
+  auto op19 = model->addOperand(&type12);
+  auto op20 = model->addOperand(&type13);
+  auto op21 = model->addOperand(&type11);
+  auto op22 = model->addOperand(&type12);
+  auto op23 = model->addOperand(&type14);
+  auto op24 = model->addOperand(&type11);
+  auto op25 = model->addOperand(&type12);
+  auto op26 = model->addOperand(&type15);
+  auto op27 = model->addOperand(&type3);
+  auto op28 = model->addOperand(&type4);
+  auto op29 = model->addOperand(&type16);
+  auto op30 = model->addOperand(&type3);
+  auto op31 = model->addOperand(&type4);
+  auto op32 = model->addOperand(&type17);
+  auto op33 = model->addOperand(&type18);
+  auto op34 = model->addOperand(&type4);
+  auto op35 = model->addOperand(&type16);
+  auto op36 = model->addOperand(&type19);
+  auto op37 = model->addOperand(&type20);
+  auto op38 = model->addOperand(&type21);
+  auto op39 = model->addOperand(&type19);
+  auto op40 = model->addOperand(&type20);
+  auto op41 = model->addOperand(&type22);
+  auto op42 = model->addOperand(&type19);
+  auto op43 = model->addOperand(&type20);
+  auto op44 = model->addOperand(&type23);
+  auto op45 = model->addOperand(&type24);
+  auto op46 = model->addOperand(&type20);
+  auto op47 = model->addOperand(&type22);
+  auto op48 = model->addOperand(&type25);
+  auto op49 = model->addOperand(&type26);
+  auto op50 = model->addOperand(&type27);
+  auto op51 = model->addOperand(&type25);
+  auto op52 = model->addOperand(&type26);
+  auto op53 = model->addOperand(&type28);
+  auto op54 = model->addOperand(&type25);
+  auto op55 = model->addOperand(&type26);
+  auto op56 = model->addOperand(&type29);
+  auto op57 = model->addOperand(&type30);
+  auto op58 = model->addOperand(&type26);
+  auto op59 = model->addOperand(&type28);
+  auto op60 = model->addOperand(&type6);
+  auto op61 = model->addOperand(&type7);
+  auto op62 = model->addOperand(&type31);
+  auto op63 = model->addOperand(&type6);
+  auto op64 = model->addOperand(&type7);
+  auto op65 = model->addOperand(&type8);
+  auto op66 = model->addOperand(&type6);
+  auto op67 = model->addOperand(&type7);
+  auto op68 = model->addOperand(&type9);
+  auto op69 = model->addOperand(&type6);
+  auto op70 = model->addOperand(&type7);
+  auto op71 = model->addOperand(&type8);
+  auto op72 = model->addOperand(&type6);
+  auto op73 = model->addOperand(&type7);
+  auto op74 = model->addOperand(&type9);
+  auto op75 = model->addOperand(&type6);
+  auto op76 = model->addOperand(&type7);
+  auto op77 = model->addOperand(&type8);
+  auto op78 = model->addOperand(&type6);
+  auto op79 = model->addOperand(&type7);
+  auto op80 = model->addOperand(&type9);
+  auto op81 = model->addOperand(&type32);
+  auto op82 = model->addOperand(&type2);
+  auto op83 = model->addOperand(&type33);
+  auto op84 = model->addOperand(&type34);
+  // Phase 2, operations
+  static int32_t b87_init[] = {1};
+  model->setOperandValue(b87, b87_init, sizeof(int32_t) * 1);
+  static int32_t b88_init[] = {2};
+  model->setOperandValue(b88, b88_init, sizeof(int32_t) * 1);
+  static int32_t b89_init[] = {2};
+  model->setOperandValue(b89, b89_init, sizeof(int32_t) * 1);
+  static int32_t b90_init[] = {3};
+  model->setOperandValue(b90, b90_init, sizeof(int32_t) * 1);
+  static int32_t b91_init[] = {1};
+  model->setOperandValue(b91, b91_init, sizeof(int32_t) * 1);
+  static int32_t b92_init[] = {1};
+  model->setOperandValue(b92, b92_init, sizeof(int32_t) * 1);
+  static int32_t b93_init[] = {1};
+  model->setOperandValue(b93, b93_init, sizeof(int32_t) * 1);
+  static int32_t b94_init[] = {1};
+  model->setOperandValue(b94, b94_init, sizeof(int32_t) * 1);
+  static int32_t b95_init[] = {3};
+  model->setOperandValue(b95, b95_init, sizeof(int32_t) * 1);
+  static int32_t b96_init[] = {1};
+  model->setOperandValue(b96, b96_init, sizeof(int32_t) * 1);
+  static int32_t b97_init[] = {1};
+  model->setOperandValue(b97, b97_init, sizeof(int32_t) * 1);
+  static int32_t b98_init[] = {1};
+  model->setOperandValue(b98, b98_init, sizeof(int32_t) * 1);
+  static int32_t b99_init[] = {3};
+  model->setOperandValue(b99, b99_init, sizeof(int32_t) * 1);
+  static int32_t b100_init[] = {1};
+  model->setOperandValue(b100, b100_init, sizeof(int32_t) * 1);
+  static int32_t b101_init[] = {2};
+  model->setOperandValue(b101, b101_init, sizeof(int32_t) * 1);
+  static int32_t b102_init[] = {2};
+  model->setOperandValue(b102, b102_init, sizeof(int32_t) * 1);
+  static int32_t b103_init[] = {1};
+  model->setOperandValue(b103, b103_init, sizeof(int32_t) * 1);
+  static int32_t b104_init[] = {3};
+  model->setOperandValue(b104, b104_init, sizeof(int32_t) * 1);
+  static int32_t b105_init[] = {1};
+  model->setOperandValue(b105, b105_init, sizeof(int32_t) * 1);
+  static int32_t b106_init[] = {1};
+  model->setOperandValue(b106, b106_init, sizeof(int32_t) * 1);
+  static int32_t b107_init[] = {1};
+  model->setOperandValue(b107, b107_init, sizeof(int32_t) * 1);
+  static int32_t b108_init[] = {3};
+  model->setOperandValue(b108, b108_init, sizeof(int32_t) * 1);
+  static int32_t b109_init[] = {1};
+  model->setOperandValue(b109, b109_init, sizeof(int32_t) * 1);
+  static int32_t b110_init[] = {1};
+  model->setOperandValue(b110, b110_init, sizeof(int32_t) * 1);
+  static int32_t b111_init[] = {1};
+  model->setOperandValue(b111, b111_init, sizeof(int32_t) * 1);
+  static int32_t b112_init[] = {1};
+  model->setOperandValue(b112, b112_init, sizeof(int32_t) * 1);
+  static int32_t b113_init[] = {3};
+  model->setOperandValue(b113, b113_init, sizeof(int32_t) * 1);
+  static int32_t b114_init[] = {1};
+  model->setOperandValue(b114, b114_init, sizeof(int32_t) * 1);
+  static int32_t b115_init[] = {1};
+  model->setOperandValue(b115, b115_init, sizeof(int32_t) * 1);
+  static int32_t b116_init[] = {1};
+  model->setOperandValue(b116, b116_init, sizeof(int32_t) * 1);
+  static int32_t b117_init[] = {3};
+  model->setOperandValue(b117, b117_init, sizeof(int32_t) * 1);
+  static int32_t b118_init[] = {1};
+  model->setOperandValue(b118, b118_init, sizeof(int32_t) * 1);
+  static int32_t b119_init[] = {2};
+  model->setOperandValue(b119, b119_init, sizeof(int32_t) * 1);
+  static int32_t b120_init[] = {2};
+  model->setOperandValue(b120, b120_init, sizeof(int32_t) * 1);
+  static int32_t b121_init[] = {1};
+  model->setOperandValue(b121, b121_init, sizeof(int32_t) * 1);
+  static int32_t b122_init[] = {3};
+  model->setOperandValue(b122, b122_init, sizeof(int32_t) * 1);
+  static int32_t b123_init[] = {1};
+  model->setOperandValue(b123, b123_init, sizeof(int32_t) * 1);
+  static int32_t b124_init[] = {1};
+  model->setOperandValue(b124, b124_init, sizeof(int32_t) * 1);
+  static int32_t b125_init[] = {1};
+  model->setOperandValue(b125, b125_init, sizeof(int32_t) * 1);
+  static int32_t b126_init[] = {3};
+  model->setOperandValue(b126, b126_init, sizeof(int32_t) * 1);
+  static int32_t b127_init[] = {1};
+  model->setOperandValue(b127, b127_init, sizeof(int32_t) * 1);
+  static int32_t b128_init[] = {1};
+  model->setOperandValue(b128, b128_init, sizeof(int32_t) * 1);
+  static int32_t b129_init[] = {1};
+  model->setOperandValue(b129, b129_init, sizeof(int32_t) * 1);
+  static int32_t b130_init[] = {1};
+  model->setOperandValue(b130, b130_init, sizeof(int32_t) * 1);
+  static int32_t b131_init[] = {3};
+  model->setOperandValue(b131, b131_init, sizeof(int32_t) * 1);
+  static int32_t b132_init[] = {1};
+  model->setOperandValue(b132, b132_init, sizeof(int32_t) * 1);
+  static int32_t b133_init[] = {1};
+  model->setOperandValue(b133, b133_init, sizeof(int32_t) * 1);
+  static int32_t b134_init[] = {1};
+  model->setOperandValue(b134, b134_init, sizeof(int32_t) * 1);
+  static int32_t b135_init[] = {3};
+  model->setOperandValue(b135, b135_init, sizeof(int32_t) * 1);
+  static int32_t b136_init[] = {1};
+  model->setOperandValue(b136, b136_init, sizeof(int32_t) * 1);
+  static int32_t b137_init[] = {2};
+  model->setOperandValue(b137, b137_init, sizeof(int32_t) * 1);
+  static int32_t b138_init[] = {2};
+  model->setOperandValue(b138, b138_init, sizeof(int32_t) * 1);
+  static int32_t b139_init[] = {1};
+  model->setOperandValue(b139, b139_init, sizeof(int32_t) * 1);
+  static int32_t b140_init[] = {3};
+  model->setOperandValue(b140, b140_init, sizeof(int32_t) * 1);
+  static int32_t b141_init[] = {1};
+  model->setOperandValue(b141, b141_init, sizeof(int32_t) * 1);
+  static int32_t b142_init[] = {1};
+  model->setOperandValue(b142, b142_init, sizeof(int32_t) * 1);
+  static int32_t b143_init[] = {1};
+  model->setOperandValue(b143, b143_init, sizeof(int32_t) * 1);
+  static int32_t b144_init[] = {3};
+  model->setOperandValue(b144, b144_init, sizeof(int32_t) * 1);
+  static int32_t b145_init[] = {1};
+  model->setOperandValue(b145, b145_init, sizeof(int32_t) * 1);
+  static int32_t b146_init[] = {1};
+  model->setOperandValue(b146, b146_init, sizeof(int32_t) * 1);
+  static int32_t b147_init[] = {1};
+  model->setOperandValue(b147, b147_init, sizeof(int32_t) * 1);
+  static int32_t b148_init[] = {1};
+  model->setOperandValue(b148, b148_init, sizeof(int32_t) * 1);
+  static int32_t b149_init[] = {3};
+  model->setOperandValue(b149, b149_init, sizeof(int32_t) * 1);
+  static int32_t b150_init[] = {1};
+  model->setOperandValue(b150, b150_init, sizeof(int32_t) * 1);
+  static int32_t b151_init[] = {1};
+  model->setOperandValue(b151, b151_init, sizeof(int32_t) * 1);
+  static int32_t b152_init[] = {1};
+  model->setOperandValue(b152, b152_init, sizeof(int32_t) * 1);
+  static int32_t b153_init[] = {3};
+  model->setOperandValue(b153, b153_init, sizeof(int32_t) * 1);
+  static int32_t b154_init[] = {1};
+  model->setOperandValue(b154, b154_init, sizeof(int32_t) * 1);
+  static int32_t b155_init[] = {1};
+  model->setOperandValue(b155, b155_init, sizeof(int32_t) * 1);
+  static int32_t b156_init[] = {1};
+  model->setOperandValue(b156, b156_init, sizeof(int32_t) * 1);
+  static int32_t b157_init[] = {1};
+  model->setOperandValue(b157, b157_init, sizeof(int32_t) * 1);
+  static int32_t b158_init[] = {3};
+  model->setOperandValue(b158, b158_init, sizeof(int32_t) * 1);
+  static int32_t b159_init[] = {1};
+  model->setOperandValue(b159, b159_init, sizeof(int32_t) * 1);
+  static int32_t b160_init[] = {1};
+  model->setOperandValue(b160, b160_init, sizeof(int32_t) * 1);
+  static int32_t b161_init[] = {1};
+  model->setOperandValue(b161, b161_init, sizeof(int32_t) * 1);
+  static int32_t b162_init[] = {3};
+  model->setOperandValue(b162, b162_init, sizeof(int32_t) * 1);
+  static int32_t b163_init[] = {1};
+  model->setOperandValue(b163, b163_init, sizeof(int32_t) * 1);
+  static int32_t b164_init[] = {1};
+  model->setOperandValue(b164, b164_init, sizeof(int32_t) * 1);
+  static int32_t b165_init[] = {1};
+  model->setOperandValue(b165, b165_init, sizeof(int32_t) * 1);
+  static int32_t b166_init[] = {1};
+  model->setOperandValue(b166, b166_init, sizeof(int32_t) * 1);
+  static int32_t b167_init[] = {3};
+  model->setOperandValue(b167, b167_init, sizeof(int32_t) * 1);
+  static int32_t b168_init[] = {1};
+  model->setOperandValue(b168, b168_init, sizeof(int32_t) * 1);
+  static int32_t b169_init[] = {1};
+  model->setOperandValue(b169, b169_init, sizeof(int32_t) * 1);
+  static int32_t b170_init[] = {1};
+  model->setOperandValue(b170, b170_init, sizeof(int32_t) * 1);
+  static int32_t b171_init[] = {3};
+  model->setOperandValue(b171, b171_init, sizeof(int32_t) * 1);
+  static int32_t b172_init[] = {1};
+  model->setOperandValue(b172, b172_init, sizeof(int32_t) * 1);
+  static int32_t b173_init[] = {1};
+  model->setOperandValue(b173, b173_init, sizeof(int32_t) * 1);
+  static int32_t b174_init[] = {1};
+  model->setOperandValue(b174, b174_init, sizeof(int32_t) * 1);
+  static int32_t b175_init[] = {1};
+  model->setOperandValue(b175, b175_init, sizeof(int32_t) * 1);
+  static int32_t b176_init[] = {3};
+  model->setOperandValue(b176, b176_init, sizeof(int32_t) * 1);
+  static int32_t b177_init[] = {1};
+  model->setOperandValue(b177, b177_init, sizeof(int32_t) * 1);
+  static int32_t b178_init[] = {1};
+  model->setOperandValue(b178, b178_init, sizeof(int32_t) * 1);
+  static int32_t b179_init[] = {1};
+  model->setOperandValue(b179, b179_init, sizeof(int32_t) * 1);
+  static int32_t b180_init[] = {3};
+  model->setOperandValue(b180, b180_init, sizeof(int32_t) * 1);
+  static int32_t b181_init[] = {1};
+  model->setOperandValue(b181, b181_init, sizeof(int32_t) * 1);
+  static int32_t b182_init[] = {1};
+  model->setOperandValue(b182, b182_init, sizeof(int32_t) * 1);
+  static int32_t b183_init[] = {1};
+  model->setOperandValue(b183, b183_init, sizeof(int32_t) * 1);
+  static int32_t b184_init[] = {1};
+  model->setOperandValue(b184, b184_init, sizeof(int32_t) * 1);
+  static int32_t b185_init[] = {3};
+  model->setOperandValue(b185, b185_init, sizeof(int32_t) * 1);
+  static int32_t b186_init[] = {1};
+  model->setOperandValue(b186, b186_init, sizeof(int32_t) * 1);
+  static int32_t b187_init[] = {1};
+  model->setOperandValue(b187, b187_init, sizeof(int32_t) * 1);
+  static int32_t b188_init[] = {1};
+  model->setOperandValue(b188, b188_init, sizeof(int32_t) * 1);
+  static int32_t b189_init[] = {3};
+  model->setOperandValue(b189, b189_init, sizeof(int32_t) * 1);
+  static int32_t b190_init[] = {1};
+  model->setOperandValue(b190, b190_init, sizeof(int32_t) * 1);
+  static int32_t b191_init[] = {2};
+  model->setOperandValue(b191, b191_init, sizeof(int32_t) * 1);
+  static int32_t b192_init[] = {2};
+  model->setOperandValue(b192, b192_init, sizeof(int32_t) * 1);
+  static int32_t b193_init[] = {1};
+  model->setOperandValue(b193, b193_init, sizeof(int32_t) * 1);
+  static int32_t b194_init[] = {3};
+  model->setOperandValue(b194, b194_init, sizeof(int32_t) * 1);
+  static int32_t b195_init[] = {1};
+  model->setOperandValue(b195, b195_init, sizeof(int32_t) * 1);
+  static int32_t b196_init[] = {1};
+  model->setOperandValue(b196, b196_init, sizeof(int32_t) * 1);
+  static int32_t b197_init[] = {1};
+  model->setOperandValue(b197, b197_init, sizeof(int32_t) * 1);
+  static int32_t b198_init[] = {3};
+  model->setOperandValue(b198, b198_init, sizeof(int32_t) * 1);
+  static int32_t b199_init[] = {1};
+  model->setOperandValue(b199, b199_init, sizeof(int32_t) * 1);
+  static int32_t b200_init[] = {1};
+  model->setOperandValue(b200, b200_init, sizeof(int32_t) * 1);
+  static int32_t b201_init[] = {1};
+  model->setOperandValue(b201, b201_init, sizeof(int32_t) * 1);
+  static int32_t b202_init[] = {1};
+  model->setOperandValue(b202, b202_init, sizeof(int32_t) * 1);
+  static int32_t b203_init[] = {3};
+  model->setOperandValue(b203, b203_init, sizeof(int32_t) * 1);
+  static int32_t b204_init[] = {1};
+  model->setOperandValue(b204, b204_init, sizeof(int32_t) * 1);
+  static int32_t b205_init[] = {1};
+  model->setOperandValue(b205, b205_init, sizeof(int32_t) * 1);
+  static int32_t b206_init[] = {1};
+  model->setOperandValue(b206, b206_init, sizeof(int32_t) * 1);
+  static int32_t b207_init[] = {3};
+  model->setOperandValue(b207, b207_init, sizeof(int32_t) * 1);
+  static int32_t b208_init[] = {2};
+  model->setOperandValue(b208, b208_init, sizeof(int32_t) * 1);
+  static int32_t b209_init[] = {2};
+  model->setOperandValue(b209, b209_init, sizeof(int32_t) * 1);
+  static int32_t b210_init[] = {2};
+  model->setOperandValue(b210, b210_init, sizeof(int32_t) * 1);
+  static int32_t b211_init[] = {7};
+  model->setOperandValue(b211, b211_init, sizeof(int32_t) * 1);
+  static int32_t b212_init[] = {7};
+  model->setOperandValue(b212, b212_init, sizeof(int32_t) * 1);
+  static int32_t b213_init[] = {0};
+  model->setOperandValue(b213, b213_init, sizeof(int32_t) * 1);
+  static int32_t b214_init[] = {1};
+  model->setOperandValue(b214, b214_init, sizeof(int32_t) * 1);
+  static int32_t b215_init[] = {1};
+  model->setOperandValue(b215, b215_init, sizeof(int32_t) * 1);
+  static int32_t b216_init[] = {1};
+  model->setOperandValue(b216, b216_init, sizeof(int32_t) * 1);
+  static int32_t b217_init[] = {0};
+  model->setOperandValue(b217, b217_init, sizeof(int32_t) * 1);
+  static float op1_init[] = {0.247857f, 0.75021f, 0.741359f, 1.36951f, -0.799518f, 0.835508f, 1.00795f, 0.758906f, 0.872059f, -0.442585f, -0.724606f, 0.347115f, 0.0888976f, 0.718811f, 1.06249f, -0.285038f};
+  model->setOperandValue(op1, op1_init, sizeof(float) * 16);
+  static float op2_init[] = {0.652068f, -0.440708f, -0.370313f, 0.0371835f, -0.200534f, 0.187246f, 0.608945f, 0.0446021f, -0.328933f, 0.608707f, -0.458118f, -0.338548f, 0.544501f, -0.100406f, -0.552947f, 0.264365f, 0.00542196f, -0.236679f, 0.00718806f, -0.39411f, 0.566754f, -0.0512145f, -0.355038f, 0.474691f, -0.0822169f, -0.646847f, 0.576151f, -0.0225515f, -0.311586f, 0.520931f, 0.0131213f, -0.0204246f, 0.122719f, 0.0407416f, -0.00254109f, -0.169118f, -0.733753f, 0.488922f, 0.210584f, 0.529329f, 0.35191f, -0.070027f, 0.939339f, 0.246604f, 0.309091f, -0.772781f, -0.0317189f, 0.184809f, 0.217716f, 0.123726f, -0.581245f, 0.753962f, -0.237803f, -0.534238f, 0.066889f, 0.205891f, 0.0796765f, -0.0730868f, 0.247787f, -0.0795177f, -0.153247f, -0.141179f, -0.107013f, 0.347468f, 0.159756f, 0.202276f, 0.333447f, 0.282742f, 0.174085f, 0.0931139f, -0.0784908f, 0.124231f, -0.0355699f, -0.0750061f, -0.0602844f, 0.153779f, 0.190586f, -0.0436086f, 0.127754f, -0.0132479f, -0.0590352f, -0.236779f, 0.100819f, 0.0578522f, -0.110667f, 0.0517516f, 0.28305f, -0.36037f, -0.0109951f, 0.258977f, -0.171027f, 0.182065f, 0.342808f, -0.0865413f, -0.120913f, 0.0876433f, -0.321358f, 0.182235f, 0.182115f, -0.102917f, 0.124579f, 0.266657f, -0.107564f, -0.0623865f, 0.107621f, -0.404334f, 0.0282603f, 0.331853f, -0.0646019f, -0.0455715f, -0.217516f, -0.0037875f, -0.235336f, -0.0671481f, 0.0357478f, -0.0844078f, 0.0935384f, -0.0619307f, -0.0631019f, 0.0568289f, -0.165787f, -0.147547f, -0.12507f, -0.16594f, -0.131169f, -0.0705661f, -0.0969777f, 0.0446729f, 0.245831f, 0.016168f, -0.0636066f, 0.00757261f, -0.241471f, -0.201184f, 0.0612182f, -0.235653f, -0.0647185f, -0.266401f, 0.140807f, 0.253679f, 0.201186f, 0.376029f, 0.55602f, 0.0176408f, -0.34448f, -0.105594f, -0.0830195f, -0.073044f, 0.332442f, 0.189069f, 0.579356f, 0.500409f, 0.081007f, 0.0224194f, -0.418452f, 0.117647f, 0.102363f, -0.308967f, -0.130247f, 0.0744453f, 0.0937165f, 0.129678f, -0.206706f, 0.355731f, -0.183979f, 0.0930233f, 0.376961f, -0.496447f, 0.0753673f, 0.550546f, -0.530313f, -0.119834f, 0.633561f, -0.350414f, 0.17257f, 0.363476f, -0.326057f, -0.117922f, 0.439519f, -0.361867f, -0.587992f, 0.540487f, -0.0493363f, -0.423359f, 0.39267f, -0.0985205f, -0.361801f, 0.406216f, 0.312372f, 0.19384f, 0.38476f, 0.0793438f, -0.0243019f, 0.0973445f, 0.34309f, -0.336955f, 0.047901f, -0.142791f, 0.111938f, -0.0117197f, -0.140463f, 0.134465f, 0.238205f, 0.133603f, 0.28098f, -0.0365245f, 0.0201062f, 0.0713887f, -0.201147f, -0.352104f, 0.122226f, -0.092246f, 0.159098f, 0.282097f, 0.418289f, -0.108599f, -0.294907f, -0.46983f, -0.238307f, -0.442626f, -0.572947f, -0.247161f, 0.0933571f, -0.387562f, -0.0395712f, -0.0761291f, -0.0795069f, 0.228746f, -0.110803f, 0.041032f, -0.00155868f, -0.0828624f, -0.224932f, 0.0649534f, 0.307345f, 0.528949f, -0.0949103f, 0.390639f, 0.54659f, 0.404815f, 0.342257f, 0.489076f, -0.121948f, 0.530045f, -0.476237f, -0.529727f, 0.262048f, -0.0304337f, -0.117802f, -0.0623434f, -0.00425207f, -0.238349f, -0.113178f, -0.259427f, -0.202885f, -0.600946f, -0.225316f, -0.0887756f, -0.29406f, -0.0257875f, 0.129552f, 0.600505f, 0.195343f, 0.693125f, -0.417967f, -0.359057f, 0.428299f, -0.633522f, -0.0536405f, -0.0580457f, -0.237309f, -0.267921f, -0.0486694f, -0.192913f, -0.344927f, -0.085713f, 0.0203166f, 0.0355307f, 0.270309f, 0.0918823f, -0.010063f, -0.135408f, -0.141108f, -0.496817f, -0.290794f, 0.224278f, -0.249464f, -0.0518539f, 0.0756295f, 0.171187f, 0.182209f, -0.195592f, 0.0958233f, -0.0921988f, -0.367889f, 0.134003f, 0.0687944f, 0.308343f, -0.0118914f, 0.331651f, -0.430663f, 0.706435f, 0.141785f, -0.554641f, 0.588355f, -0.750443f, -0.669483f, -0.996132f, -0.457539f, 0.493816f, -0.817835f, 0.120477f, 0.303217f, 0.46568f, 0.630415f, -0.92812f, -0.261296f, -0.702809f, -0.383505f, -0.48721f, 0.299454f, 1.24191f, 0.41616f, 0.162217f, 0.296053f, 0.251336f, 0.0753915f, 0.0408618f, -0.108743f, -0.0320105f, -0.296446f, -0.22903f, 0.277229f, -0.0633153f, 0.121183f, -0.0197022f, -0.284926f, -0.35553f, -0.0807346f, -0.334026f, -0.584447f, -0.200952f, 0.274273f, 0.255205f, 0.298184f, 0.135537f, 0.128646f, -0.0911873f, -0.345975f, -0.51712f, -0.331822f, 0.541729f, 0.790656f, -0.363103f, 0.9478f, 1.07197f, 0.00359358f, -0.397684f, -0.204973f, -0.592952f, 1.0766f, 0.92906f, 0.670814f, -0.0147435f, 0.112532f, 0.0736042f, -1.07179f, -1.08754f, -0.629355f, 0.68915f, 0.12786f, 0.522442f, -0.973202f, -0.867001f, 0.019969f, -0.654796f, -0.849004f, 0.197318f, -0.0344764f, 0.0267163f, -0.0116256f, 0.00203475f, 0.0356207f, 0.000402505f, -0.0853754f, 0.100378f, 0.0482042f, -0.0503914f, 0.0231722f, -0.00244786f, -0.033307f, 0.0556787f, -0.0229831f, -0.0586009f, 0.0728227f, 0.0432203f, 0.0261995f, 0.0298879f, -0.0300803f, -0.0232209f, 0.0302866f, -0.0522305f, -0.0859193f, 0.0553994f, -0.0223054f, 0.0875387f, -0.0641483f, -0.0985766f, -0.300987f, -0.185793f, 0.0301473f, -0.171482f, -0.0271402f, 0.0324297f, -0.104419f, -0.0167332f, -0.201047f, -0.012749f, -0.414162f, 0.0129281f, -0.126695f, -0.177922f, -0.158758f, 0.109131f, 0.15325f, 0.279018f, -0.144136f, -0.247177f, 0.166079f, -0.247908f, -0.251021f, 0.136724f};
+  model->setOperandValue(op2, op2_init, sizeof(float) * 432);
+  static float op4_init[] = {-0.604559f, 0.937928f, -0.974893f, -0.53343f, 1.28805f, 1.10148f, -0.0531712f, 0.645655f, -0.739696f, 0.761929f, -0.768367f, 0.947203f, -0.0259644f, -0.0806925f, 0.826225f, 0.0647016f, 1.1949f, -0.590577f, -0.48047f, 1.0571f, -0.531508f, -0.145154f, -0.85109f, -0.428907f, -0.990977f, -0.21766f, -0.831976f, 0.807643f, -0.883484f, -0.101848f, -0.633951f, -0.934549f, -0.637571f, 0.917919f, -0.616174f, 0.638678f, -0.522414f, 0.164932f, 0.735401f, 0.388233f, -0.54634f, 0.663964f, -0.714432f, -0.770424f, -0.506502f, -0.00663996f, 1.20178f, -0.658902f, 0.202565f, -0.772786f, -0.908852f, -0.753642f, 0.299485f, -0.64437f, -0.258062f, -0.647217f, 1.16684f, -0.601416f, -0.581131f, -0.604002f, 0.303339f, 0.99038f, -0.252728f, 0.835258f, -0.479581f, 1.05239f, 0.0875528f, 0.436033f, 1.14433f, -0.755638f, 1.2817f, -0.110367f, -0.055392f, -0.327483f, 0.960676f, -0.268293f, 0.632768f, -0.77256f, -0.821636f, 0.0321576f, 0.777652f, -0.50267f, 0.998972f, 0.684318f, -0.592786f, -0.105259f, -0.183601f, -0.83277f, -0.584282f, -0.548963f, -0.186272f, -0.573955f, 0.637204f, -0.455254f, -0.0298786f, 0.0313744f, -0.835853f, 1.1131f, 1.13073f, -0.527641f, 0.6035f, 1.09069f, -0.727978f, -0.957797f, 0.795879f, 0.0702782f, 0.992534f, 0.447629f, 1.15544f, 1.02855f, -0.760967f, -0.552526f, 1.16415f, -0.720886f, -0.704716f, -0.918078f, -0.495209f, 0.79913f, -0.579286f, 1.12242f, 1.24057f, 0.868452f, 0.422623f, 1.26555f, -0.85856f, 0.536015f, 0.277351f, -0.375872f};
+  model->setOperandValue(op4, op4_init, sizeof(float) * 128);
+  static float op5_init[] = {-0.371999f, -0.346798f, 0.0479857f, 0.357291f, 0.0781941f, -0.468469f, -0.189905f, -0.330524f, 0.149986f, -0.160447f, -0.0118703f, -0.550328f, -0.791003f, 0.40966f, -0.504578f, -0.59432f, -0.388201f, 0.599258f, 0.765913f, 0.0550903f, 0.687241f, 0.416152f, 0.45043f, 0.799941f, 0.183287f, -0.0806467f, 0.40882f, 0.038171f, 0.623295f, 0.334548f, -0.0286598f, 0.625486f, -0.0592684f, -0.44542f, 0.877997f, -0.37489f, 0.0650874f, 0.523281f, -0.299677f, -0.547368f, -0.273818f, 0.507475f, 0.0302324f, 0.628441f, 0.00878996f, 0.106071f, -0.590101f, 0.00397916f, 0.74002f, 0.656696f, 0.610534f, 0.469231f, 0.788127f, -0.0209616f, 0.695851f, -0.258907f, -0.104862f, 0.419681f, 0.288236f, 0.614652f, 0.567888f, 0.144987f, 0.180178f, 0.0734783f, 0.322781f, -0.568792f, 0.724734f, 0.733f, -0.118631f, -0.267416f, -0.560893f, 1.09369f, -0.33351f, -0.177277f, 0.451596f, -0.409597f, 0.758123f, -0.107428f, 0.446403f, -0.339231f, 0.715291f, 0.726725f, 0.104168f, 0.113386f, 0.801029f, -0.49758f, -0.403269f, 0.104698f, 0.390301f, 0.0562365f, -0.660356f, 0.726264f, -0.382822f, -0.502128f, 0.373597f, -0.327868f, -0.140265f, -0.263564f, -0.00081655f, -0.205775f, -0.216874f, -0.287382f, 0.754078f, 0.568083f, -0.580143f, -0.797676f, -0.193579f, -0.0638705f, -0.42645f, -0.218093f, 0.131062f, 0.366589f, -0.318487f, 0.400512f, 0.0918075f, 0.219986f, -0.191933f, -0.695975f, 0.376914f, -0.629351f, -0.305271f, -0.273703f, -0.539896f, -0.24429f, 0.738327f, -0.0349007f, -0.588518f, 0.656455f, 0.210178f, -0.410348f, -0.0931675f, 0.140479f, -0.455182f, -0.267616f, -0.319923f, -0.409643f, 0.288601f, -0.285263f, 0.194517f, 0.144924f, -0.52604f, 0.517934f, -0.158135f, -0.375607f, -0.417484f, 0.654575f, 0.209492f, -0.630293f, 0.152386f, 0.727502f, 0.418395f, 0.877609f, 0.213141f, -0.608543f, 0.141474f, -0.394892f, 0.584262f, 0.163144f, -0.145766f, 0.297692f, -0.126787f, -0.375714f, 0.374215f, -0.435386f, 0.489997f, 0.967364f, -0.518685f, -0.0186661f, -0.199576f, -1.02716f, 0.0914696f, -0.293028f, -0.342356f, 0.253988f, -0.345911f, -0.0787308f, 0.893786f, 0.0658312f, 0.328602f, 0.471665f, -0.454748f, 0.4051f, 0.42156f, -0.0440271f, -0.250534f, 0.309111f, 0.495076f, 0.453569f, 0.55799f, -0.0140493f, 0.52114f, 0.0349987f, 0.703054f, -0.387149f, 0.105532f, 0.0556309f, -0.403943f, 0.224924f, -0.602211f, -0.126065f, -0.189629f, -0.324051f, 0.0385442f, 0.142331f, 0.399993f, 0.541429f, 0.099055f, -0.748623f, 0.108785f, 0.604047f, -0.0259912f, -0.450731f, 0.310894f, -0.301575f, -0.302417f, -0.35221f, 0.0479682f, -0.168233f, 0.00968778f, -0.263735f, -0.248705f, 0.0826444f, 0.696327f, -0.232563f, 0.281257f, -0.243034f, -0.977377f, 0.260563f, -0.184195f, -0.81334f, 0.385865f, 0.130855f, -0.0985384f, 1.04408f, -0.425736f, -0.299794f, -0.324138f, 0.0633125f, -0.0375996f, 0.241082f, 0.00295235f, 0.132798f, 0.126659f, -0.218771f, -0.058806f, 0.0403471f, 0.665479f, 0.291473f, -0.42599f, 0.238544f, 0.0194395f, -0.464092f, 0.206833f, -0.320888f, -0.408994f, 0.252735f, -0.190033f, 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-0.361545f, -0.0891978f, 0.671198f, 0.142142f, -0.352542f, -0.233065f, 0.257493f, -0.0495003f, -0.191727f, -0.0484265f, 0.482953f, 0.193174f, -0.528268f, -0.246402f, -0.000374761f, -0.0302073f, 0.0310964f, -0.213433f, -0.460854f, -0.481105f, -0.60283f, 0.434087f, 0.142084f, 0.705319f, -0.171898f, -0.0783328f, -0.198899f, -0.469111f, -0.513186f, 0.258557f, -0.493187f, 0.157313f, 0.250994f, 0.220334f, 0.0393204f};
+  model->setOperandValue(op5, op5_init, sizeof(float) * 1152);
+  static float op7_init[] = {-0.239844f, 0.432217f, -0.153807f, 0.0767933f, -0.275068f, 0.0063897f, 0.0516512f, 0.422338f, 0.0895534f, -0.416501f, 0.240182f, 0.0289379f, 0.302629f, -0.0327263f, -0.580243f, 0.86227f, 0.517094f, -0.23759f, 0.536654f, 0.597244f, 0.667096f, -0.507551f, -0.255663f, 0.61003f, 0.976404f, 0.232841f, 0.358804f, 0.348653f, 0.47637f, 0.230082f, 0.458516f, -0.664486f, -0.279672f, 0.192337f, -0.179005f, 0.656821f, -1.05123f, 0.0301599f, -0.677498f, -0.646811f, 0.100461f, 0.898003f, 0.12403f, 1.04799f, 0.960812f, -0.00393687f, -0.175513f, 0.242039f, 0.163904f, -0.022697f, 0.296417f, 0.225485f, 0.650953f, 0.257254f, 0.358139f, -0.39075f, 0.627265f, 0.0965187f, -0.232091f, -0.25681f, 0.651693f, 0.631126f, 0.499249f, 0.956892f, 0.710567f, -0.384283f, 0.920582f, 0.525813f, 0.0432827f, 0.0850359f, 1.35225f, -0.463563f, -0.61526f, 1.34561f, 2.03387f, -1.1429f, 0.108398f, 0.14919f, 0.387328f, 0.335212f, -0.33643f, 0.481889f, 0.742792f, 0.416105f, 0.267452f, 1.12879f, -0.692795f, -0.116663f, -0.651768f, 0.815917f, 0.150634f, -1.101f, -0.0903521f, 0.642167f, 0.636696f, 0.31574f, -0.432929f, 0.332695f, 0.571667f, -0.927278f, -0.330166f, 0.728891f, 0.120788f, 0.798598f, 0.215431f, 0.672161f, -0.256499f, -0.0800854f, 0.435699f, 0.64343f, -0.333017f, 0.271489f, 0.429805f, 0.21972f, 0.286028f, -0.512005f, -0.14715f, -0.265395f, 0.543187f, -0.288313f, 0.233415f, 0.571179f, -0.218133f, 0.990613f, 0.0603392f, 0.353106f, 0.610102f, 0.899427f};
+  model->setOperandValue(op7, op7_init, sizeof(float) * 128);
+  static float op8_init[] = {-0.172699f, 0.0449607f, -0.00371321f, 0.0898063f, -0.0704206f, -0.0275239f, 0.041895f, -0.00635676f, -0.0417219f, -0.0280383f, -0.173593f, 0.135424f, -0.0752411f, 0.11462f, -0.124894f, 0.000502583f, -0.216759f, -0.0630591f, -0.110061f, 0.12233f, -0.0932574f, -0.161026f, 0.186579f, 0.130671f, -0.0936801f, -0.0569374f, 0.357974f, 0.0954326f, 0.101225f, -0.0409947f, -0.0455288f, -0.0440348f, 0.123336f, 0.0231551f, -0.0408172f, -0.00361653f, -0.00148246f, 0.119164f, 0.0527698f, 0.0506977f, 0.256418f, -0.0326844f, -0.0874518f, 0.067015f, -0.0604058f, 0.0366124f, 0.00296697f, 0.116773f, 0.218754f, 0.00682259f, 0.126256f, -0.142779f, -0.0523525f, -0.0846195f, 0.117748f, 0.0111739f, -0.0813845f, 0.089366f, -0.0741314f, 0.0120595f, 0.021114f, 0.0707698f, -0.0105984f, 0.0755084f, 0.12208f, 0.0323274f, 0.0109762f, 0.0425386f, 0.0567808f, -0.0683524f, 0.0843128f, 0.0345055f, -0.057605f, 0.0924838f, 0.088714f, 0.0128912f, 0.00135126f, -0.101799f, 0.0929571f, 0.111422f, 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0.0106403f, -0.0544982f, -0.154347f, 0.112921f, -0.0589115f, -0.157886f, 0.035458f, 0.106848f, 0.0371984f, 0.0239643f, 0.0421104f, -0.0259203f, 0.180176f, -0.212496f, -0.0366865f, -0.0723261f, 0.031068f, -0.0449782f, -0.115249f, -0.176421f, 0.128785f, 0.0496948f, 0.000222186f, -0.0294286f, -0.0897237f, 0.00569609f, 0.116698f, 0.285006f, -0.156228f, 0.127624f, 0.148411f, 0.0609212f, -0.135154f, -0.00909233f, 0.147309f, -0.169101f, -0.0343822f, 0.0851516f, -0.133019f, 0.201457f, -0.130316f, -0.104724f, 0.177934f, -0.0438326f, -0.372659f, 0.0286109f, -0.000941961f, -0.14556f, 0.0897591f, 0.231051f, -0.0873842f, 0.0141118f, -0.0139249f, -0.0289038f, 0.138774f, -0.0571027f, -0.0705663f, -0.01782f, -0.0442669f, -0.11826f};
+  model->setOperandValue(op8, op8_init, sizeof(float) * 16384);
+  static float op10_init[] = {0.870905f, 0.732366f, -0.669046f, 1.08174f, 0.916159f, -0.294452f, 0.592262f, 0.301429f, -0.422655f, -0.625296f, -0.536564f, -0.667137f, -0.583286f, -0.72358f, -0.568471f, -0.57524f, -0.62291f, -0.911421f, -0.501374f, -0.00290018f, -0.878221f, -0.051163f, -0.74821f, 0.888223f, 0.813446f, 0.55647f, -0.622013f, 0.836827f, 0.841449f, -0.816436f, -0.759883f, -0.658268f, -0.625168f, 0.871381f, -0.78675f, -0.608052f, -0.0327976f, -0.379691f, -0.654795f, -0.0660218f, -0.676479f, -0.664595f, 0.265069f, -0.625888f, 0.169051f, -0.675591f, 0.299855f, -0.703214f, -0.134523f, -0.59296f, 0.937484f, -0.710908f, 0.845609f, -0.475655f, -0.636727f, 0.533551f, 0.124115f, 0.695435f, 0.879939f, -0.377836f, -0.816544f, 0.277795f, -0.607381f, -0.656329f, -0.667769f, 1.03546f, -0.725715f, -0.620013f, -0.527745f, -0.646767f, -0.275308f, -0.620535f, -0.637898f, -0.210308f, 1.20405f, 0.595138f, 0.794743f, 0.230801f, -0.840184f, -0.533846f, 0.487095f, -0.708161f, -0.744136f, -0.818685f, 1.0441f, -0.865297f, -0.666535f, 0.501392f, 0.186682f, -0.305148f, 0.56623f, 0.904152f, 0.799276f, 0.318903f, -0.21392f, -0.759348f, 1.00587f, -0.924452f, -0.69364f, 0.775983f, 0.740833f, -1.03741f, 0.567915f, -0.742716f, -0.793044f, 1.04104f, 1.06893f, -0.932649f, -0.672023f, -0.674185f, -0.697389f, 0.243591f, -0.875875f, -0.175759f, 0.0657881f, 0.764382f, 0.616322f, 0.697396f, -0.48311f, -0.592917f, -0.368845f, 1.1508f, -0.615879f, 1.07167f, 0.983414f, -0.53735f, 0.828645f, -0.713031f};
+  model->setOperandValue(op10, op10_init, sizeof(float) * 128);
+  static float op11_init[] = {-0.0338548f, -0.209956f, 0.299f, -0.587087f, -0.155182f, -0.215745f, -0.457096f, 0.354364f, -0.0881957f, 0.448084f, 0.448586f, 0.265426f, -0.588544f, 0.100833f, 0.472292f, 0.884849f, 0.231727f, 0.277485f, -0.347502f, 0.294058f, 0.429232f, 0.856874f, 0.414706f, -0.696934f, 0.0382086f, -0.235027f, -0.208378f, -0.267724f, -0.500691f, 0.574836f, 0.0970658f, 0.392687f, -0.180284f, -0.126758f, -0.357164f, 0.569162f, 0.53462f, 0.83247f, -0.139077f, 0.291479f, 0.201703f, -0.0439143f, 0.560568f, -0.288697f, 0.579956f, 0.462056f, 0.707969f, 0.331557f, 0.71481f, 0.380786f, -0.150362f, 0.654365f, -0.318957f, -0.337636f, 0.57301f, 0.474281f, 0.565656f, 0.509379f, 0.245357f, 0.326285f, -0.651439f, 0.345691f, -0.116152f, -0.302133f, 0.780393f, -0.490086f, 0.247162f, 0.383248f, 0.0440418f, -0.177182f, 0.254644f, 0.296667f, 0.359842f, -0.278091f, -0.277828f, -0.595406f, -0.179306f, 0.431211f, 0.440019f, 0.310423f, 0.208222f, 0.540036f, 0.643585f, -0.139872f, -0.521879f, -0.122953f, 0.218204f, 0.158868f, -1.03219f, 0.557886f, 0.0889677f, -0.235379f, -0.392137f, -0.642783f, 0.328969f, 0.0884135f, -0.309692f, 0.763224f, 0.628604f, 0.00669528f, -0.0988385f, 0.79442f, 0.132674f, 0.250137f, 0.914897f, -0.107312f, -0.588339f, 0.473188f, 0.0187198f, -0.174877f, -0.0569728f, 0.0701776f, 0.735162f, 0.154904f, 0.688248f, -0.374409f, -0.556647f, 0.340098f, 0.888618f, 0.0980508f, -0.569228f, -0.595296f, -0.170562f, -0.0317408f, -0.395618f, -0.0171476f, 0.0485352f, 0.43209f, -0.00638226f, -0.0261422f, 0.0718189f, -0.075711f, -0.293662f, -0.319053f, -0.403627f, 0.174707f, -0.448796f, 0.392557f, 0.181877f, 0.370088f, 0.324692f, 0.177263f, 0.018459f, -0.210587f, 0.176304f, 0.420158f, 0.178299f, -0.805978f, 0.0792364f, -0.0386405f, 0.124362f, -0.792909f, -0.122755f, -0.0688359f, 0.159819f, -0.0211371f, -0.122289f, 0.360688f, 0.341697f, 0.0625401f, 0.0971241f, -0.478006f, 0.908729f, 0.189923f, 0.510477f, 0.20677f, 0.236684f, 0.776365f, 0.442561f, 0.090511f, 0.177896f, -0.236025f, 0.0264561f, 0.118261f, -0.809493f, 0.238168f, 0.112513f, 0.338984f, -0.110895f, 0.305834f, -0.621152f, 0.00687668f, 0.447304f, -0.0398545f, 0.370995f, -0.283421f, -0.213979f, 0.113023f, 0.342538f, 0.0130436f, -0.037166f, -0.22709f, 0.772525f, -0.174775f, 0.234323f, 0.159163f, -0.42859f, 0.277611f, -0.632671f, 0.565038f, 0.103225f, -0.305878f, -0.526211f, 0.136796f, -0.259547f, -0.3352f, 0.535223f, -0.031504f, -0.0424749f, 0.481292f, -0.286163f, 0.33113f, -0.38828f, 0.00899621f, 0.306374f, 0.0976362f, -0.198731f, 0.609803f, -0.0760053f, -0.461488f, -0.391667f, 0.00487682f, 0.679276f, 0.256499f, -0.185734f, 0.36559f, 0.00840063f, 0.0567441f, -0.379714f, 0.800748f, -0.468488f, 0.358766f, 0.284236f, 0.0282058f, -0.223142f, 0.277211f, -0.0509614f, -0.0823523f, 0.185893f, -0.335907f, -0.0972623f, -0.13957f, 0.100473f, -0.172652f, 0.31467f, -0.220244f, -0.0687491f, -0.117143f, 0.156706f, -0.365631f, 0.313351f, -0.189641f, -0.537811f, -0.157297f, -0.232214f, -0.25754f, -0.507994f, -0.201826f, 0.21426f, -0.547716f, 0.109537f, -0.161968f, 0.0497426f, 0.341563f, -0.273487f, 0.327382f, 0.271454f, 0.225869f, 0.799898f, 0.170059f, 0.322003f, 0.6798f, 0.0915071f, 0.377649f, -0.423599f, 1.03058f, 0.583441f, 0.481912f, 0.268723f, -0.781103f, -0.212737f, 0.400762f, -0.17187f, -0.18443f, 0.0283509f, 0.700205f, 0.00291917f, 0.345323f, 0.513524f, -0.0680777f, 0.282601f, 0.326917f, 0.18524f, 0.599054f, 0.428758f, 0.76124f, 0.404333f, -0.408655f, 0.29747f, -0.161153f, -0.388405f, 0.24769f, -0.660875f, -0.0948309f, 0.50273f, 0.563415f, -0.406743f, 0.408056f, -0.59666f, -0.375152f, 0.392314f, -0.679927f, 0.610437f, -0.384638f, -0.451703f, -0.416953f, -0.0573409f, 0.179864f, 0.0947484f, 0.0941479f, -0.0885249f, -0.501555f, 0.270931f, 0.179285f, -0.0532051f, -0.516431f, -0.616671f, -0.0110025f, 0.282093f, -0.148804f, -0.680338f, -0.0646467f, -0.249968f, -0.308296f, 0.334441f, -0.358073f, 0.505024f, 0.565072f, 0.24723f, 0.255784f, 0.129823f, -0.0143696f, 0.175873f, -0.424062f, 0.37883f, 0.339341f, 0.202346f, -0.0812525f, 0.151254f, -0.668127f, 0.379888f, 0.117267f, -0.423117f, -0.0725053f, 0.0516017f, -0.11775f, 0.1602f, -0.550289f, -0.584689f, 0.687462f, 0.170713f, -0.54351f, -0.657189f, 0.118749f, -0.0700519f, 0.476461f, 0.101546f, -0.740269f, -0.490129f, -0.619385f, 0.0119928f, -0.98304f, -0.410634f, -0.464535f, -0.222629f, -0.145482f, -0.285285f, -0.593367f, 0.163485f, 0.546191f, -0.401133f, -0.169553f, -0.449783f, 0.285928f, -0.393424f, -0.103438f, 0.319025f, -0.422313f, -0.0548196f, 0.755713f, 0.299799f, -0.224316f, 0.186109f, 0.261191f, 0.188806f, 0.452686f, -0.132676f, 0.587353f, 0.486365f, 0.111516f, 0.377064f, 0.372242f, -0.202814f, -0.242745f, 0.429545f, 0.146983f, 0.455895f, 0.535846f, -0.412878f, -0.531814f, 0.763798f, -0.386117f, -0.0437994f, 0.721294f, 0.480678f, -0.177401f, -0.0745525f, -0.267356f, -0.14923f, 0.0208479f, 0.0218007f, -0.203715f, 0.220439f, -0.0209882f, 0.0163083f, 0.755739f, 0.279977f, 0.92335f, 0.32819f, 0.0551619f, 0.720485f, 0.171199f, 0.31528f, 0.392863f, -0.386591f, 0.494346f, 0.0935399f, 0.218577f, 0.127615f, 0.0894765f, -0.291666f, -0.106409f, -0.0171746f, 0.391619f, 0.594811f, 0.581108f, 0.47502f, 0.0360244f, 0.248309f, -0.433769f, 0.333228f, 0.784775f, 0.582655f, 0.800568f, 0.60786f, 0.178147f, 0.204481f, 0.532827f, -0.314762f, -0.178923f, -0.204282f, 0.451897f, 0.213505f, 0.149531f, -0.294723f, 0.242786f, 0.327522f, 0.163408f, -0.450946f, 0.606869f, 0.174476f, 0.478188f, -0.222704f, 0.0591118f, -0.901394f, -0.395556f, -0.418037f, 0.24394f, 0.204331f, -0.0563055f, -0.449448f, 0.00225183f, 0.384857f, -0.390059f, -0.291526f, 0.0406258f, 0.231365f, -0.181439f, 0.329772f, -0.550588f, -0.43976f, -0.0649923f, 0.14784f, 0.201397f, 0.326097f, 0.631178f, 0.519138f, 0.285717f, 0.222943f, -0.101931f, 0.00119461f, -0.0954484f, 0.339454f, 0.452597f, 0.301302f, -0.213641f, 0.231858f, -0.344925f, -0.402381f, 0.403374f, 0.0886633f, 0.320585f, 0.0666854f, -0.0594505f, -0.0818335f, 0.264554f, 0.00271777f, 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-0.826136f, 0.0841467f, -0.102329f, 0.290162f, 0.278434f, -0.246496f, 0.0624403f, 0.00899192f, -0.244363f, -0.000689143f, -0.734794f, 0.703372f, 0.0110255f, 0.215332f, 0.00447861f, 0.099689f, -0.0203157f, 0.260015f, 0.514569f, 0.322258f, -0.0145341f, 0.498998f, 0.213067f, 0.334479f, 0.295417f, 0.168774f, -0.510815f, -0.400703f, -0.0200453f, 0.435062f, 0.620301f, 0.0252454f, 0.0282759f, -0.36328f, 0.0926921f, -0.221672f, -0.58886f, -0.0400342f, -0.313232f, -0.519594f, 0.243078f, -0.334079f, -0.270033f, -0.495776f, 0.167092f, 0.177772f, 0.280106f, 0.00288477f, 0.240111f, -0.00231105f, 0.431575f, 0.268733f, 0.0265645f, 0.158631f, 0.230716f, 0.716073f, -0.0215768f, 0.12377f, 0.187739f, 0.274746f, 0.5097f, -0.15606f, -0.0945299f, -0.361237f, 0.759519f, -0.311927f, 0.0848565f, 0.0137691f, 0.604014f, 0.325685f, 0.169347f, -0.340699f, -0.417058f, 0.354207f, 0.386487f, 0.147206f, -0.0506241f, -0.214027f, -0.0513623f, 0.42701f, -0.634591f, 0.187363f, -0.508312f, -0.00114855f, -0.0599517f, 0.402596f, 0.492643f, 0.241626f, -0.171303f, 0.818462f, 0.216673f, -0.194423f, -0.447242f, -0.616053f, 0.105917f, -0.248924f, -0.236358f, -0.141672f, 0.0837928f, -0.0377266f, 0.0810627f, 0.407032f, -0.403289f, 0.0850846f, 0.195155f, 0.763047f, 0.605947f, 0.205287f, 0.0275962f, 0.424874f, 0.111251f, 0.0067634f, -0.270874f, -0.352443f, -0.307449f, -0.430445f, 0.522896f, -0.118207f, 0.157462f, 0.312531f, 0.31119f, -0.126322f, 0.136599f, 0.404666f, 0.328707f, -0.962272f, 0.264548f, 0.100268f, 0.486026f, -0.29642f, -0.49643f, -0.854072f, 0.225632f, 0.0917746f, -0.339475f, 0.226054f, 0.392809f, -0.506118f, -0.360228f, -0.0652379f, -0.0141473f, 0.357535f, -0.105279f, -0.32792f, -0.18552f, 0.272587f, 0.275618f, 0.203625f, 0.23702f, -0.0533812f, -0.00699177f, -0.187079f, 0.751397f, 0.0730081f, -0.295114f, -0.293974f, -0.381472f, 0.69258f, -0.259377f, 0.181655f, 0.291579f, -0.000446001f, -0.228219f, 0.092192f, 0.153849f, 0.229261f, -0.554917f, -0.540707f, 0.708528f, -0.152686f, -1.22525f, 0.575331f, -0.314974f, -0.458275f, 0.830017f, 0.0762217f, -0.1202f, 0.333304f, 0.111341f, -0.0184735f, -0.0996309f, 0.161016f, 0.403695f, 0.839637f, 0.492135f, -0.823486f, 0.96226f, -0.446345f, 0.289852f, 0.543863f, -0.198117f, 0.752913f, 0.380549f, -0.213973f, -0.437432f, 0.363786f, 0.165172f, 0.224717f, 0.65566f, -0.2263f, 0.459862f, 0.260625f, -0.412871f, 0.00663674f, 0.690948f, -0.39654f, 0.271418f, 0.814153f, -0.363809f, 0.771566f, 0.454207f, 0.291864f, -0.826874f, 0.205491f, -0.59236f, 0.180294f, -0.574109f, -0.133154f, -0.687293f, 0.624961f, 0.750975f, -0.115789f, 0.219708f, -0.560142f, -0.347924f, 0.475591f, 0.668954f, -0.525235f, 0.560277f, 0.406582f, 0.259707f, -0.291881f, 0.40382f, -0.691378f, 0.511281f, 0.38349f, 0.60171f, 0.175382f, 0.797663f, 0.66795f, -0.110644f, -0.122143f, 0.0752459f, 0.649028f, 0.258376f, 0.763628f, -0.525527f, 0.28668f, 0.338321f, 0.550138f, -0.33597f, 0.226952f, 0.531764f, -0.705424f, 0.175642f, -0.0982047f, -0.428523f, -0.37932f, -0.291669f, 0.618546f, -0.923448f, 1.11912f, -0.141063f, 0.166016f, 0.507537f, -0.189442f, -0.0258596f, 0.346139f, 0.433924f, -0.185028f, 0.373976f, -0.511641f, -0.426385f, 0.451116f, 0.523525f, 0.206911f, 0.607599f, 0.194165f, 0.382406f, 0.935012f, -0.668921f, -0.259511f, 0.429638f, 0.115543f, 0.334018f, -0.541269f, 0.216871f, -0.641842f, 0.683943f, -0.502034f, -0.268726f, 0.701026f, -0.174208f, 0.662809f, 0.368597f, -0.135951f, -0.169557f, -0.466358f, 0.0146659f, 0.625388f, -0.190924f, -0.587081f, 0.0369928f, 0.209533f, -0.0256201f, -0.134377f, 0.367434f, 0.0341216f, -0.436878f, -0.351488f, 0.278601f, -0.158937f, 0.648963f, -0.0653587f, 0.23024f, -0.402509f, -0.208165f, -0.486905f, -0.0833748f, -0.114049f, 0.424813f, -0.0702822f, -0.539892f, -0.124429f, 0.184419f, 0.203463f, -0.121436f, -0.520316f, 1.00983f, -0.0868194f, -0.501019f, 0.0462809f, 0.0783426f, -0.2484f, 0.0981621f, -0.198552f, -0.303788f, -0.0840944f, -0.18279f, 0.600747f, -0.0584895f, 0.100108f, -0.669185f, -0.0780443f, -0.331786f, -0.52951f, -0.270123f, 0.519388f, -0.299453f, -0.527781f, -0.678231f, -0.300144f, -0.00385544f, 0.349333f, 0.851644f, -0.336946f, 0.235634f, 0.220692f, 0.411873f, -0.402994f, -0.012952f, 0.0415505f, 0.3485f, 0.196319f, 0.465808f, 0.111701f, -0.26433f, 0.220039f, -0.402731f, 0.0500919f, -0.319965f, -0.0414993f, 0.475354f, 0.143973f, -0.479436f, -0.233601f, 0.158693f, 0.549028f, -0.397703f, 0.336638f, -0.0746536f, -0.303844f, -0.0445528f, -0.233848f, -0.361522f, -0.00597053f, 0.344429f, 0.229481f, -0.458113f, -0.00821081f, -0.111579f, 0.592684f, 0.00628453f, -0.499848f, 0.496396f, -0.343879f, -0.575317f, -0.293076f, -0.160916f, -0.352197f, 0.0679993f, 0.0551412f, -0.0312388f, 0.265375f, -0.201201f, 0.0245684f, 0.462555f, 0.347122f, -0.972172f, -0.0306904f, 0.0297101f, -0.11272f, 0.477086f, 0.481387f, 0.9836f, -0.398339f, 0.0708219f, -0.753974f, -0.23255f, 0.260514f, -0.245355f, -0.0931575f, -0.673779f, -0.0817291f, 0.199195f, -0.480285f, -0.45005f, -0.023799f, -0.366601f, -0.2084f, 0.666304f, 0.132828f, 0.0877088f, 0.454745f, 0.229825f, 0.264379f, 0.407093f, 0.330497f, 0.218693f, 0.523911f, 0.328874f, 0.805786f, 0.00485716f, -0.211797f, 0.404341f, -0.120829f, -0.241701f, -0.764544f, 0.17835f, -0.30668f, -0.0872752f, 0.97527f, 0.0813365f, 0.472389f, 0.919017f, -0.136896f, 0.134787f, 0.0240096f, -0.60919f, -0.232189f, 0.638233f, -0.53722f, 0.383588f, 1.04688f, -0.223798f, 0.468294f, -0.220214f, 0.405335f, -0.280534f, 0.286776f, -0.179761f, 0.178508f, -0.297183f, 0.182498f, -0.685467f, 0.580719f, 0.19707f, -0.128853f, -0.819698f, -0.270809f, -0.832294f, -0.152185f, -0.393175f, -0.750241f, 0.529206f, 0.762727f, -0.407887f, -0.244154f, 0.572863f, 0.466904f, 0.957789f, 0.686932f, 0.133498f, 0.18891f, 0.850856f, 0.510167f, -0.172768f, 0.14671f, -1.13979f, -0.742267f, 0.393743f, 0.444338f, -0.33688f, -0.0438455f, 0.314722f, 0.306787f, -0.405244f, 0.441624f, 0.505547f, -0.291027f, 0.414324f, -0.252424f, 0.570165f, -0.324644f, -0.521873f, -0.0440274f, -0.176604f, 0.866987f, -0.429828f, 0.280288f, -0.0479095f, -0.246395f, -0.581399f, 1.1762f, -0.870758f, 0.643341f, 0.721751f, -0.412596f, -0.406957f, 0.610477f, 0.501528f, 0.41953f, 0.71976f, -0.913314f, 0.638418f, -0.444716f, -0.425936f, -0.0714459f, -0.656934f, -0.436864f, -0.208498f, 0.283547f, 0.403649f, -0.0865038f, 0.157091f, -0.676679f, -0.0651144f, 0.710754f, -0.689077f, 0.528029f};
+  model->setOperandValue(op11, op11_init, sizeof(float) * 1152);
+  static float op13_init[] = {0.546519f, 0.196527f, 1.33245f, 0.223313f, -0.0686019f, 0.29652f, 0.373173f, 0.536225f, 0.675113f, -0.632758f, -0.340469f, 0.693325f, 0.451477f, -0.38477f, 0.163996f, -0.0238434f, -0.480369f, 0.486697f, -0.157606f, -0.453389f, -0.0613977f, 0.148022f, 0.210699f, 0.305469f, -0.719091f, -0.98168f, -0.729431f, 0.384724f, 0.170649f, 0.102487f, -0.177468f, -0.112562f, 0.977599f, 0.843605f, -0.160566f, -0.0826119f, -1.01795f, 0.327381f, -0.311044f, 0.148776f, 0.458008f, 0.712339f, -0.627031f, -0.0185205f, -0.220114f, -0.254519f, 0.157792f, -0.0902074f, -0.40048f, 0.0213905f, -0.106975f, 0.0542978f, -0.259207f, -0.529396f, -0.023698f, 0.0370436f, 0.175882f, -0.231802f, -0.755031f, -0.635971f, -0.210382f, 0.263938f, 0.644176f, -0.407618f, -0.815028f, 0.719426f, -0.215798f, -0.770013f, -0.190236f, -0.594785f, -0.0741564f, 0.436073f, -0.0194503f, 0.253288f, 0.257328f, -0.475578f, 0.323997f, 0.351296f, 0.0860487f, -0.836167f, 0.220064f, -0.593962f, -0.319109f, 0.20685f, -0.474809f, 0.0252552f, 0.137135f, 0.44559f, 0.241269f, -0.0192984f, 0.139146f, -0.431877f, 0.618441f, 0.246926f, -0.749076f, -0.602428f, -0.0262464f, -0.727089f, 0.614319f, 0.119553f, -0.658924f, 0.177904f, 0.520725f, -0.24752f, 0.539497f, -0.346223f, 1.01883f, -0.375712f, 0.150706f, -0.0695844f, 0.291091f, 0.231353f, -0.302372f, -0.159618f, 1.3969f, 0.838611f, -0.0641228f, -0.112692f, -0.443575f, 0.839417f, 0.531622f, 0.328611f, -0.124474f, 0.493831f, 0.0234903f, 0.0202693f, -0.531455f, 0.58728f};
+  model->setOperandValue(op13, op13_init, sizeof(float) * 128);
+  static float op14_init[] = {0.0492167f, -0.0080753f, 0.106292f, 0.0105276f, -0.0331312f, 0.114954f, 0.170489f, -0.12154f, 0.0805692f, -0.167832f, 0.034986f, -0.296966f, -0.0655937f, -0.111175f, 0.0439435f, -0.018318f, -0.134041f, -0.0846412f, 0.092653f, -0.0790839f, 0.179607f, 0.0128861f, 0.170719f, -0.00102839f, -0.000371042f, 0.187442f, 0.367099f, 0.155459f, 0.127148f, 0.109095f, -0.0116157f, -0.0649709f, 0.00564519f, -0.220081f, 0.0481978f, -0.158649f, -0.00169554f, -0.189301f, 0.0927649f, -0.0162247f, -0.146722f, 0.0395212f, -0.119687f, -0.0263079f, -0.0115938f, -0.00645318f, -0.00155876f, 0.201296f, 0.00391423f, 0.0928273f, -0.0865713f, 0.0358025f, 0.0465153f, -0.192458f, -0.0337003f, 0.0168396f, -0.105297f, -0.052292f, -0.200595f, 0.0113962f, 0.0109133f, -0.0220112f, 0.055337f, -0.177347f, 0.0508988f, 0.0870318f, -0.132901f, -0.0590428f, -0.0393112f, 0.109377f, -0.0827402f, 0.112023f, -0.0645175f, 0.159355f, -0.0984026f, -0.18086f, 0.15466f, 0.0725992f, 0.0280992f, 0.0225695f, 0.00691936f, -0.0502526f, -0.128364f, -0.145571f, 0.0579586f, -0.0274957f, -0.16697f, -0.0250412f, 0.0943546f, 0.0787729f, 0.0940538f, -0.119917f, 0.0964136f, 0.113825f, -0.152387f, 0.311643f, -0.0707457f, -0.0727547f, -0.173086f, -0.113407f, -0.0740743f, -0.00903834f, -0.204262f, -0.0651392f, 0.00987691f, -0.129447f, -0.149183f, -0.120871f, -0.0475758f, 0.036237f, -0.226021f, 0.106552f, -0.0534957f, 0.108059f, -0.0924064f, -0.118662f, -0.00377724f, -0.0365475f, -0.0159883f, -0.0557885f, -0.0465726f, 0.0687464f, 0.0692653f, -0.0202816f, 0.190164f, 0.069391f, 0.036889f, 0.155402f, 0.103209f, 0.124473f, -0.0607203f, -0.11585f, -0.153651f, -0.127314f, 0.149033f, -0.0828471f, -0.00839595f, 0.198123f, 0.122013f, 0.167998f, 0.173856f, 0.0256196f, 0.117699f, 0.126546f, 0.0918655f, 0.0382004f, -0.065435f, -0.0483645f, -0.0119214f, -0.0109207f, -0.129997f, -0.142993f, -0.0613742f, -0.108548f, 0.0510479f, 0.020964f, 0.0262848f, 0.0460446f, 0.0716021f, 0.0597847f, -0.0358898f, -0.141561f, -0.0386211f, 0.111586f, -0.0162418f, -0.158925f, -0.219007f, -0.0756682f, -0.109976f, -0.0832409f, 0.0277708f, 0.145679f, 0.0500395f, -0.111505f, -0.0670436f, 0.279826f, -0.0844559f, -0.000112902f, 0.154262f, -0.204945f, -0.0589911f, 0.032408f, -0.11697f, 0.039011f, -0.254155f, -0.0195576f, 0.193946f, 0.00560876f, 0.0117224f, -0.0429483f, -0.0874491f, 0.166817f, 0.208694f, -0.0294162f, -0.135881f, 0.141971f, -0.0327922f, -0.00175662f, 0.124897f, -0.118557f, -0.119867f, 0.115371f, -0.00347566f, 0.0124675f, -0.00602114f, -0.0738759f, 0.0870936f, -0.0791408f, -0.017976f, -0.00963917f, 0.0734867f, -0.148776f, -0.132703f, -0.140691f, 0.170037f, 0.000135891f, -0.0458496f, 0.153835f, -0.117437f, -0.0346555f, -0.076906f, 0.0373166f, -0.0619154f, -0.054829f, 0.0411179f, -0.0415604f, 0.108682f, -0.0672608f, 0.0434165f, 0.0643523f, 0.226074f, 0.0755257f, 0.180693f, -0.0955687f, 0.0446819f, 0.135113f, -0.0790001f, -0.199555f, 0.190408f, -0.000178168f, -0.145356f, -0.144526f, -0.0218069f, 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0.0303234f, -0.0341824f, 0.00541279f, 0.125561f, -0.0228641f, -0.0996703f, -0.0327039f, 0.106556f, 0.040576f, -0.0228616f, 0.0756781f, -0.0313239f, 0.148017f, 0.087239f, -0.0422876f, 0.0128014f, 0.00778474f, 0.0124598f, 0.0560041f, 0.0447847f, 0.105744f, -0.198212f, -0.0173031f, -0.0021516f, 0.0959182f, -0.0394694f, -0.0131409f, 0.144321f, -0.0949611f, -0.0434338f, -0.028591f, -0.0792033f, -0.0809983f, 0.155448f, 0.000320005f, -0.0940891f, -0.0247999f, -0.0676534f, -0.042852f, 0.0848677f, -0.0446216f, -0.0964214f, 0.0934581f, -0.0733443f, -0.0147374f, 0.152916f, 0.0987156f, -0.205368f, 0.0375851f, 0.0463014f, -0.026474f, -0.0989731f, 0.109547f, 0.0338784f, 0.0118188f, -0.0516393f, 0.117725f, -0.150448f, 0.0169205f, -0.153319f, -0.0180276f, -0.0475676f, -0.0511672f, 0.00929482f, -0.0593558f, 0.028082f, -0.0343435f, 0.172867f, 0.0589468f, -0.109606f, 0.15939f, 0.124152f, 0.0375051f, -0.0954869f, -0.00923394f, -0.0446397f, 0.156135f, -0.0690702f, 0.0285207f, -0.0350714f, -0.00227138f, 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0.103041f, 0.125105f, 0.11604f, 0.160601f, 0.172004f, -0.162463f, 0.00177551f, -0.0324243f, 0.0470986f, -0.0923051f, -0.0861101f, -0.117457f, 0.222946f, 0.145702f, 0.0620147f, 0.141801f, -0.0542949f, -0.102184f, -0.0538152f, 0.0616995f, 0.280185f, -0.0208195f, 0.0329347f, -0.140841f, -0.247536f, 0.00563455f, -0.215743f, -0.0765964f, -0.0428443f, 0.109371f, -0.107962f, 0.0184958f, -0.253019f, 0.16686f, 0.105852f, 0.0197912f, 0.216231f, -0.0231013f, 0.0684397f, 0.250186f, 0.0677787f, 0.0552047f, -0.0654028f, 0.0345012f, 0.0404865f, 0.205448f, -0.0396411f, -0.0148495f, 0.0217306f, 0.0751467f, 0.00868058f, -0.197404f, -0.0259062f, 0.233391f, -0.0509572f, -0.0701687f, 0.0864018f, 0.04512f, -0.0828308f, 0.0347599f, 0.0356228f, 0.139091f, -0.10029f, 0.181864f, 0.144721f, -0.0580658f, 0.200026f, 0.0608931f, -0.100605f, 0.0500621f, -0.116185f, 0.061231f, 0.0399899f, 0.0704832f, -0.0198649f, 0.0436746f, -0.0848174f, -0.0594157f, 0.0459141f, 0.101992f, -0.0225639f, 0.0328491f, -0.124576f, 0.00901623f, -0.106617f, -0.0790743f, -0.149393f, -0.111297f, -0.00141785f, -0.0986489f, -0.0272536f, -0.111998f, 0.0644795f, 0.00456973f, -0.0416466f, -0.169109f, 0.153414f, 0.0223079f, -0.0251582f, -0.0452782f, 0.297413f, 0.101319f, -0.034451f, -0.0636178f, 0.0208852f, -0.0953486f, -0.129885f, -0.0650877f, 0.207028f, -0.0067712f, 0.110558f, -0.00460292f, -0.0343452f, -0.0647179f, 0.0895972f, -0.166407f, 0.0299957f, 0.114112f, 0.0825283f, 0.0639826f, -0.0588411f, 0.0719045f, 0.13956f, 0.137511f, -0.0367233f, 0.124973f, 0.0333517f, 0.206634f, 0.139346f, -0.0619772f, 0.274648f, -0.170636f, 0.0522071f, -0.161702f, -0.00273581f, -0.0613217f, -0.133662f, -0.103478f, -0.0305509f, -0.23801f, 0.11859f, 0.108553f, -0.0210826f, -0.00371995f, 0.08826f, 0.246381f, -0.20268f, 0.000161593f, -0.159964f, -0.0143778f, -0.230486f, -0.0084759f, 0.0263689f, -0.215712f, -0.315595f, -0.255577f, 0.17439f, -0.236849f, 0.158027f, -0.0979086f, 0.00595291f, -0.152628f, -0.231792f, -0.274363f, -0.0221431f, 0.0773764f, 0.0405473f, 0.0537216f, -0.0648253f, 0.0395505f, 0.169131f, -0.0911498f, -0.05096f, -0.276332f, -0.142917f, 0.118599f, 0.00238534f, -0.257787f, 0.203012f, -0.0643763f, -0.134695f, -0.0879208f, -0.00628858f, -0.0430767f, 0.271704f, -0.0849041f, 0.0831666f, 0.107565f, -0.260383f, -0.0866423f, 0.138457f, 0.00619943f, -0.000413046f, 0.104216f, 0.0333808f, 0.00863497f, -0.107758f, -0.124805f, 0.270046f, 0.0737486f, 0.065203f, -0.113866f, -0.0330365f, -0.191473f, 0.0398691f, 0.118263f, 0.0205686f, -0.0784466f, -0.161596f, 0.00894492f, 0.0908254f, 0.0254452f, 0.0771828f, -0.271077f, 0.0428394f, 0.083752f, 0.0356295f, -0.201973f, 0.0980716f, 0.166446f, -0.121299f, 0.2049f, -0.143584f, -0.00551848f, 0.173327f, 0.183502f, 0.233481f, -0.0436572f, 0.032631f, -0.173408f, 0.149638f, -0.0951374f, 0.0468391f};
+  model->setOperandValue(op14, op14_init, sizeof(float) * 16384);
+  static float op16_init[] = {0.8739f, 0.830384f, -0.767024f, -0.878567f, 0.767678f, -0.558645f, -0.618775f, -0.612598f, 0.910247f, 0.796888f, 0.563224f, 0.630585f, -0.716768f, 0.630871f, 0.734415f, -0.211464f, 0.613973f, -0.504694f, -1.0123f, -0.0627354f, 1.00681f, -0.42962f, 0.466991f, -0.450799f, 0.803035f, 0.693793f, 0.732683f, -0.692463f, 0.886803f, -0.565427f, -0.576628f, -0.652566f, -0.782693f, 0.674996f, 0.221864f, 0.572101f, 0.803257f, -0.52347f, -0.486955f, 0.727345f, 0.589734f, 1.15092f, -0.769234f, -0.0774833f, -0.462587f, 0.74472f, 1.08679f, 1.08325f, 0.383234f, -0.845903f, 1.26034f, 0.813296f, 0.771082f, 0.776552f, 0.846018f, -0.685205f, 0.695407f, 0.797641f, 0.626686f, 0.817206f, 0.515052f, 0.50643f, -0.598648f, -0.46153f, -0.452983f, 0.583775f, 0.640815f, 0.539884f, -0.435857f, -0.513433f, -0.485565f, -0.195357f, 0.652978f, -0.33663f, 0.661144f, -0.898781f, 0.287976f, 0.635894f, -0.62165f, 1.0629f, -0.681778f, -0.185328f, 0.487961f, 0.872278f, 0.395395f, -0.740133f, 0.817477f, -0.57104f, -0.664395f, 0.906709f, -0.0626727f, -0.587757f, 0.951452f, -0.61133f, 0.566099f, -0.653262f, 0.896796f, 0.510386f, -0.00755904f, -0.520829f, 0.699523f, -0.51857f, -0.71965f, 0.323285f, -0.547704f, -0.916064f, -0.617135f, -0.584734f, -0.566928f, -0.680113f, 0.935143f, -0.548582f, 0.577092f, 0.969824f, -0.473696f, -0.53212f, 0.666168f, 0.797083f, 0.329202f, 0.815607f, -0.826578f, 0.890131f, 0.866098f, 0.759649f, -0.554823f, -0.791157f, 0.559045f, -0.747694f};
+  model->setOperandValue(op16, op16_init, sizeof(float) * 128);
+  static float op17_init[] = {-0.177647f, -0.0871816f, 0.0601548f, 0.116089f, -0.183163f, 0.578973f, 0.0811623f, 0.372188f, -0.292915f, -0.251623f, -0.133364f, 0.0249744f, 0.209747f, -0.151377f, -0.274688f, 0.10489f, -0.346888f, 0.0908122f, 0.251565f, 0.102152f, -0.659776f, 0.27186f, -0.0203186f, 0.0910226f, 0.0232463f, 0.0918937f, -0.227945f, 0.220206f, -0.129868f, 0.0454901f, 0.00159753f, 0.277318f, 0.341466f, -0.0645028f, 0.29646f, -0.302511f, -0.225254f, 0.181877f, -0.003094f, -0.368428f, 0.0974374f, -0.200103f, 0.0589677f, 0.277546f, 0.111057f, 0.0328741f, -0.426973f, -0.199579f, -0.0472897f, 0.12313f, -0.242737f, -0.122301f, -0.0727011f, -0.235287f, -0.198718f, 0.324696f, -0.0974758f, -0.0987441f, -0.0489072f, -0.460212f, -0.244398f, -0.723718f, 0.0412443f, 0.267359f, -0.464882f, -0.32003f, -0.303246f, -0.329555f, 0.0122901f, 0.167574f, -0.0176612f, 0.299886f, -0.180337f, 0.293521f, -0.276708f, 0.277298f, 0.0906849f, 0.0211019f, 0.0815586f, -0.148871f, 0.0734914f, 0.428517f, 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-0.0281585f, 0.330799f, 0.196422f, -0.158644f, 0.0104495f, 0.153696f, 0.154121f, -0.293512f, 0.0318065f, 0.615847f, 0.319811f, -0.196002f, 0.0428157f, 0.274682f, -0.716382f, -0.518719f, 0.572651f, 0.0312116f, 0.189001f, 0.114644f, 0.216293f, -0.141647f, 0.101355f, -0.189668f, -0.160207f, 0.202959f, 0.112228f, -0.201573f, -0.0583956f, -0.441833f, -0.140472f, 0.136687f, -0.0816845f, -0.0523801f, -0.0820299f, 0.0932448f, 0.0421082f, -0.505471f, 0.299505f};
+  model->setOperandValue(op17, op17_init, sizeof(float) * 1152);
+  static float op19_init[] = {0.380364f, 0.737516f, 0.474086f, 0.849658f, 0.804377f, -0.080858f, -0.10305f, 0.536719f, -1.1622f, -0.342834f, 0.402781f, 0.115227f, 0.24287f, -0.695056f, -0.0436921f, 0.222036f, 0.996912f, 0.176891f, -0.0650841f, 0.269952f, -0.00177294f, -0.0444905f, -0.431159f, 0.182715f, -0.0429493f, 1.03982f, -1.14416f, -0.334853f, -0.319257f, 0.250542f, 0.427705f, 1.00408f, 0.319165f, 0.338126f, 1.06596f, -0.130311f, 0.1664f, -0.91822f, -0.482969f, 0.379555f, 0.931786f, -0.259521f, -0.26676f, -0.511134f, -0.161333f, 0.407205f, 0.127215f, -0.115874f, -0.74857f, -0.614097f, -1.24632f, 0.438902f, -0.010038f, -0.131985f, -0.290398f, -0.303011f, 0.362789f, 0.295431f, 0.486214f, 0.48313f, 0.473817f, -0.260674f, -0.160361f, 0.720992f, 0.004341f, -0.0257513f, -0.544244f, -0.197532f, -0.0570926f, -0.0470323f, -0.358175f, 0.309724f, -0.121827f, -0.451902f, 0.654175f, -0.379612f, 0.425311f, 0.64248f, 0.4375f, -0.608515f, 0.183475f, -0.59398f, 0.735809f, -0.911337f, -0.50899f, 0.477327f, 0.424055f, -1.43826f, 0.624114f, 0.084826f, -0.97254f, -1.32759f, 0.622444f, 1.64941f, -0.44358f, -0.345241f, 0.272338f, 0.318131f, -0.716748f, 0.360981f, -0.0467942f, -0.517288f, 0.874968f, 0.893388f, -0.269836f, 1.12224f, -0.0204914f, -0.0885676f, -0.31172f, -0.76596f, -0.00294207f, -1.0415f, -1.26892f, -0.614158f, -0.893911f, 0.585932f, -0.60524f, -0.365573f, 0.793604f, 0.154101f, 0.602275f, 0.0436358f, 1.52191f, -0.525973f, 0.601713f, 0.7219f, -0.308903f, -0.316313f, -0.198256f, 0.560813f, -1.91373f, 1.20156f, 0.412508f, 0.354517f, 0.949946f, -1.29522f, -0.712151f, -1.15794f, 0.91844f, -0.524767f, 0.732848f, -0.513226f, 1.0062f, -0.260316f, 0.256711f, -0.754329f, 0.287398f, 1.30026f, -0.375037f, 1.20769f, -0.0969743f, 0.499185f, 0.925531f, 0.234913f, -0.153141f, -0.403909f, 0.0366042f, 0.169739f, 0.116354f, -0.264196f, -1.46265f, -0.785626f, -0.301059f, -0.890582f, -0.369919f, -0.121138f, -0.894905f, 0.298203f, 1.05391f, 0.365703f, -0.698288f, 0.568782f, -0.420118f, -0.243541f, -0.510473f, -0.485931f, 0.14858f, 0.716983f, -0.561495f, -0.274852f, -0.0997454f, 0.799118f, 0.5632f, 0.3f, -0.143994f, 0.167208f, -0.405972f, -0.611116f, 0.592297f, 0.0573383f, -0.302561f, 0.397041f, -0.208663f, 0.105459f, 0.208787f, -0.28467f, -0.53325f, -0.289965f, -0.46143f, -0.0343105f, 0.454569f, -0.986058f, -0.528081f, -0.484903f, -0.313444f, -0.159601f, -0.057389f, -0.414452f, 1.10135f, 0.310185f, -0.201504f, -0.383645f, 0.358057f, 0.418672f, -0.0795512f, 0.262256f, 0.050103f, 0.106968f, 0.0782813f, -0.328971f, 0.0522201f, 0.331822f, 0.42769f, 0.085807f, 0.317563f, -0.0834861f, -0.964089f, -0.674804f, -0.763733f, 1.20728f, -0.38138f, 0.567048f, 0.257946f, -0.790288f, 0.503187f, 0.637437f, 0.0358286f, 0.573902f, -0.955088f, -0.526057f, -0.427204f, 0.251301f, -0.0395128f, -0.954701f, 0.364203f, 1.39881f, 0.198054f, 0.481997f, -0.56449f, -0.328474f, -0.499845f, -1.18902f, 0.387863f, 0.154186f, 0.213897f, 0.0501174f};
+  model->setOperandValue(op19, op19_init, sizeof(float) * 256);
+  static float op20_init[] = {-0.121763f, -0.00146586f, -0.152926f, -0.0166871f, -0.0651794f, -0.0883152f, 0.226854f, 0.0820697f, -0.0387004f, -0.0709573f, -0.0293144f, 0.0838588f, 0.0277707f, 0.0109299f, -0.160442f, 0.0837343f, 0.0469172f, -0.00955172f, 0.082859f, -0.0517241f, 0.00340798f, -0.187592f, -0.0247601f, -0.185591f, -0.0532604f, 0.105719f, -0.0966383f, -0.0199812f, -0.00629264f, -0.294315f, 0.0403008f, 0.0803754f, 0.0908397f, 0.219608f, -0.0440038f, 0.189251f, -0.291901f, 0.1426f, -0.134149f, 0.0519352f, 0.0551092f, -0.0487455f, -0.153575f, -0.228557f, -0.208332f, 0.0684225f, -0.0891165f, 0.0469084f, -0.0286844f, -0.0918755f, -0.0639394f, -0.233065f, 0.103416f, -0.0636482f, -0.0807054f, 0.0911907f, 0.162369f, -0.0989415f, 0.0365839f, -0.22269f, 0.0418927f, -0.0636223f, -0.000230235f, 0.117136f, -0.0605703f, 0.127913f, -0.0568488f, 0.0117915f, -0.0931372f, 0.0390826f, -0.22523f, -0.26497f, 0.151425f, -0.0157661f, 0.00381962f, 0.0363325f, -0.159047f, 0.0596872f, 0.16343f, -0.136773f, 0.150644f, -0.144535f, -0.186384f, -0.0577443f, 0.250243f, 0.0107071f, 0.139932f, 0.0679555f, -0.17552f, 0.16454f, -0.218745f, 0.0534704f, -0.133623f, -0.0147184f, -0.201297f, -0.0154522f, 0.265836f, 0.227862f, 0.0136758f, 0.112423f, -0.116164f, 0.0440703f, -0.00406094f, 0.122091f, 0.303093f, -0.0224877f, -0.0710294f, -0.0362077f, 0.0404482f, -0.0223894f, -0.240027f, -0.0128031f, -0.209106f, 0.0263517f, 0.162145f, 0.161153f, -0.0253479f, 0.0410495f, 0.00849734f, -0.0909553f, -0.0838269f, 0.0309831f, -0.0774216f, 0.171137f, -0.224768f, 0.123728f, 0.168099f, 0.33109f, -0.0550043f, -0.11535f, -0.0540238f, 0.110545f, -0.282231f, 0.19566f, 0.161858f, -0.0861269f, -0.0411603f, 0.175063f, -0.178382f, 0.0596902f, -0.229927f, -0.139029f, 0.0268697f, 0.338593f, -0.103072f, -0.0721262f, -0.0566519f, 0.258236f, -0.153182f, 0.308195f, -0.0448432f, -0.165331f, 0.0151538f, 0.203669f, -0.134432f, -0.0512151f, -0.0995045f, 0.126257f, 0.0785744f, -0.20454f, -0.266039f, -0.2169f, 0.100161f, 0.0778487f, 0.194347f, 0.139995f, 0.167684f, -0.101231f, 0.124728f, 0.327965f, -0.0403867f, -0.0215f, -0.194443f, -0.0495848f, 0.367298f, -0.164628f, -0.147905f, 0.165968f, -0.12477f, -0.259033f, -0.167712f, -0.272459f, 0.0789812f, 0.155705f, -0.116364f, -0.213157f, 0.0109595f, -0.324647f, 0.173547f, -0.153593f, -0.0375692f, -0.0271882f, -0.209502f, 0.17778f, -0.283972f, -0.271674f, -0.337646f, -0.296036f, 0.389238f, -0.131556f, 0.177566f, -0.206016f, 0.343375f, -0.0749384f, -0.0414254f, -0.123846f, 0.0649346f, -0.13411f, -0.165414f, 0.0754255f, 0.25563f, -0.106748f, -0.209256f, 0.127924f, -0.241351f, 0.0433725f, -0.10482f, -0.00963543f, -0.00829906f, 0.387104f, 0.0515396f, 0.356357f, -0.279054f, 0.301085f, 0.152901f, 0.0874326f, 0.112942f, 0.0719238f, 0.106289f, -0.0121451f, 0.210162f, 0.0121593f, -0.0388293f, -0.0416732f, -0.12197f, 0.0653273f, 0.069732f, -0.274103f, -0.132969f, 0.352856f, -0.233851f, -0.0569251f, -0.110681f, -0.198357f, -0.0540766f, -0.0852768f, 0.179024f, 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-0.23692f, 0.053388f, 0.396106f, -0.0410978f, 0.00122743f, -0.141285f, -0.0194634f, 0.240345f, 0.0563302f, 0.0557607f, 0.216166f, -0.018195f, -0.0587413f, 0.0335691f, -0.0811946f, 0.0310523f, -0.071152f, 0.00116798f, -0.248101f, -0.233317f, 0.00207474f, 0.211031f, -0.182801f, -0.23281f, -0.0803899f, 0.0796748f, -0.373119f, -0.0236714f, 0.298858f, -0.210002f, -0.123173f, 0.056211f, 0.0710101f, -0.000420267f, 0.222125f, -0.0806963f, -0.177015f, -0.293845f, -0.0810273f, 0.312525f, 0.0173415f, 0.0854641f, -0.0657604f, 0.246809f, 0.18022f, 0.261195f, -0.0449006f, -0.0299894f, 0.125036f, -0.167513f, -0.0828896f, 0.294635f, 0.147186f, 0.172629f, -0.16528f, 0.082555f, -0.130248f, -0.139386f, 0.355252f, 0.17594f, 0.178713f, -0.121214f, -0.0727996f, -0.113729f, -0.0205094f, 0.405982f, -0.060515f, 0.0601772f, 0.144893f, -0.0382382f, -0.103134f, -0.107361f, 0.142849f, 0.245431f, 0.238787f, -0.0994103f, 0.0760072f, 0.14f, 0.154757f};
+  model->setOperandValue(op20, op20_init, sizeof(float) * 32768);
+  static float op22_init[] = {1.08059f, 0.613529f, -0.951719f, -0.861612f, 0.867697f, 0.776146f, 0.886088f, 0.0360881f, -0.228725f, 0.99308f, 0.772503f, 0.13115f, 0.444418f, 0.753733f, 0.806567f, 0.957842f, -1.40967f, -0.29546f, -0.59267f, 0.666514f, -1.10016f, -0.646609f, 0.673707f, 0.953951f, 0.393974f, 0.98207f, -0.644093f, 0.89083f, -0.145055f, -0.821302f, 0.0106507f, -1.09542f, 0.705736f, -0.0362283f, -0.649667f, -0.401635f, -0.00998712f, 0.739409f, -0.187072f, 0.690995f, -0.175346f, -0.465088f, 0.753494f, -1.065f, 1.0958f, -0.684324f, -0.946476f, 0.273813f, 0.795813f, 0.986562f, -0.739017f, -0.449237f, 1.0614f, 0.819235f, 0.557115f, 0.0782367f, 0.00833844f, 0.804665f, 0.954324f, 0.631661f, 0.942427f, -0.650992f, -0.797254f, -0.283754f, 0.497299f, -1.00708f, 0.869227f, -0.574946f, -1.04143f, 0.826134f, 0.710585f, 0.76314f, 0.477792f, 0.930909f, -0.913406f, -1.28013f, 1.40116f, -0.587567f, 0.0107547f, 0.895997f, -0.702578f, -0.681548f, -1.42103f, 0.439222f, 0.629061f, -0.661517f, 0.650495f, 1.01512f, 0.304494f, 0.471469f, 0.70978f, 0.520241f, -1.12464f, 0.789097f, 0.486918f, -0.564991f, -1.16599f, 0.908221f, 0.900087f, 0.804052f, -0.912126f, 1.16053f, -0.964254f, -1.47969f, 0.75153f, -1.10504f, 0.643193f, 0.654283f, -0.774442f, 0.859534f, 1.08754f, 0.894428f, -0.349845f, 0.717952f, -0.818105f, -0.685272f, 0.719653f, 0.221689f, 0.580021f, -0.868784f, -0.765754f, 0.335712f, -1.05373f, -0.736756f, -1.34203f, 0.840665f, -0.783447f, -0.76105f, 0.736778f, -0.714565f, -0.757179f, 0.502076f, -0.429628f, -0.815403f, 0.305288f, 0.511788f, 0.639633f, 0.833758f, -0.881914f, 0.670985f, -0.759582f, 0.477742f, -1.97672f, 0.0150744f, 0.892992f, -0.513419f, -0.636598f, -0.391863f, 0.714185f, -0.271203f, 0.50773f, -0.725078f, -1.09182f, -0.00830997f, 0.800519f, -0.790665f, 0.011206f, 0.648068f, 0.314541f, 0.833785f, 0.743304f, -0.729218f, 0.69944f, 0.716866f, -0.0155263f, 0.236963f, -0.750609f, -0.764535f, -0.974223f, 0.907331f, 0.766474f, -0.902966f, 0.503484f, -0.00109834f, 0.83286f, -0.568512f, -0.30153f, -0.555918f, 0.772897f, -0.910785f, -0.0350145f, -0.973868f, 0.404545f, -0.0615412f, 0.00991651f, -1.01877f, 0.676516f, -0.74005f, -0.598321f, -0.80478f, -1.03634f, -0.874505f, 1.21163f, 1.10213f, -0.00699455f, -0.072837f, -0.449261f, 0.976919f, 0.0676252f, 0.695134f, -0.812793f, 0.759372f, 0.768298f, -0.855527f, 0.614652f, -0.903347f, -1.3134f, 0.884192f, 1.05967f, 0.478357f, -1.11453f, -0.234713f, -0.723932f, 0.288597f, 0.0341888f, -0.4238f, 0.0638279f, 0.793826f, -0.591246f, 0.95119f, 0.88514f, -0.191094f, -0.677312f, -0.934787f, 0.553466f, 0.570809f, 0.292745f, -0.427575f, -0.881358f, -0.879608f, 0.395251f, 0.48285f, -0.605223f, 0.904051f, -0.953032f, -0.500631f, -0.0687485f, 0.0676696f, 0.62603f, 0.0224478f, 0.419152f, 0.835996f, 0.0583883f, -0.620254f, -1.18509f, -0.968522f, -0.298168f, 0.805448f, -0.797511f, 0.413079f, 0.754239f, -0.934051f, 0.800133f, 1.00281f, -0.730008f, 0.2403f};
+  model->setOperandValue(op22, op22_init, sizeof(float) * 256);
+  static float op23_init[] = {-0.28458f, 0.0472449f, 0.32551f, 0.661396f, -0.529311f, -0.109768f, -0.191594f, -0.174226f, -0.677528f, -0.400651f, -0.468258f, 0.465917f, -0.318087f, -0.764231f, -0.291188f, -0.284253f, 0.586599f, -0.0226678f, 0.390401f, -0.471706f, 0.438813f, 0.453643f, -0.36546f, -0.301168f, -0.271752f, -0.334392f, 0.482651f, -0.289412f, -0.793406f, 0.300859f, 0.224297f, 0.203824f, -0.288313f, 0.350108f, -0.368492f, 0.803083f, 0.379972f, -0.337444f, -0.283055f, -0.345158f, 0.388449f, 0.82468f, -0.0244637f, 0.568288f, -0.457818f, -1.08335f, 0.48652f, 0.432265f, -0.233837f, -0.233288f, 0.478888f, -0.339039f, -0.527783f, -0.274578f, 0.227933f, -0.326306f, 0.291881f, -0.25079f, -0.172483f, -0.235968f, -0.213382f, 0.188088f, -0.597735f, 0.145517f, -0.677593f, 0.243537f, -0.168354f, 0.210169f, 0.497489f, -0.156191f, -0.188713f, -0.389135f, 0.125653f, -0.468001f, 0.236705f, 0.743493f, -0.568997f, 0.0730394f, -0.415253f, -0.275788f, 0.211339f, 0.13102f, 0.742574f, -0.939167f, 0.00453726f, 0.256094f, -0.465423f, -0.276601f, 0.273844f, -0.0529241f, -0.154002f, 0.065955f, 0.502945f, -0.144296f, 0.308102f, -0.445824f, -0.199373f, -0.360619f, -0.266055f, -0.374078f, 0.347835f, -0.551932f, 0.385501f, 0.402392f, -0.233246f, 0.674142f, 0.0426675f, -0.957917f, 0.263741f, -0.313646f, -0.394376f, -0.557937f, 0.288833f, -0.3077f, 0.406252f, 0.342111f, -0.251185f, -0.403173f, 0.0751117f, 0.118978f, 0.431095f, 0.0858463f, 0.673327f, 0.167784f, 1.01841f, -0.155637f, 0.526669f, 0.429405f, -0.438051f, 0.40704f, 0.21189f, -0.384288f, 0.560401f, -0.0269653f, 0.239517f, 0.357908f, -0.107261f, -0.294274f, 0.309814f, -0.315181f, 0.388376f, -0.261831f, 0.614283f, -0.304983f, -0.229939f, -0.236821f, 0.0349122f, 0.8521f, -0.25575f, 0.529979f, -0.231175f, 0.251326f, 0.325649f, 0.329067f, -0.315128f, 0.41153f, 0.454485f, 0.21335f, 0.501762f, -0.297765f, -0.129734f, 0.310647f, -0.200211f, -0.657485f, 0.10809f, -0.405919f, -0.22658f, 0.610314f, 0.551553f, -0.286746f, -0.529356f, 0.691515f, -0.233684f, 0.298975f, -0.854537f, -0.813706f, 0.679447f, -0.496609f, -0.29352f, 0.119398f, -0.369995f, 0.28706f, -0.726949f, 0.428352f, 0.206034f, 0.239836f, -0.277531f, 0.35422f, -0.434068f, 0.740928f, 0.378439f, 0.377754f, -0.944411f, -0.666439f, 0.466947f, 0.592947f, 0.780001f, -0.360031f, -0.771556f, 0.0891092f, 0.201805f, -0.341506f, 0.084474f, 0.444853f, 0.143224f, 0.50902f, -0.08028f, -0.192673f, -0.62729f, 0.00593949f, -1.1024f, -1.02446f, 0.252455f, 0.16224f, -1.51712f, -0.00369547f, 0.0075995f, 0.192303f, -0.547526f, -0.205436f, -0.209118f, -0.0254876f, 0.287526f, 0.423511f, 0.0307847f, -0.318243f, -0.0436689f, -0.366271f, 0.283879f, 0.547196f, 0.14235f, 0.228076f, 0.0688717f, -0.0120464f, 0.656107f, 0.525906f, 0.485617f, -0.463831f, -0.297706f, 0.32931f, 0.212747f, 0.0766123f, 0.280379f, -0.475746f, 0.618455f, 0.209996f, 0.395897f, -0.310497f, 0.0888236f, -0.446726f, -0.405172f, 0.075344f, -0.201732f, 0.00210309f, 0.385812f, 0.424705f, -0.183616f, 0.0771259f, 0.153591f, 0.259769f, -0.115946f, -0.0235543f, -0.150271f, 0.344592f, 0.459448f, -0.222459f, -0.517041f, -0.0945315f, -0.384485f, 0.16076f, -0.332681f, -0.196776f, 0.0322294f, 0.411114f, 0.175539f, -0.527312f, 0.0564111f, 0.277134f, -0.341931f, -0.514875f, -0.342404f, -0.0767196f, 0.0884651f, -0.230879f, 0.345558f, 0.0852015f, 0.0562657f, 0.257861f, -0.369273f, 0.377067f, 0.241246f, 0.257019f, 0.343953f, 0.0311605f, 0.347905f, -0.425566f, 0.485304f, 0.244659f, 0.0619747f, 0.109269f, -0.38288f, -0.244667f, -0.0344031f, -0.136566f, -0.154542f, -0.336944f, 0.308047f, 0.0538502f, -0.404385f, 0.0463656f, 0.198913f, 0.137075f, 0.241449f, -0.199885f, -0.12434f, 0.306686f, -0.122854f, 0.398624f, 0.218665f, -0.633676f, -0.931847f, 0.2059f, -0.261068f, 0.331143f, 0.126376f, -0.184037f, -0.198129f, -0.370324f, -0.0560973f, -0.32744f, 0.559529f, 0.0841585f, -0.602346f, -0.375545f, 0.27432f, -0.395894f, -0.0159903f, 0.509431f, 0.297769f, -0.765591f, 0.159231f, 0.139198f, -0.536258f, -0.398787f, 0.149015f, -0.0567586f, -0.138725f, -0.0111194f, 0.140182f, -0.30886f, 0.203031f, -0.0419858f, 0.329565f, -0.52822f, -0.33655f, -0.397831f, 0.243507f, 0.111685f, 0.299017f, 0.10769f, -0.0312799f, 0.109584f, 0.120701f, -0.12889f, 0.349554f, -0.157182f, -0.093955f, 0.119006f, 0.105169f, -0.0889017f, 0.189185f, 0.36128f, -1.09355f, -0.058658f, -0.769913f, 0.096028f, 0.19114f, 0.53226f, 0.279309f, 0.179189f, 0.448786f, -0.13838f, 0.160635f, 0.0633367f, -0.275156f, 0.378503f, 0.0944601f, -1.19245f, -0.0320738f, 0.241066f, -0.132407f, -0.524387f, 0.106939f, -0.251766f, 0.11987f, -0.409609f, 0.222276f, -0.0441906f, -0.0494878f, -0.0501241f, -0.0844014f, -0.28418f, 0.225391f, 0.113369f, -0.154496f, 0.186213f, 0.14614f, 0.401862f, -0.0313085f, 0.560078f, -0.0407017f, 0.122991f, -1.05534f, -0.495545f, 0.420298f, 0.0906709f, -0.113776f, 0.211673f, 0.0413234f, -0.0240217f, -0.591792f, -0.129843f, -0.0503685f, -0.0230143f, 0.524557f, -0.171754f, -0.557895f, -0.020142f, -0.416382f, 0.203279f, -0.296933f, 0.414196f, -0.461552f, 0.448204f, -0.604003f, 0.386268f, -0.300078f, 0.595266f, -0.522842f, 0.31545f, -0.533617f, 0.274282f, 0.112026f, 0.48007f, 0.384362f, 0.290018f, 0.536309f, 0.15782f, -0.364838f, 0.488889f, 0.351907f, 0.597652f, 0.287762f, -0.28167f, 0.160969f, -0.297121f, 0.404882f, -0.149116f, 0.0386217f, -0.349471f, -0.621411f, -0.0252337f, 0.409071f, -0.242507f, -0.384841f, -0.0629887f, 1.14271f, 0.292164f, -0.035478f, 0.421029f, 0.741154f, 0.294348f, -0.568311f, -1.02438f, 0.547155f, -0.147867f, -0.0352431f, 0.559739f, 0.555878f, 0.0771088f, -0.656885f, -0.604422f, -0.0270905f, -0.319741f, 0.0413747f, 0.205865f, -0.157557f, 0.20142f, 0.0739973f, -0.202374f, 0.182571f, 0.125495f, -0.358981f, 0.347608f, 0.120924f, 0.297148f, -0.209438f, -0.130999f, 0.289417f, -0.0272582f, 0.297316f, 0.00982058f, -0.0579106f, 0.138692f, 0.114156f, -0.473807f, -0.122035f, 0.442049f, -0.198079f, -0.262147f, 0.317284f, 0.0710323f, -0.58181f, 0.183706f, 0.287913f, 0.489588f, -0.727535f, -0.253829f, -0.134941f, 0.0686071f, 0.407758f, -0.386223f, -0.194309f, -0.784921f, -0.883296f, -0.503808f, -0.523626f, -0.467586f, 0.394829f, 0.209305f, 0.348011f, -0.0472632f, 0.35137f, 0.255519f, -0.481423f, -0.350921f, -0.890102f, -0.25589f, 0.501613f, -0.583939f, -0.625298f, 0.0170016f, -1.20323f, 0.235603f, -0.0938557f, 0.0682872f, 0.417151f, 0.874886f, 0.209409f, -0.350934f, -1.52988f, -0.319489f, 0.252675f, 0.0163845f, -0.014077f, 0.52858f, -0.331857f, -0.384076f, 0.435026f, -0.702681f, -0.450906f, -0.289385f, 0.468552f, -0.236413f, -0.272462f, -0.177053f, -0.181411f, -0.877142f, -0.523707f, -0.191871f, 0.123453f, -0.0973767f, -0.328066f, 0.455483f, 0.018019f, -0.491974f, -0.0457672f, 0.58567f, -0.106745f, 0.234218f, 0.592343f, -0.215221f, -0.146446f, -0.393353f, 0.0845755f, -0.366009f, 0.325779f, 0.672865f, -0.387826f, 0.0140082f, 0.454678f, -0.438467f, -0.0146397f, 0.323818f, 0.754958f, -0.583166f, -0.0151241f, 0.169896f, -0.128034f, -0.381487f, 0.357348f, -0.0903463f, 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0.320521f, 0.02419f, 0.61694f, 0.512716f, 0.598198f, 0.445239f, 0.173841f, -0.764185f, -0.704966f, -0.585418f, -0.0527982f, -0.307089f, -0.411287f, -0.489087f, -0.166577f, 0.4596f, -0.210193f, -0.34088f, 0.425077f, -0.0379874f, 0.519145f, 0.563041f, -0.331036f, -0.275483f, -0.655757f, 0.398409f, 0.667285f, 0.445515f, -0.820241f, -0.45353f, 0.308196f, -0.99734f, -0.294409f, 0.346829f, -0.451895f, -0.795142f, -0.0511266f, -0.107286f, -0.154059f, 0.346707f, -0.0845256f, 0.0391692f, 0.347465f, 0.271567f, 0.398179f, -0.0316902f, -0.570784f, 0.864692f, -0.581542f, 0.531353f, 0.443992f, 0.217736f, 0.705419f, -0.531833f, 0.233822f, 0.596461f, -0.300839f, 0.299358f, 0.432538f, 0.678099f, 0.178463f, 0.41265f, -0.464257f, 0.628287f, 0.136917f, -0.116851f, 0.591243f, -0.6497f, -0.589883f, 0.253878f, -0.206552f, -0.300106f, -0.436572f, 0.358151f, -0.30087f, 0.0741844f, -0.133629f, 0.0734079f, 0.309023f, -0.31858f, -0.330816f, -0.491164f, -0.185619f, 0.0477906f, 0.102383f, -0.275384f, -0.144486f, -0.116014f, -0.094743f, 0.16468f, 0.00824189f, 0.192893f, 0.180182f, -0.0374888f, -0.334105f, 0.0964284f, -0.362218f, 0.250041f, -0.0907593f, 0.379193f, 0.53907f, -0.185023f, 0.22417f, -0.802062f, 0.115863f, 0.160576f, -0.00339825f, -0.49276f, -0.172174f, 0.500552f, -0.0207371f, -0.970855f, -0.117337f, -0.38892f, 0.0990167f, -0.495046f, 0.31771f, 0.312408f, -0.000407688f, -0.585845f, -0.282656f, -0.136133f, 0.265468f, -0.481894f, -0.477013f, 0.14466f, 0.717022f, 0.183071f, -0.735398f, -0.136935f, -0.719801f, -0.29953f, 0.249766f, -0.0110162f, 0.285124f, 0.077133f, 0.808596f, -0.448734f, 0.510237f, 0.38693f, -0.129041f, -0.458999f, 0.0185829f, -0.12189f, -0.266424f, 0.285585f, 0.110139f, -0.319555f, 0.655882f, -0.534353f, -0.0848718f, 0.419384f, 0.318302f, 0.0163499f, 0.0373466f, -0.549442f, 0.17553f, -0.0221397f, -0.24192f, -0.916088f, -0.304531f, -0.581433f, 0.0304764f, 0.239215f, -0.0925164f, -0.466268f, 0.378297f, -0.131788f, -0.0244173f, -0.141029f, -0.493859f, 0.120541f, -0.130281f, 0.191682f, 0.0499562f, 0.0387449f, 0.0573297f, -0.222652f, 0.0243462f, -0.00673447f, -0.125307f, -0.0958154f, 0.130999f, 0.516754f, -0.0796003f, 0.200398f, 0.114443f, -0.00693852f, -0.128189f, -0.0793437f, 0.135334f, 0.294696f, -0.852946f, 0.0276752f, 0.334047f, -0.0192718f, -0.157855f, -0.258005f, 0.0512356f, -0.116596f, 0.207956f, 0.105078f, 0.127174f, 0.62152f, 0.531852f, -0.654424f, -0.77393f, -0.884332f, -0.396202f, 0.368097f, 0.0321f, 0.205717f, 0.115985f, 0.00618104f, 0.0671344f, -0.845518f, 0.538342f, 0.15833f, -0.967178f, -0.431731f, -0.586238f, 0.0832515f, 0.179131f, -0.245743f, -0.0332011f, -0.171913f, 0.171773f, -0.00721768f, -0.059507f, -0.0616651f, -0.376146f, -0.168347f, 0.345351f, -0.255941f, -0.262391f, 0.19388f, 0.186394f, 0.322809f, 0.0325143f, 0.424184f, -0.35143f, -0.222107f, 0.150236f, 0.492884f, 0.0464353f, -0.257465f, 0.479298f, 0.0364896f, 0.176826f, -0.252383f, 0.41896f, -0.0680623f, 0.164341f, -0.426261f, -0.222705f, 0.245079f, 0.358465f, -0.246757f, -0.223973f, 0.166328f, 0.282368f, 0.455028f, 0.367856f, -0.347886f, -0.409378f, -0.362854f, 0.283562f, 0.169756f, -0.193617f, 0.00312812f, -0.495832f, 0.352697f, -0.183691f, -0.551904f, 0.107424f, -0.583319f, 0.256329f, 0.107989f, -0.0331182f, -0.269719f, -0.877305f, 0.770568f, 0.0217897f, 0.191136f, -0.171633f, 0.253218f, 0.404315f, -0.788884f, 0.0112146f, 0.745102f, -0.138125f, -0.633483f, 0.504864f, 0.0741772f, 0.00743548f, -0.558327f, 0.0308562f, -0.0460712f, 0.156505f, 0.412151f, 0.253912f, -0.405737f, -0.417017f, 0.287808f, -0.60025f, -0.0854479f, 0.060658f, 0.251385f, 0.191479f, -0.17089f, 0.184903f, 0.144427f, -0.323747f, -0.253991f, 0.692197f, 0.180504f, 0.718203f, 0.339426f, 0.0880803f, 0.1821f, -0.0226106f, 0.239636f, 0.297463f, -0.329112f, -0.252176f, 0.129749f, -0.689667f, -0.0406387f, -0.705156f, 0.487122f, 0.339248f, -0.480679f, -0.250687f, -0.485937f, 0.350601f, -0.494732f, -0.243734f, -0.268831f, -0.410827f, 0.0092456f, -0.180332f, -0.231252f, -0.117829f, 0.683444f, 0.239322f, 0.246556f, -0.131343f, 0.491822f, 0.123562f, 0.192736f, -0.340809f, -0.644343f, -0.290442f, -0.0756787f, -0.324289f, 0.507526f, 0.411936f, -0.177079f, 0.402165f, -0.267137f, 0.24193f, 0.360351f, -0.246662f, -0.571923f, -0.702905f, 0.226792f, -0.139328f, 0.22413f, -0.227143f, -0.709298f, 0.51886f, -0.612136f, 0.625465f, 0.465218f, 0.00702443f, -0.426036f, -0.411896f, 0.0610381f, 0.629113f, -0.477653f, -0.0435138f, 0.14425f, 0.974669f, 0.116439f, -0.242099f, -0.453082f, -0.592571f, -0.606518f, -0.0694814f, 0.49124f, 0.435993f, 0.0573165f, -0.0463377f, -0.0815331f, 0.171534f, 0.523446f, -0.45542f, -0.224177f, -0.237075f, -0.0303856f, -0.281409f, 0.161822f, 0.640442f, -0.188442f, 0.582021f, 0.188833f, -0.441974f, 0.401265f, -0.256714f, 1.07948f, 0.0952702f, -0.205754f, 0.38561f, -0.0153532f, -0.324404f, -0.201656f, -0.49744f, -0.622206f, -0.614933f, 0.466828f, -0.407296f, -0.0402541f, 0.226478f, 1.38546f, -0.195908f, -0.377207f, -0.465495f, 0.64496f, -0.696121f, 0.368228f, 0.487155f, -0.675746f, 0.369155f, -0.135017f, 0.201887f, 0.196515f, -0.211104f, -0.528813f, -0.573743f, -0.658933f, -0.210996f, 0.374055f, -0.342353f, -0.112863f, 0.436295f, -0.537892f, 0.773281f, 0.319618f, -0.607668f, 0.125097f, 0.452643f, 0.3964f, -0.45951f, 0.0684969f, 0.331722f, 0.0313258f, 0.232967f, 0.433636f, 0.0453946f, 0.696013f, 0.305709f, -0.00556975f, -1.04627f, -0.182575f, -0.312805f, 0.289384f, -0.209719f, 0.498444f, -0.0556132f, 0.618527f, -0.489828f, -0.27455f, 0.454784f, 0.38062f, -0.053773f, -0.197319f, -0.0958428f, 0.0976471f, 0.391348f, 0.691822f, -0.928015f, -0.180371f, 0.28998f, 0.53853f, -0.928278f, 0.152375f, -0.0323293f, -0.235519f, 0.242977f, -0.253792f, 0.0648444f, 0.273537f, -1.09638f, 0.494502f, 0.260978f, -0.119055f, -0.505667f, -0.420982f, 0.721884f, 0.342437f, -0.584703f, -0.316703f, 0.314904f, 0.482382f, 0.800729f, -0.197054f, 0.318495f, 0.472762f, 0.660303f, -0.34121f, 0.682947f, 0.423539f, 0.360519f, -0.127974f, 0.336235f, 0.454418f, 0.123031f, -0.421285f, 0.257301f, -0.147292f, -0.372451f, -0.217667f, -0.770868f, 0.173788f, -0.292246f, 0.37707f, -0.51294f, 0.246741f, -0.250596f, -0.102101f, 0.529798f, -0.168518f, 0.40385f, 0.731781f, -0.305084f, -0.329997f, -0.294573f, 0.45172f, 0.320347f, 0.444778f, -0.845154f, 0.503533f, 0.204295f, -0.625158f, -0.256043f, 0.172196f, -0.528596f, -0.1252f, -0.8008f, -0.00855475f, -0.116112f, 0.484289f, 0.114892f, -0.387584f, 0.476534f, 0.357803f, 0.321582f, -0.794938f, -0.401772f, 0.636876f, -0.310624f, 0.42546f, 0.680463f, 0.216965f, -0.74392f, -0.922457f, -0.699813f, -0.129799f, -0.16734f, -0.859169f, 0.328387f, 0.688874f, 0.669709f, -0.228886f, -0.469983f, 0.728589f, 0.27625f, -0.0885543f, 0.415512f, -0.284111f, -0.807751f, 0.0895664f, -0.474001f};
+  model->setOperandValue(op23, op23_init, sizeof(float) * 2304);
+  static float op25_init[] = {0.059552f, -0.776265f, 0.586331f, -0.19955f, -1.15878f, -0.623411f, 0.482733f, 0.620705f, -1.42987f, 0.599004f, 0.296987f, 0.243854f, -0.326452f, -1.66933f, 0.114657f, -0.912619f, -1.40799f, 0.873297f, -2.02128f, 0.349338f, 1.03578f, -0.584717f, 0.68394f, 0.12814f, 0.766933f, -0.348055f, 0.426793f, -0.0519259f, -0.31104f, -0.70917f, -1.98005f, 0.466914f, -1.22813f, 0.922352f, 0.803956f, -0.758258f, -0.0178442f, 0.159704f, -0.693864f, 0.541313f, -0.61248f, 0.140332f, -0.732719f, -0.061292f, -1.21815f, -1.36358f, 1.55065f, -0.867879f, -0.118565f, -1.429f, -0.24872f, 0.756503f, -0.276562f, 1.01472f, 0.613279f, 0.252628f, -0.154586f, 0.213353f, -0.259666f, -0.0845054f, 1.48898f, -0.78227f, 0.475328f, -0.149806f, -0.126194f, -0.504444f, -0.156527f, -0.485018f, -0.398986f, -0.390188f, 0.805819f, 1.24142f, 1.92392f, -0.0204732f, -0.34912f, -0.821812f, 0.714334f, 1.01406f, -0.827258f, 1.56897f, 0.435821f, 0.00175438f, -0.196037f, -1.00622f, -0.934045f, -0.814433f, -0.00923873f, 0.67536f, -0.183227f, 0.118676f, 1.29346f, -0.292178f, -0.172461f, 0.696343f, -0.603604f, -0.135618f, 0.911071f, 0.863372f, 1.14968f, 0.495017f, 0.525449f, 0.94923f, -0.203282f, -1.86435f, 0.334763f, -0.803913f, -0.151671f, 0.61989f, -0.661122f, 0.621632f, -0.835182f, 0.0620014f, 0.110495f, 0.10499f, 0.867545f, -0.117217f, -0.450633f, 0.805698f, 0.270723f, 0.080994f, -0.234987f, -0.834794f, 0.946942f, -0.149305f, -0.994457f, 0.0162253f, -0.229257f, 0.749062f, -0.160174f, -0.192936f, -0.562147f, -0.481395f, 0.0400992f, 0.707402f, 1.25304f, 0.0850877f, -0.387467f, -0.719366f, 0.425257f, 0.663763f, -0.312089f, 0.084609f, -0.127238f, 0.0892191f, 0.452648f, -0.180974f, 0.200651f, -1.02692f, 0.723075f, -0.819408f, 0.61707f, 0.638342f, -1.42357f, 0.182241f, -1.5596f, -0.504548f, 0.99742f, 2.21562f, -0.450749f, 0.899844f, -0.779047f, -0.0130739f, 0.932655f, -0.301747f, -0.302013f, 1.12503f, -1.0337f, 0.157642f, -0.390012f, -0.439374f, 0.319801f, -0.420911f, 0.207037f, -0.415911f, 0.133631f, 0.65813f, -0.103256f, 1.28002f, -0.722025f, 0.198662f, 0.668599f, -0.573971f, -0.503427f, 0.327037f, 0.382418f, 0.452662f, -0.326031f, -0.109258f, 0.634596f, -0.626296f, -0.882987f, -0.975486f, -0.198001f, -0.736511f, -0.401334f, 0.675054f, -0.0783199f, 0.820609f, -0.213448f, -0.517507f, 0.424629f, 0.708728f, 0.375385f, -0.204245f, 1.46808f, 1.40466f, -0.615909f, -0.109114f, 1.3006f, -0.314086f, -0.640962f, 0.597668f, -1.2886f, -0.942914f, -0.615433f, -0.267436f, -0.234165f, 0.180395f, -0.505358f, 0.389795f, -0.418978f, 0.16119f, 0.701265f, 1.801f, 0.797389f, 1.04949f, 0.470902f, 0.794846f, 1.20815f, 0.639917f, 0.1663f, 0.715599f, 0.227951f, -1.18309f, 0.619096f, 0.799573f, 0.666824f, -0.205099f, -0.0918158f, 0.922449f, -0.674654f, 0.607058f, -1.33098f, 0.303168f, -0.158435f, 0.493879f, 0.64636f, 0.76502f, 0.398199f, -0.708121f, 0.245043f, -0.573639f, 1.09403f, 0.477721f, -0.794756f, 0.0482809f};
+  model->setOperandValue(op25, op25_init, sizeof(float) * 256);
+  static float op26_init[] = {0.00876338f, 0.159478f, 0.311471f, -0.00469625f, -0.242645f, -0.283327f, 0.117541f, 0.154311f, 0.016744f, 0.0241657f, 0.166488f, 0.0644902f, -0.0694389f, 0.0201139f, -0.0289717f, -0.113529f, -0.149222f, -0.0559651f, 0.0669082f, -0.0953956f, 0.115591f, -0.0932612f, 0.198847f, 0.258349f, 0.0286179f, 0.0536193f, -0.0161622f, 0.0876863f, 0.0223337f, -0.0558078f, -0.015007f, 0.0117489f, -0.123187f, -0.00973389f, -0.0112027f, -0.0269762f, 0.216264f, 0.0934549f, 0.0489395f, -0.0667397f, -0.048408f, -0.201219f, -0.051415f, 0.217466f, 0.00516112f, -0.0248904f, 0.0924763f, -0.0488527f, 0.02581f, -0.0741177f, 0.0257687f, 0.0631479f, -0.135362f, -0.0443659f, -0.112051f, -0.00969363f, 0.176092f, -0.160745f, 0.0324613f, 0.143151f, -0.281107f, 0.119342f, 0.0919042f, 0.0855942f, 0.0613969f, 0.0313948f, -0.0784912f, 0.270995f, -0.0791038f, 0.0612157f, 0.149409f, 0.0454657f, 0.206511f, -0.0189417f, 0.123541f, -0.0517153f, 0.0294248f, 0.111004f, 0.186126f, -0.135645f, 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0.12883f, -0.00173171f, 0.182896f, -0.107363f, 0.123074f, -0.14054f, 0.209795f, 0.116346f, -0.0617875f, 0.110168f, -0.0232458f, -0.172889f, 0.0595888f, -0.192809f, 0.00841598f, -0.199597f, -0.0586655f, -0.00795562f, -0.0956537f, 0.00128222f, 0.0421622f, -0.152675f, 0.181584f, -0.0704876f, 0.0858321f, -0.0567543f, 0.11328f, 0.152461f, -0.208114f, -0.167482f, -0.0419129f, 0.0908803f, -0.140871f, 0.0105671f, 0.160085f, 0.207388f, 0.199671f, -0.0255306f, -0.0943408f, 0.111921f, -0.180809f, 0.0473658f, 0.0100724f, -0.216183f, 0.0654583f, -0.0243085f, 0.0737685f, -0.0502344f, -0.205512f, -0.0139682f, 0.109137f, 0.105571f, 0.0552158f, -0.125576f, 0.0620585f, 0.068879f, -0.0253168f, 0.133263f, 0.0400752f, -0.0424402f, -0.0872983f, -0.107545f, -0.0277247f, -0.0578045f, 0.0362632f, 0.140196f, -0.0261901f, 0.187779f, -0.0635921f, -0.0523621f, 0.229485f, -0.0190439f, -0.0718016f, 0.043292f, 0.0299828f, 0.123821f, -0.158516f, 0.153005f, -0.214138f, 0.131521f, 0.0891609f, 0.193635f, -0.0886758f, -0.0056219f, -0.0073096f, 0.140728f, -0.0284736f, -0.186328f, 0.00946189f, -0.0481822f, 0.145028f, -0.0471732f, 0.142449f, 0.0480657f, -0.0927644f, 0.017843f, 0.0131457f, -0.03732f, -0.0260419f, 0.0918974f, -0.0431395f, -0.118994f, 0.231523f, -0.318429f, 0.0397127f, 0.0492337f, 0.0726929f, 0.10699f, -0.35274f, 0.164078f, 0.149988f, 0.131295f, -0.00388833f, -0.0601893f, -0.0853431f, 0.267183f, -0.0624809f, 0.0213025f, -0.109965f, -0.00912624f, 0.0275681f, -0.256799f, 0.0402505f, 0.199534f, -0.00599506f, 0.14945f, -0.0331971f, 0.0865041f, -0.0730954f, 0.0564954f, 0.270481f, -0.149565f, -0.0988167f, 0.00997729f, 0.0891173f, -0.0959777f, 0.0471534f, 0.0116906f, -0.02657f, 0.0191297f, 0.0985174f, -0.0396014f, 0.014939f, -0.142408f, -0.188645f, 0.145756f, 0.12443f, -0.0477664f, 0.106668f, 0.118081f, 0.0601337f, 0.0923126f, -0.0981329f, 0.0247064f, 0.189113f, 0.184961f, 0.0779132f, -0.0683965f, 0.0574355f, 0.010815f, 0.128234f, -0.0222933f, -0.104797f, -0.273139f, -0.0875092f, -0.0713455f, -0.0670424f, -0.0397861f, -0.0757338f, -0.0321257f, 0.0375769f, 0.187379f, -0.106943f, 0.127953f, 0.270204f, -0.0822088f, -0.0242656f, 0.0990913f, 0.227184f, 0.0255154f, 0.156065f, -0.0162164f, -0.175027f, -0.0536166f, 0.350152f, -0.0863701f, 0.108102f, 0.0131009f, 0.0558025f, -0.22567f, 0.2056f, -0.295193f, -0.14584f, 0.0661884f, -0.0893963f, 0.11974f, -0.0382503f, 0.0285192f, -0.100242f, 0.113722f, 0.0184857f, -0.00448416f, -0.0413476f, -0.0891821f, -0.177578f, 0.0180004f, -0.165026f, -0.0337959f, -0.236752f, 0.180452f, -0.085643f, 0.108829f, 0.0491221f, 0.117443f, -0.234701f, 0.138727f, -0.025024f, 0.0401201f, 0.0987451f, -0.066132f, -0.16346f, -0.100028f, -0.186702f, -0.110143f, 0.0575087f, -0.130745f, -0.0705247f, 0.0110047f, 0.198597f, 0.1569f, -0.187375f, -0.0377752f, -0.0192336f, 0.0893955f, -0.104773f, -0.0441842f, 0.0238164f, 0.0458868f, 0.061032f, -0.187736f, -0.0753091f, -0.0973642f, -0.00944946f, 0.0210427f, -0.0883291f, 0.0215373f, 0.0569074f, -0.0131094f, -0.190012f, -0.0206695f};
+  model->setOperandValue(op26, op26_init, sizeof(float) * 65536);
+  static float op28_init[] = {0.950459f, 0.0296315f, -0.0123494f, 1.19466f, 0.255425f, -0.197264f, 1.6053f, 0.809934f, 0.513879f, 0.820272f, 0.23914f, -0.194486f, -0.458706f, 0.368204f, -3.87869f, -0.0187326f};
+  model->setOperandValue(op28, op28_init, sizeof(float) * 16);
+  static float op29_init[] = {1.23719f, -0.67217f, 1.08832f, 0.484643f, -1.00873f, -0.653809f, 0.661964f, 1.06108f, 0.184015f, -0.878391f, -2.61659f, 1.83468f, -1.24167f, -0.334045f, -1.42114f, -1.4081f, 0.743121f, -1.58702f, 1.60977f, 0.541011f, 1.03177f, -0.777374f, 0.170171f, -0.410803f, -2.08614f, -0.253479f, -2.48095f, 0.450924f, -1.17839f, 1.02977f, 0.632391f, 0.683954f, 1.24468f, -1.03801f, 0.808721f, 0.503261f, 1.52073f, -0.299188f, 0.0812176f, -0.914902f, -1.96872f, -0.236636f, -1.64942f, -0.512883f, -0.442176f, -0.0897904f, -1.55935f, 2.44719f, -0.321642f, 0.045825f, -0.0790507f, -2.15146f, -0.670395f, 0.376227f, 0.796031f, 0.631427f, -0.277739f, 0.175722f, 0.0270909f, 0.811911f, 0.761613f, 0.639926f, 3.61268f, -1.81263f, -0.688285f, 0.315179f, 0.18691f, -1.5542f, 1.12532f, 0.312383f, 0.0806777f, -0.642157f, 1.22573f, 0.183517f, -0.756625f, -0.332537f, 0.916962f, 1.02378f, 4.7186f, -1.10432f, -0.0695368f, 0.18656f, 0.428627f, -1.33377f, 3.06145f, -0.561649f, -0.496272f, -1.75449f, 1.9422f, -0.33641f, -0.0531178f, -0.696678f, -0.0305814f, -1.75068f, -1.7157f, 1.20486f, -0.779788f, 0.937587f, -0.774572f, 1.5068f, -1.08521f, 1.30134f, -0.970244f, 0.509486f, -0.322837f, -0.513111f, 2.5801f, -0.221533f, 1.53355f, -0.0568376f, 0.26331f, 0.0692347f, -0.911869f, 0.874316f, -1.37498f, 0.116868f, -0.563794f, 1.08106f, -0.737648f, 1.09901f, 0.941713f, 0.319754f, 3.2568f, -0.13864f, 0.882837f, -0.194686f, 2.77097f, -0.19543f, -0.54728f, 0.935008f, -1.22157f, 0.670149f, -1.28085f, 0.137126f, -0.665442f, 0.262963f, 0.34245f, -0.106122f, 2.05506f, -0.604292f, -0.217629f, -0.123072f, -3.16904f, 0.02477f};
+  model->setOperandValue(op29, op29_init, sizeof(float) * 144);
+  static float op31_init[] = {-0.517417f, 0.0426414f, -0.357654f, 0.645831f, -0.182669f, -1.11405f, 0.516978f, 0.0161366f, -0.438554f, 1.18839f, -1.07079f, 0.0316377f, 0.552099f, 1.03371f, 1.01932f, 0.267632f};
+  model->setOperandValue(op31, op31_init, sizeof(float) * 16);
+  static float op32_init[] = {0.0442092f, 0.100294f, -0.165622f, -0.0254995f, -0.000117605f, 0.108391f, 0.103699f, -0.0864047f, 1.14539f, -0.0113399f, -0.0835518f, -0.0363124f, 0.0108043f, -0.0282255f, 0.00364833f, -0.0477529f, 0.136618f, -0.24613f, 0.137167f, 0.000881128f, 0.123369f, 0.697108f, 0.223616f, 0.022898f, -0.159309f, -0.374391f, 0.165748f, 0.376668f, -0.570377f, -0.0785476f, 0.560518f, 0.186954f, 0.8159f, 0.0888002f, 0.406594f, 0.0370246f, -0.127239f, -0.517474f, 0.0261465f, 0.229986f, 0.0585454f, 0.166348f, 0.304265f, 0.120066f, 0.354865f, -0.224302f, -0.735672f, -0.0550739f, 0.404087f, 0.0294423f, 0.0200603f, 0.0209366f, -0.000457059f, -0.0117939f, -0.30404f, 0.00396221f, -0.0269691f, -0.0334725f, -0.0343909f, -0.0246526f, -0.0922904f, 0.0158384f, 0.575937f, 0.0346629f, -0.101794f, 0.254893f, -0.00422475f, -1.21483f, 0.10141f, -0.191787f, 0.473363f, 0.0594516f, 0.141317f, 0.0189096f, 0.120227f, 0.0256014f, 0.0587697f, 0.018237f, 0.818418f, -0.162319f, 0.0492727f, -0.277837f, 0.0923082f, -0.0693218f, 1.13724f, -0.436901f, 0.134505f, 0.165517f, 0.216349f, 0.521773f, 0.133342f, -0.538622f, -0.00520006f, -0.352552f, 0.186707f, -0.563571f, 0.157166f, -0.203963f, 0.615195f, -0.0157265f, -0.184236f, -0.127932f, 0.1663f, -0.280368f, -0.659668f, 0.118125f, 0.440214f, 0.0015294f, 0.0927123f, -0.197986f, 0.0760051f, 0.08768f, 0.0432116f, -0.7727f, -0.39429f, 0.121467f, 0.290871f, 1.06573f, -0.0100696f, -0.3215f, -0.605128f, -0.365822f, 0.0282545f, 0.0354838f, 0.233038f, -0.479717f, 0.179297f, 0.23784f, -0.0593619f, -0.0224619f, 0.0558388f, -0.026943f, 0.080387f, -0.0668255f, 0.0346286f, 0.0982081f, -0.0113279f, -0.0573998f, 0.0346731f, -0.276434f, 0.029451f, 0.978238f, 0.046547f, -0.0428502f, -0.069273f, -0.112573f, 0.0353035f, 0.0760213f, -0.229825f, 0.256784f, -0.0865124f, -0.117515f, -0.0190794f, 0.053253f, -0.0527775f, 0.0563685f, -0.216214f, -0.0908149f, 0.0196348f, -0.0147699f, 0.000646807f, 0.519219f, 0.553983f, -0.0162967f, 0.180212f, -0.158552f, 0.103136f, -0.0657329f, 0.716499f, 0.00303961f, 0.383627f, -0.0865072f, 0.159668f, -0.10951f, 0.504002f, -0.237362f, -0.018895f, 0.402239f, -0.253648f, -0.042068f, 0.632025f, 0.28811f, 0.0143706f, 0.365129f, 0.110419f, -0.292138f, -0.40216f, 0.0356688f, -0.803869f, -0.0731997f, 0.0585228f, 0.116289f, -0.00771922f, 0.14662f, -0.151595f, 0.0332509f, 0.422503f, -0.0735451f, -0.022096f, 0.419504f, 0.0316678f, -0.108478f, -0.0858874f, -0.117858f, -0.0308824f, -0.0150928f, -0.135797f, -0.00134129f, -0.0363398f, -0.133177f, -0.329766f, -0.0157401f, -0.0585963f, 0.418158f, -0.0203871f, -0.0345592f, -0.869422f, -0.0642393f, -0.248801f, 0.310259f, -0.0907119f, -0.428003f, 0.0452463f, 0.0290068f, -0.40103f, 0.130153f, 0.180791f, -0.0258097f, -0.141686f, -0.323571f, -0.395809f, -0.0476737f, 0.27939f, 0.161304f, 0.238462f, -0.0476686f, 0.453612f, 0.02649f, 0.129983f, 0.0522385f, 0.0297746f, 0.213469f, 0.11375f, 0.0878489f, 0.199765f, -0.0642271f, -0.271912f, 0.00243141f, 0.835912f, 0.104512f, -0.0144645f, 0.0659315f, -0.0166996f, -0.0624446f, -0.627624f, -0.104059f};
+  model->setOperandValue(op32, op32_init, sizeof(float) * 256);
+  static float op34_init[] = {1.19974f, -0.185076f, 1.32092f, 0.0976943f, -0.187869f, -0.601424f, 0.109655f, -0.824136f, 1.76613f, 1.92313f, 0.0470319f, 0.0441899f, 1.04743f, 1.48342f, 1.92262f, 0.417516f};
+  model->setOperandValue(op34, op34_init, sizeof(float) * 16);
+  static float op35_init[] = {-0.192145f, 0.606418f, -0.0568535f, -0.174212f, -0.220749f, 0.294504f, 0.250408f, 0.0870216f, -0.106517f, -0.0128364f, 0.190258f, 0.458306f, 0.936822f, -0.362511f, -0.0127489f, -0.0133373f, -0.232533f, -0.442404f, -0.128353f, 0.140481f, 0.354678f, 0.165237f, 0.0561957f, 0.540504f, -0.169096f, -0.31736f, 0.124375f, 0.145857f, -0.286506f, -0.333099f, -0.451718f, -0.691901f, -0.0416297f, -0.195466f, -0.0223783f, 0.427847f, -0.0137003f, -0.172101f, -0.0535766f, 0.271151f, -0.0675339f, -0.429987f, 0.108888f, -0.110792f, -0.921419f, -0.121298f, -0.258522f, -0.52257f, -0.344404f, 0.519004f, 0.167952f, -0.327749f, -0.400563f, 0.765311f, 0.285217f, 0.367853f, -0.200799f, -0.290995f, 0.27534f, 0.530624f, 0.955898f, -0.176768f, -0.445762f, 0.444517f, -0.357274f, 0.324649f, -0.107971f, 0.150048f, 0.494237f, 0.30383f, 0.324753f, 0.567321f, -0.301667f, -0.296505f, 0.264912f, 0.250856f, 0.279213f, -0.466188f, -0.337701f, 0.291899f, -0.064519f, -0.745488f, -0.305469f, 0.61913f, 0.0724054f, -0.444646f, -0.0926981f, 0.161211f, -0.146827f, 0.00351782f, 0.130313f, -0.132444f, -1.32228f, -0.323326f, -0.0250575f, -0.701916f, -0.207874f, 0.0825065f, -0.10657f, -0.341674f, -0.223069f, 0.791148f, 0.0434073f, 0.322624f, -0.0867508f, -0.227108f, 0.121276f, 0.139853f, 0.0622248f, 0.00764603f, -0.313398f, 0.101314f, -0.24079f, 0.620351f, -0.251547f, 0.0892458f, 0.370692f, 0.201349f, 0.233192f, 0.221301f, -0.164076f, -0.111546f, 0.0542954f, 0.223996f, 0.370248f, -0.315324f, -0.155129f, 0.476494f, -0.00596379f, -0.131588f, -0.276947f, 0.468515f, 0.00297447f, -0.529512f, 0.0695675f, 0.0265823f, -0.0858685f, 0.310371f, 0.0143207f, -0.0321677f, -0.515507f, -0.335209f, 0.171599f, 0.021023f};
+  model->setOperandValue(op35, op35_init, sizeof(float) * 144);
+  static float op37_init[] = {1.01203f, 0.729789f, 1.05009f, 2.45074f, -0.428937f, -0.168061f, 0.883948f, -0.463319f, 0.716813f, 0.896726f, -1.56615f, -1.25198f, -0.865042f, 1.70229f, 1.22468f, 0.840712f, 0.992703f, 0.409845f, 1.88565f, 0.918815f, 0.842341f, -1.1515f, -1.97437f, 1.05457f, 0.111851f, 0.675341f, 0.645972f, -0.579008f, -0.226735f, 0.758494f, -1.2271f, 0.945416f};
+  model->setOperandValue(op37, op37_init, sizeof(float) * 32);
+  static float op38_init[] = {0.0270471f, 0.00919901f, -0.0193453f, 0.0103695f, -0.0430962f, -0.0132642f, 0.0137244f, 0.00528576f, 0.0410232f, -0.0444378f, 0.00887553f, -0.0248847f, -0.000360784f, 0.00789876f, 0.00872832f, 0.00384528f, 0.0841045f, 0.049066f, -0.0429076f, -0.000282252f, 0.0454269f, 0.20789f, -0.0372577f, -0.130965f, -0.0968065f, 0.447734f, 8.29139e-05f, -0.0827644f, 0.0259536f, 0.067688f, -0.0901188f, -0.00476768f, -0.812498f, -0.0419137f, -0.404739f, -0.481643f, -0.364882f, 0.0809418f, 0.61269f, -0.0632456f, -0.0305597f, 0.334748f, 0.4738f, 0.316527f, 0.132221f, -0.574053f, 0.0378586f, 0.47517f, 0.404207f, 0.370556f, -0.0152144f, -0.0397815f, -0.245993f, -0.0494612f, -0.302243f, -0.132276f, -1.62311f, 0.112993f, -0.0164078f, -0.333526f, 0.228636f, 0.142801f, 0.304721f, -0.116069f, 0.093896f, 0.6867f, -0.143538f, -0.0901391f, 0.43879f, 0.0573514f, -0.328247f, -0.0460923f, -0.0681418f, 0.0378803f, -0.0743326f, 0.186537f, 0.336441f, 0.343403f, 0.0384152f, 0.180381f, 0.230074f, -0.403994f, 0.0168588f, -0.133206f, 0.161728f, 0.6601f, -0.112798f, -0.379202f, -0.228558f, 0.615611f, -0.0327493f, 0.594717f, 0.318287f, 0.0584771f, 0.0113252f, -0.144715f, -0.301842f, -0.0705235f, 0.0115849f, 0.131159f, 0.670893f, 0.168075f, -0.0718182f, 0.0903675f, -0.353166f, 0.161096f, -0.0640814f, 0.362689f, 0.175512f, -0.473472f, 0.270516f, -0.0792066f, -0.0256601f, -0.0171877f, -0.120534f, -0.113002f, 0.357678f, 0.161182f, -0.0263743f, -0.923133f, 0.463269f, 0.772355f, 0.0742514f, 0.00882856f, 0.063145f, 0.109518f, -0.0389513f, 0.0758492f, -0.0484083f, -0.14761f, -0.122375f, 0.0561956f, -0.150992f, -0.0506205f, 0.522672f, -0.075867f, 0.156564f, 0.120401f, -0.370186f, -0.450635f, -0.100374f, -0.0106076f, -0.0834781f, 0.0691193f, -0.0671956f, 0.11691f, 0.0368327f, 0.0432756f, -0.205644f, 0.0410307f, -0.0199087f, -0.427719f, -0.293893f, 0.468435f, -0.0095345f, -0.198647f, -0.144639f, 0.468013f, -0.247251f, 0.0817541f, -0.216556f, 0.138428f, -0.134626f, 0.798388f, 1.2151f, 0.0627166f, 0.0323023f, -0.468217f, 0.213002f, 0.482848f, 0.0785823f, -0.155659f, 0.0957937f, 0.175202f, 0.53568f, -0.0522815f, 0.199507f, 0.438776f, 0.0555042f, -0.186707f, 0.738733f, 0.198786f, -0.379305f, -0.21661f, 0.276172f, 0.111102f, -0.187843f, 0.00667934f, 0.479794f, 0.417874f, -0.0321797f, 0.113586f, 0.149764f, 0.344401f, 0.0596981f, -0.0722722f, -0.144758f, 0.216975f, -0.273642f, -0.05668f, -0.174795f, 0.315556f, -0.0698253f, -0.0174929f, 1.22012f, 0.298247f, -0.0437427f, 0.0571144f, -0.0448819f, -0.035783f, 0.341813f, -1.44398f, -0.932115f, 0.0554499f, 0.139797f, 0.0454919f, 0.101146f, -0.0365573f, 0.0181533f, -0.072497f, 0.00469406f, 0.114721f, -0.0307393f, -0.0595061f, -0.107221f, -0.0190126f, -0.066591f, 0.0274221f, -0.220164f, 0.04476f, 0.0132432f, -0.033681f, -0.122918f, 0.129631f, 0.0465355f, 0.00490838f, -0.0404164f, 0.085287f, -0.19016f, -0.00529878f, 0.0815777f, 0.214508f, -0.0097201f, -0.014709f, 0.175969f, -0.284429f, -0.138555f, 0.24701f, -0.0639662f, -0.627076f, -0.192857f, 0.721998f, -0.226272f, -0.287441f, 0.163892f, -0.434394f, 0.134582f, 0.346779f, 0.139164f, 0.0617441f, 0.15026f, 0.0976386f, 0.0772374f, -0.241325f, -1.20489f, 0.231982f, -0.324956f, -0.00869559f, 0.629038f, 0.00517482f, -0.000377918f, -0.0204305f, 0.210397f, 0.106963f, -0.231252f, -0.226723f, -0.0227848f, -0.049826f, 1.16369f, -0.050116f, -0.271526f, 0.328031f, -0.205096f, -0.363005f, -0.214108f, 0.225625f, -0.539605f, 0.0983158f, -0.619605f, -0.0497222f, -0.251876f, 0.0436864f, -0.160641f, 0.0571772f, 0.272138f, 0.0668712f, -0.430683f, -0.0100436f, 0.295768f, 0.298574f, -0.106221f, -0.260428f, -0.177709f, 0.0896013f, 0.053705f, 0.0500741f, 0.131009f, -0.181435f, -0.416209f, -0.257817f, 0.266792f, 0.113934f, 0.289465f, -0.150348f, 0.156032f, -0.194724f, -0.663587f, -0.254988f, 0.0849075f, -0.0868606f, -0.444052f, -0.223751f, -0.276668f, 0.0910332f, -0.210636f, 0.129256f, 0.258805f, 0.10269f, -0.286526f, -0.00178165f, 0.563636f, 0.429938f, -0.0224727f, 0.0574613f, 0.05257f, 0.0964023f, -0.0647819f, 0.00682808f, 1.0809f, -0.843355f, -0.764512f, 0.568327f, -0.154132f, 0.299537f, 0.299945f, 0.544647f, 0.208732f, 0.429021f, 0.692963f, -0.0132254f, -0.315425f, -0.0306844f, 0.454138f, 0.0640088f, -0.0526967f, -0.0886315f, -0.353569f, -0.0445053f, 0.419271f, 0.0554374f, 1.36378f, 0.0733646f, -0.150825f, -0.0180057f, -0.497634f, 0.0108371f, -0.0605194f, 0.196103f, -0.413485f, 0.104696f, -0.150669f, 0.125607f, 0.66632f, 0.105853f, 0.603983f, -0.0469635f, -0.536611f, 0.324353f, 0.0555507f, -0.0131337f, -0.187258f, -0.111389f, -0.122898f, 0.137639f, 0.183434f, -0.012268f, 0.343272f, -0.128094f, 0.901428f, -0.159127f, 0.281001f, 0.201204f, -0.383114f, -0.204803f, -0.02333f, 0.0352839f, 0.118129f, -0.282447f, -0.0108675f, -0.0391744f, -0.229019f, 0.0577521f, 0.116441f, 0.0644183f, 0.427821f, -0.704257f, 0.524999f, 0.186882f, -0.127407f, -0.35676f, 0.0595068f, 0.115227f, 0.0461664f, -0.142496f, -0.00631152f, -0.0108409f, -0.481236f, -0.0852718f, -0.376636f, 0.525184f, -0.273659f, 0.121326f, 0.472309f, -0.261966f, 0.0891272f, 0.0111846f, 0.253588f, -0.597467f, 0.0274354f, -0.116376f, 0.18483f, -0.381528f, -1.08966f, 0.220949f, 0.0125376f, -0.159113f, -0.607749f, -0.117129f, 0.0208151f, -0.0192488f, 0.965594f, 0.0103654f, 0.122626f, 0.27669f, 0.308212f, 0.41214f, -0.17695f, 0.457152f, -0.186629f, -0.811885f, -0.450484f, 0.326845f, -0.313783f, -0.0318016f, -0.0703636f, -0.348998f, 0.401331f, -0.0972392f, -0.0138799f, 0.941508f, 0.183815f, -0.368143f, 0.348649f, 0.34287f, -0.329698f, 0.971174f, -0.38763f, 0.270437f, -0.177012f, -0.503141f, -0.464137f, -0.166893f, -0.128612f, -0.233088f, -0.447929f, 0.283954f, 0.091494f, 0.468883f, -0.17161f, 0.414808f, -0.156788f, -0.0546122f, 0.149743f, 0.149753f, 0.164002f, 0.338386f, 0.306504f, -0.636032f, 0.220797f, 1.17419f, 0.228991f, 0.207466f, 0.34877f, -0.215867f, -0.11421f, 0.0348584f, -0.292257f, -0.929841f, -0.0867478f, 0.343753f, -0.313036f, 0.0911876f, -0.065675f, 0.277021f, 0.174759f, -0.0565729f, 0.20129f, -0.183456f, 0.0117971f, -0.288494f, -0.102646f, -0.242777f};
+  model->setOperandValue(op38, op38_init, sizeof(float) * 512);
+  static float op40_init[] = {6.42744f, 0.0321568f, -0.000620484f, 1.38238f, 0.80865f, -0.00817357f, -0.0552231f, 0.722048f, -0.0648024f, 0.00133108f, -0.0215043f, -0.0571425f, 1.02867f, 1.70436f, -0.3152f, 0.00116053f, 0.952789f, -0.00285661f, 0.684438f, -0.342237f, 0.47185f, -0.382995f, -1.09887f, 0.927754f, -0.395105f, 0.399458f, 1.70644f, 1.26431f, -0.628364f, -0.0923156f, 0.128607f, 0.136128f};
+  model->setOperandValue(op40, op40_init, sizeof(float) * 32);
+  static float op41_init[] = {-0.213624f, 0.138209f, 0.0335167f, 0.0765658f, -0.469466f, -0.273326f, -0.00221819f, -0.295019f, 0.0829199f, -0.0548812f, -0.490404f, -0.00631009f, 0.14766f, -0.322987f, -1.15481f, 0.0922192f, -0.518827f, 0.0107877f, -0.141691f, -0.281104f, -0.444652f, -0.0437552f, -0.282668f, -0.0346714f, -0.304982f, 0.655019f, 0.0312901f, 0.236608f, -0.0684982f, -0.0444543f, 0.948018f, 0.33508f, -1.01091f, -0.96846f, 0.358376f, -0.314516f, -0.607375f, 0.582129f, 1.09556f, 0.493909f, 1.29421f, 1.0163f, 0.364732f, 0.341571f, 0.0880636f, -0.351738f, -2.30092f, -0.150112f, -0.960678f, 0.297181f, -0.0706625f, -0.19208f, -0.0957771f, 0.309638f, 0.0750161f, -0.780806f, 0.511076f, 0.773651f, -0.396476f, -0.540966f, 0.0747744f, 0.438967f, 0.0576069f, -0.240702f, 0.965804f, 0.444225f, -0.236452f, -0.0359711f, -0.576393f, 0.191653f, 0.25384f, 0.403406f, 0.785365f, 0.791804f, -0.236619f, -0.159129f, -0.0397893f, -0.0192526f, 0.639548f, -0.151068f, -0.708892f, 0.0186311f, -0.169363f, 0.641973f, 0.835608f, -0.0062986f, -0.0722358f, -0.280815f, 0.528226f, 0.234705f, -0.0855388f, 0.0502671f, -0.0663052f, -0.0660385f, -1.09458f, -0.30802f, -0.352286f, -0.541121f, 0.0738992f, -0.600995f, -0.85345f, -0.640068f, 0.35932f, -0.94734f, -0.750374f, 0.0843853f, 0.533934f, 0.342629f, -0.285891f, -0.362343f, 2.27695f, -0.178586f, -0.146698f, 0.051864f, -1.63582f, -0.498046f, 0.439183f, 0.25438f, 0.860595f, 0.605293f, -0.487595f, 0.693431f, 0.0504463f, 0.0676578f, 0.491436f, 0.00781199f, 0.970881f, 1.24158f, 0.522268f, -1.66232f, 0.596904f, -0.771637f, -0.314527f, -0.0736619f, 0.477234f, -0.26977f, -1.32936f, 0.571956f, 0.401798f, 0.163323f, -0.48078f, -0.199079f, 3.68406f, 0.0363556f, -0.0116286f, 0.683029f, -0.411191f, -0.223925f, -2.16462f, 0.863175f, -0.0633758f, -0.104411f, 0.697775f, -0.0682223f, -0.170274f, -0.798971f, 0.543116f, -0.577803f, -0.264083f, -1.29701f, 1.3298f, 2.19506f, 0.129616f, -0.0882273f, 0.387708f, 0.835795f, -0.44719f, 0.727769f, -0.154647f, -1.36135f, -0.1804f, -0.972617f, -0.102816f, 0.0446513f, 0.00496158f, 0.254847f, -0.289563f, -0.1219f, 0.715903f, 1.20232f, 0.50676f, -0.160549f, 0.0658346f, -0.500259f, -0.18733f, -0.553927f, -0.327592f, -0.0115506f, -0.0648266f, 1.02016f, -0.445415f, 0.147632f, -2.72305f, -1.02403f, 0.091488f, 0.389223f, -0.340593f, 0.0441604f, -0.0813384f, -1.26204f, 0.451759f, 0.109403f, 0.163282f, -0.108921f, -0.513226f, 0.00951998f, -0.962222f, -0.0764701f, 0.417888f, -0.0341903f, -0.215405f, -0.135682f, 0.448615f, -0.0672329f, 0.319827f, 0.36181f, -0.0126959f, 0.120521f, -0.410612f, -0.41408f, 0.0858084f, -0.0372158f, 0.354041f, 0.407449f, -3.48641f, 0.715232f, -0.0997449f, -0.011738f, 0.39694f, -0.472036f, -0.731723f, 0.364184f, -0.032735f, -0.651235f, 0.316316f, 0.617327f, -0.563622f, -0.31476f, -1.77474f, 0.888013f, 0.460156f, 0.208053f, 0.928476f, -0.262615f, -0.0164628f, -0.125161f, 1.41364f, 0.104717f, -0.105201f, -0.949609f, -0.225559f, -0.34806f, 0.382115f, -0.0615256f, -0.466405f, -0.549317f, -0.837217f, 0.954736f, -0.138345f, -0.148199f, 0.526336f, 0.0140706f, -0.162999f, 0.511944f, -0.274986f, -0.340369f, -0.046259f, 0.346976f, -0.0313568f, 0.228732f, -0.0489806f, 0.223879f, 0.562803f, 0.0103503f, 0.0799935f, 0.558369f, -0.171246f, 0.171886f, 0.166322f, 0.238082f, 0.673778f, -0.77636f, -0.163403f, -0.0436278f, 0.141954f, -0.0472412f, -0.204982f, -0.0389803f};
+  model->setOperandValue(op41, op41_init, sizeof(float) * 288);
+  static float op43_init[] = {0.3436f, -1.04269f, 0.225925f, -0.537982f, 1.08172f, -0.204524f, 0.172497f, 0.674492f, 0.456061f, 0.668595f, -0.481863f, -0.133324f, 1.32533f, 0.993317f, 0.748185f, -0.195914f, -0.0134926f, 0.688711f, 0.511972f, 0.636836f, 0.279939f, 0.321013f, 0.876996f, -0.260606f, -0.451471f, 0.190377f, 0.252418f, -0.148638f, -0.0716072f, -0.423855f, -0.435216f, 0.208755f};
+  model->setOperandValue(op43, op43_init, sizeof(float) * 32);
+  static float op44_init[] = {-0.997767f, -0.138253f, 0.257102f, 0.198314f, -0.288036f, 0.000366378f, 0.179375f, 0.0428916f, 0.37398f, 0.200809f, 0.0708428f, -0.0552363f, 0.2561f, 0.0673435f, 0.214471f, -0.273985f, -0.0436041f, -0.280273f, -0.178842f, -0.125207f, -0.0355889f, 0.115009f, 0.378167f, -0.322478f, -0.228919f, -0.304841f, 0.0869207f, 0.00978466f, 0.208113f, 0.0447535f, 0.0834528f, -0.00224961f, 0.943316f, 0.0268451f, -0.0400112f, 0.269991f, 0.128187f, 0.0418591f, -0.183381f, 0.0012768f, 0.0109702f, -0.111818f, -0.111524f, -0.184526f, -0.0207905f, 0.370109f, -0.0994838f, -0.145518f, -0.157454f, 0.0129944f, 0.108774f, -0.0487951f, -0.0819522f, 0.0119885f, 0.0174093f, 0.28421f, 0.646448f, -0.075307f, 0.0465415f, 0.0487265f, 0.0308747f, -0.069307f, -0.053984f, -0.0313228f, -0.509124f, -0.064913f, -0.112027f, 0.208081f, -0.135588f, 0.159906f, -0.178343f, -0.0181903f, 0.0335903f, -0.150214f, 0.303698f, 0.427552f, -0.435008f, -0.224716f, -0.19117f, 0.210815f, 0.065515f, 0.421522f, -0.221878f, 0.0720313f, 0.0249512f, -0.0440652f, 0.154486f, 0.431391f, 0.12956f, -0.0195364f, -0.0706577f, -0.0933352f, 0.0266882f, -0.0467516f, 0.0801773f, -0.0014517f, -0.625292f, 0.712272f, -0.24107f, -0.305843f, 0.0221034f, -0.0928243f, 0.154919f, 0.376946f, -0.126919f, 0.720612f, -0.188993f, -0.186095f, 0.00157104f, 0.188757f, 0.353384f, -0.132509f, -0.0108723f, 0.387704f, 0.325389f, -0.00314436f, -0.345477f, 0.0887929f, 0.169411f, -0.109333f, -0.265296f, 0.0980931f, 0.359309f, 0.112137f, 0.0153721f, -0.257252f, 0.0359218f, 0.118771f, -0.349838f, -0.374118f, -0.146685f, 0.33613f, -0.0721935f, 0.193789f, 0.0234959f, -0.290478f, 0.0641786f, -0.218367f, -0.270102f, 0.67599f, -0.35043f, -0.0972091f, -0.13407f, -0.388246f, 0.113249f, 0.318534f, -0.305088f, 0.181331f, 0.188322f, -0.0540989f, -0.0382463f, -0.239647f, 0.221239f, -0.0593219f, -0.260486f, -0.0336027f, -0.0638945f, 0.116237f, 0.081521f, 0.0775405f, 0.0944801f, 0.25328f, -0.122297f, 0.174045f, -0.0975344f, 0.519531f, 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0.21933f, -0.00990585f, 0.0960152f, 0.461456f, 0.206761f, -0.132683f, -0.172062f, 0.105766f, -0.0173104f, -0.373499f, -0.106453f, -0.704373f, 0.0746062f, -0.165774f, 0.319425f, -0.137625f, -0.0313657f, 0.0443941f, -0.0456422f, -0.104721f, -0.0697701f, 0.0331451f, -0.00422528f, 0.0029677f, 0.852368f, -0.0198872f, -0.0900668f, -0.101453f, -0.137428f, 0.129322f, 0.17863f, -0.247587f, -0.118253f, -0.112031f, 0.175801f, -0.134212f, -0.318574f, -0.224928f, 0.077698f, 0.0958551f, -0.0497655f, 0.138903f, 0.0930927f, -0.0231865f, -0.0319309f, 0.0748791f, -0.0068748f, 0.215623f, 0.0509231f, -0.170587f, -0.0273425f, -0.113463f, 0.221946f, -0.234851f, -0.129824f, 0.0869991f, 0.3187f, -0.183724f, -0.0374509f, -0.143004f, 0.0116296f, 0.27605f, 0.533397f, -0.356008f, -0.258424f, 0.411369f, 0.0760917f, -0.319263f, 0.193123f, -0.0324642f, 0.249571f, -0.0725184f, -0.199219f, -0.421124f, -0.273295f, -0.0909357f, -0.15422f, 0.144798f, -0.0767782f, -0.178438f, 0.0840012f, -0.138935f, 0.26065f, -0.0501507f, 0.114025f, -0.245332f, 0.183401f, -0.109097f, 0.0802959f, 0.22644f, 0.0158754f, 0.079201f, 0.168063f, -0.0962881f, -0.177862f, -0.00585562f, 0.122612f, 0.0474541f, -0.115574f, -0.13249f, 0.0516973f, 0.0379483f, 0.205485f, 0.0571525f, 0.138432f, 0.167085f, 0.149931f, -0.30555f, -0.154863f, 0.273669f, -0.269363f, -0.277303f, -0.117719f, -0.130056f, 0.16254f, 0.0178595f, 0.0099221f, -0.0821058f, -0.832783f, -0.247802f, 0.000437512f, -0.0718738f, 0.105544f, -0.0859228f, -0.0781981f, -0.0152479f, 0.0577682f, 0.0432432f, 0.0893925f, -0.0169638f, 0.0401341f, -0.137957f, 0.0371843f, 0.00780299f, 0.135383f, -0.0905592f, 0.248079f, 0.043501f, -0.20674f, -0.120261f, -0.170613f, -0.073779f, -0.0261543f, -0.0111784f, -0.108507f, 0.106975f, 0.0158704f, -0.0650415f, 0.0471562f, 0.108786f, -0.0010104f, -0.0342219f, 0.293312f, 0.22832f, 0.277243f, 0.294822f, 0.0161702f, -0.0171233f, -0.234202f, -0.0539014f, 0.108611f, -0.236384f, 0.140614f, 0.0165573f, 0.0789557f, -0.0727585f, 0.77537f, -0.185072f, 0.00318486f, -0.210554f, 0.172684f, 0.0692409f, -0.161854f, -0.0680684f, -0.0440112f, 0.392964f, 0.213336f, -0.0669562f, -0.0180805f, -0.284579f, -0.229557f, -0.0504555f, -0.0627434f, -0.0186419f, -0.239511f, 0.392045f, -0.194569f, 0.0204815f, 0.185961f, -0.148468f, -0.249575f, 0.303668f, 0.108663f, -0.149364f, 0.084945f, -0.339009f, -0.391481f, -0.139502f, 0.174247f, 0.0906451f, 0.234767f, 0.0705702f, -0.256438f, -0.290319f, 0.027072f, -0.150724f, 0.174573f, -0.0824633f, 0.538801f, -0.0963668f, 0.321383f, 0.316815f, -0.0753205f, 0.286798f, 0.340526f, 0.333932f, -0.0500382f, -0.0795599f, 0.0308395f, -0.092027f, -0.0163176f, 0.0254774f, 0.300869f, 0.182059f, -0.0667341f, -0.0822605f, 0.1041f, 0.32807f, 0.0277766f, -0.0633457f, 0.00799717f, 0.190551f, -0.0428556f, 0.0791671f, -0.0787359f, 0.105112f, -0.141626f, -0.129662f, -0.0928458f, 0.0939267f, 0.319918f, 0.00197538f, -0.0705373f, 0.00349081f, -0.0381092f, 0.106843f, -0.115107f, 0.14461f, -0.0941022f, 0.104072f, 0.0441417f, -0.101069f, -0.036769f, 0.0614558f, -0.0730298f, 0.0384882f, 0.0669455f, -0.0696751f, 0.517891f, 0.0550475f, 0.0723489f, 0.247997f, 0.0756446f, -0.286603f, -0.129575f, 0.173436f, 0.105001f, -0.00469504f, -0.0901384f, -0.253675f, 0.20491f, -0.0585889f, 0.295482f, 0.170905f, -0.281103f, 0.145994f, 0.0866278f, 0.0307803f, -0.0569594f, 0.0426422f, 0.360389f, 0.55195f, 0.09593f, 0.397124f, 0.191536f, -0.211722f, 0.234034f, -0.0784443f, -0.378966f, -0.190407f, -0.00750651f, -0.66388f, 0.565919f, -0.0253019f, -0.421638f, -0.0402029f, 0.0754944f, -0.206012f, 0.183688f, 0.337428f, 0.0737486f, 0.0190236f, -0.232534f, -0.195353f, 0.125169f, 0.0331415f, -0.356153f, 0.0242174f, -0.021123f, -0.142455f, 0.326315f, 0.0163432f, -0.0150546f, 0.051416f, -0.283135f, -0.0462949f, 0.0929148f, 0.0121951f, 0.132771f, -0.013616f, 0.164926f, 0.253921f, -0.139483f, -0.118191f, 0.00735195f, -0.0405987f, -0.184553f, 0.324665f, 0.303452f, -0.458574f, 0.250838f, -0.27917f, -0.130921f, 0.0916452f, 0.185078f, 0.24469f, -0.301072f, -0.370228f, 0.178628f, 0.145236f, 0.183097f, 0.150434f, 0.086305f, 0.0389938f, 0.875306f, -0.00167366f, 0.045869f, -0.237671f, 0.0890955f, 0.0192966f, 0.124476f, 0.0126363f, 0.0490718f, 0.0615049f, 0.105296f, -0.108085f, -0.313966f, 0.426299f, 0.124506f, -0.0795267f, 0.174412f, 0.272431f, 0.124504f, 0.0739427f, -0.0700362f, 0.111758f, 0.00671678f, -0.107815f, -0.0662027f, -0.0918283f, -0.102847f, -0.0980065f, -0.0483559f, -0.120665f, 0.0151454f, 0.00351556f, -0.488797f, 0.0444841f, -0.253477f, -0.28651f, 0.00837357f, 0.0809181f, -0.0199791f, -0.0799819f, 0.0997407f, 0.235679f, 0.97399f, -0.167017f, -0.122257f, 0.597685f, 0.0827836f, 0.119421f, 0.243396f, -0.0572792f, -0.0470654f, 0.120889f, -0.0969786f, -0.0506503f, 4.19253e-05f, -0.0744475f, 0.135971f, -0.0525192f, 0.056829f, -0.148527f, 0.191463f, 0.116223f, -0.0730916f, 0.0129901f, 0.350111f, 0.135758f, 0.152902f, 0.485041f, 0.0448233f, -0.111131f, -0.233994f, -0.410416f, 0.243623f, 0.138663f, -0.00277319f, 0.227577f, 0.0683518f, -0.210476f, 0.226312f, 0.21227f, -0.0362238f, 0.206224f, -0.0785877f, -0.20799f, -0.0422812f, 0.225806f, -0.347121f, -0.154161f, -0.15515f, 0.109949f, 0.386982f, -0.399289f, -0.374705f, -0.193131f, 0.123094f, -0.198874f};
+  model->setOperandValue(op44, op44_init, sizeof(float) * 1024);
+  static float op46_init[] = {0.0353964f, -0.498098f, -0.0637909f, 1.46605f, 0.0985285f, 1.55767f, 1.67486f, 2.08488f, 1.24002f, 1.53329f, -0.0350761f, 0.185034f, 3.21054f, 0.0545383f, 0.137788f, 1.5124f, -0.0263243f, 1.91751f, 1.16072f, 1.34599f, 0.0323791f, -0.516612f, 3.40556f, -0.203818f, 0.916529f, 1.36208f, 1.47077f, 1.58338f, 0.0124303f, 0.116432f, -0.00318241f, -0.000725091f};
+  model->setOperandValue(op46, op46_init, sizeof(float) * 32);
+  static float op47_init[] = {0.156179f, 0.740114f, 0.146084f, -0.180304f, 0.135386f, -0.112967f, -0.159752f, -0.0912054f, -0.16292f, -0.170387f, 0.184984f, 0.534837f, -0.222242f, 0.0663174f, 0.322167f, -0.246094f, 0.225455f, 0.0679039f, -0.139034f, 0.0039652f, 0.096747f, 0.0668452f, -0.101501f, 0.184103f, -0.189683f, -0.181256f, -0.226854f, -0.115267f, 0.117309f, 0.212836f, 0.0102671f, -0.00837151f, 0.205307f, -0.118807f, 0.473089f, -0.27765f, 0.0257295f, -0.295094f, -0.306755f, -0.196187f, -0.151386f, -0.190512f, 0.279854f, 0.368561f, -0.512608f, 0.123368f, 0.785377f, -0.338917f, 0.246306f, -0.39264f, -0.164611f, -0.108249f, 0.0665555f, 0.271457f, -0.442514f, 0.309919f, -0.24764f, -0.256974f, -0.244039f, -0.130222f, 0.144196f, 0.288034f, 0.16275f, -0.0276356f, 0.0973298f, 0.172178f, 0.361618f, -0.159499f, -0.147958f, -0.236342f, -0.197888f, -0.139265f, -0.0194431f, -0.0795726f, 0.154615f, -0.0446899f, -0.209686f, 0.102243f, 0.751226f, -0.128102f, 0.17202f, -0.496175f, -0.0630421f, -0.141689f, -0.0395602f, 0.209026f, -0.399518f, 0.229802f, -0.11026f, -0.0416616f, -0.0478338f, -0.0866013f, 0.0788821f, 0.145776f, 0.163885f, -0.00528089f, 0.322996f, 0.674345f, -0.250062f, -0.266435f, 0.300283f, -0.245216f, -0.171486f, -0.218911f, -0.278993f, -0.238749f, 0.188046f, 0.398108f, -0.367571f, 0.161006f, -0.251809f, -0.283983f, 0.308162f, -0.147899f, -0.256196f, -0.028727f, 0.148012f, 0.237726f, -0.543712f, 0.184632f, -0.229882f, -0.0937904f, -0.23355f, -0.230001f, 0.159108f, 0.186345f, 0.195609f, 0.129094f, 0.489674f, -0.0359821f, 0.287801f, -0.349692f, 0.310358f, -0.550261f, -0.432363f, -0.390494f, -0.310232f, -0.378422f, 0.330258f, 0.210456f, -0.7278f, 0.343291f, -0.112808f, -0.449118f, 0.422889f, -0.56646f, -0.363238f, -0.285837f, 0.386119f, 0.402224f, -0.728247f, 0.29205f, -0.396501f, -0.402005f, -0.351576f, -0.278841f, 0.310083f, 0.328826f, 0.322681f, 0.242448f, 0.230535f, -0.205397f, 0.441373f, -0.201717f, 0.0573488f, -0.362298f, -0.335419f, -0.231367f, -0.0660249f, -0.192796f, 0.201418f, -0.0941352f, -0.462079f, 0.230986f, 0.0567214f, -0.278781f, 0.272637f, -0.405269f, -0.192166f, -0.325699f, 0.228205f, 0.318716f, -0.363493f, 0.188267f, -0.245576f, -0.301783f, -0.107653f, -0.160302f, 0.208713f, 0.167456f, 0.19856f, 0.195301f, 0.167139f, 0.639249f, -0.396651f, -0.173979f, 0.170304f, -0.206958f, -0.0727969f, -0.147468f, -0.12681f, -0.162747f, -0.00979657f, -0.0850251f, -0.12852f, 0.13592f, -0.436702f, -0.143019f, 0.110177f, -0.261806f, -0.2219f, -0.0652627f, 0.0486492f, 0.267457f, -0.252875f, 0.0509038f, -0.162644f, 0.0361367f, -0.100097f, -0.111549f, 0.0648925f, -0.0166337f, 0.217277f, 0.200447f, 0.341306f, -0.348518f, -0.0825517f, -0.17013f, 0.328561f, -0.346055f, -0.274162f, -0.227547f, -0.221071f, -0.312126f, 0.0529024f, -0.446766f, -0.346986f, 0.294348f, -0.709363f, -0.258129f, 0.174978f, -0.334403f, -0.354706f, -0.246383f, 0.300609f, 0.287097f, -0.326242f, -0.0250746f, -0.290678f, -0.221031f, -0.200902f, -0.185348f, 0.197853f, 0.0334783f, 0.239879f, 0.349207f, 0.202404f, -0.169038f, 0.219634f, -0.0465216f, 0.240188f, -0.12988f, -0.230147f, -0.162086f, -0.0892766f, -0.219808f, 0.0623033f, -0.560078f, -0.357664f, 0.18296f, -0.540818f, -0.205105f, 0.0497816f, -0.0818515f, -0.224175f, -0.22876f, 0.27044f, 0.203257f, -0.0265541f, -0.0891287f, -0.109839f, -0.326671f, -0.0904553f, -0.116456f, 0.158232f, 0.00285579f, 0.0707352f, 0.215775f};
+  model->setOperandValue(op47, op47_init, sizeof(float) * 288);
+  static float op49_init[] = {0.473197f, -1.08994f, 0.157816f, 0.475708f, 1.16729f, 1.19871f, 0.434978f, 0.260128f, 0.362141f, 0.81847f, 0.155825f, 1.22273f, -0.382775f, 0.24913f, 0.492578f, -0.541874f, 2.08853f, 2.6003f, -0.14665f, 1.43908f, -0.740456f, -0.0744309f, -0.208456f, 0.235227f, 1.44235f, 1.09803f, -0.430158f, 0.810813f, 0.336378f, 0.0121858f, 0.65212f, 0.865938f, 0.137012f, 0.389252f, -0.54846f, -0.951355f, 1.09939f, 0.120903f, 0.0200256f, 0.277682f, -0.0387516f, 0.193967f, 0.248117f, 1.22538f, 0.930871f, -0.169939f, -0.747988f, 0.66065f, -0.23336f, 1.11278f, 1.44047f, -1.61965f, 0.535887f, 2.11026f, 0.840902f, 0.677272f, 1.36815f, 0.758101f, -0.292219f, 0.202975f, -2.03518f, 1.01007f, 0.902706f, -0.218632f};
+  model->setOperandValue(op49, op49_init, sizeof(float) * 64);
+  static float op50_init[] = {0.0613606f, -0.553296f, 0.195442f, 0.267107f, 0.555671f, -0.10669f, -0.145497f, 0.0230295f, 0.0348993f, -0.179045f, 0.0174281f, -0.010889f, -0.0904074f, -0.0220914f, 0.0483935f, -0.0840004f, 0.0468793f, -0.0856841f, -0.00308835f, -0.301048f, -0.188984f, -0.135143f, 0.249993f, -0.0918953f, 0.0902932f, 0.0467749f, -0.00621833f, -0.0903459f, 0.186926f, -0.00039472f, -0.0259989f, 0.0783119f, -0.042534f, 0.215926f, 0.0965445f, 0.12098f, -0.0839443f, -0.0667839f, 0.163285f, 0.0395507f, 0.162628f, 0.0585461f, 0.0800772f, 0.212197f, 0.12528f, -0.223154f, 0.107762f, 0.145602f, 0.456506f, 0.0179339f, 0.250854f, -0.0810258f, 0.286478f, -0.222802f, 0.233478f, -0.151214f, 0.106238f, -0.0293863f, 0.158757f, -0.106969f, 0.0623353f, 0.0613231f, -0.195503f, -0.063429f, -0.437771f, -0.000534805f, 0.162869f, 0.168638f, -0.052143f, 0.176157f, 0.213678f, -0.247235f, -0.0893308f, 0.152861f, 0.000336537f, 0.339348f, 0.225011f, 0.0203482f, -0.160058f, 0.488881f, -0.20454f, 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-0.162631f, -0.0215861f, -0.153888f, 0.387294f, -0.00764126f, 0.0608081f, 0.47267f, 0.0546126f, -0.0603822f, -0.368747f, -0.193413f, 0.413439f, 0.250573f, -0.0919951f, -0.205062f, -0.378597f, -0.103693f, -0.0364686f, 0.024476f, -0.136754f, 0.0202888f, -0.0178216f, 0.125527f, -0.597289f, 0.261673f, -0.191381f, 0.0123846f, 0.267765f, -0.0545825f, -0.112335f, 0.257105f, -0.1548f, 0.000756895f, -0.000135195f, -0.0493844f, 0.0711406f, 0.201368f, -0.126064f, 0.476796f, -0.133337f, 0.313014f, -0.176392f, 0.0668156f, 0.183926f, 0.0512879f, 0.0928857f, 0.41671f, -0.0552113f, -0.333994f, -0.269322f, 0.367407f, -0.0710696f, 0.213496f, 0.130636f, 0.0498f, 0.590488f, -0.168079f, 0.056651f, -0.0263843f, 0.129157f, -0.116934f, 0.18456f, 0.164398f, 0.0416276f, 0.0862844f, -0.0460175f, -0.0476335f, -0.266252f, -0.154253f, 0.0745028f, -0.31326f, 0.107256f, 0.0455637f, -0.142944f, 0.0386776f, -0.0196847f, -0.000644906f, 0.0109701f, -0.00890023f, 0.0802168f, -0.126913f, -0.10912f, -0.0567636f, -0.107934f, 0.179347f, 0.241797f, 0.638128f, -0.130217f, 0.197146f, -0.211336f, -0.0737465f, 0.111125f, -0.111334f, 0.178715f, 0.595705f, -0.00355858f, -0.280972f, 0.288604f, -0.246517f, 0.104765f, 0.23599f, 0.0626923f, 0.431966f, -0.0706402f, 0.444929f, -0.0391279f, 0.214596f, 0.0142286f, -0.127732f, 0.101488f, 0.167395f, 0.189494f, 0.111607f, 0.0246908f, 0.0359995f, 0.120173f, -0.045409f, 0.256838f, -0.0781464f, 0.00970439f, -0.0484562f, 0.247528f, 0.0649018f, -0.158475f, 0.139769f, -0.0900704f, -0.371826f, 0.0790552f, -0.37067f, -0.208308f, -0.211739f, -0.282507f, -0.270256f, 0.205481f, -0.503264f, 0.270588f, -0.0385014f, -0.26717f, 0.128288f, 0.362188f, 0.19137f, -0.247913f, -0.153628f, -0.167465f, 0.814905f, -0.0979974f, 0.0865845f, 0.386866f, -0.37493f, -0.129166f, 0.120307f, 0.435242f, -0.218038f, 0.0716689f, -0.34914f, -0.152382f, 0.062478f, -0.114676f, -0.23435f, 0.0159545f, 0.171189f, -0.00842011f, 0.131103f, -0.262238f, -0.215891f, -0.102031f, 0.0864728f, 0.0985599f, 0.164302f, -0.0653579f, 0.320503f, -0.556148f, 0.536547f, -0.0820048f, 0.14663f, 0.397948f, 0.0787573f, -0.748766f, -0.129899f, -0.474231f, 0.123753f, 0.27761f, 0.0410578f, -0.543769f, 0.339079f, 0.0367555f, -0.2571f, -0.0964757f, -0.0154511f, 0.00377123f, -0.113003f, 0.0291767f, -0.257889f, 0.124925f, 0.0266814f, 0.114631f, 0.256503f, -0.0293197f, 0.0422625f, -0.00998103f, 0.0881326f, 0.104533f, -0.125819f, -0.243805f, -0.0148122f, 0.51277f, -0.197339f, 0.257117f, 0.144041f, 0.245811f, -0.160956f, 0.305854f, 0.0214668f, 0.308474f};
+  model->setOperandValue(op50, op50_init, sizeof(float) * 2048);
+  static float op52_init[] = {2.09374f, -0.224081f, -0.26393f, -0.213004f, 0.148951f, 1.95099f, 0.00966659f, 0.00670771f, 0.751565f, 0.15019f, -0.259461f, -0.210099f, 0.114971f, 0.522198f, 0.00564572f, 0.242789f, 1.04283f, 0.983166f, -0.110847f, -0.112012f, -0.707376f, 0.0605569f, 0.967749f, 1.54696f, 2.39179f, -0.0660475f, -1.02395f, 0.663784f, 0.0684345f, 0.835432f, -0.0555699f, -0.595563f, 1.63423f, -0.275387f, -0.57632f, -0.448239f, 1.57884f, -0.854438f, -0.00365815f, 0.157436f, -0.458565f, 0.175284f, -0.240444f, -0.955042f, -0.158954f, 0.0995562f, 1.09967f, -0.109549f, 1.181f, -0.130396f, -0.246582f, -0.121111f, -0.0830782f, -0.801972f, -0.0843711f, -0.0243731f, -0.21979f, 0.114646f, -0.358143f, 0.00306739f, -0.00465024f, 1.03416f, -0.229731f, 1.37862f};
+  model->setOperandValue(op52, op52_init, sizeof(float) * 64);
+  static float op53_init[] = {-0.12698f, -0.238352f, 0.244215f, -0.458646f, 1.27555f, -0.421724f, 0.0884984f, -0.250955f, -0.158853f, -0.176467f, -0.0758706f, -1.31031f, -0.776091f, -0.753093f, -0.0744585f, 0.458402f, -0.386373f, -0.379819f, -0.205575f, -0.434537f, -0.528748f, 0.667563f, 0.197939f, -0.00334295f, -0.674948f, 0.0583558f, 0.349504f, 0.0669012f, -0.62573f, 0.0202494f, -0.851811f, 0.0796548f, -0.349216f, 0.336193f, 0.242802f, 0.410446f, 0.127221f, 0.337145f, -0.671162f, 0.550955f, -0.047319f, 0.60033f, 0.342804f, 0.128321f, -0.329242f, -0.581331f, -0.757822f, 0.260636f, 0.183208f, 0.0755782f, -0.0630638f, -0.328286f, 0.71131f, -0.747697f, -0.114446f, 0.878907f, -0.362007f, 0.567657f, -0.0426601f, -0.120681f, -0.158017f, -0.132928f, -0.0400564f, -0.119035f, -0.347841f, 0.27945f, 0.522869f, -0.318377f, -0.617688f, 0.00215388f, -0.288244f, -0.0643205f, -0.125579f, 0.0714863f, 0.491909f, -1.17593f, -0.790597f, 0.237053f, 1.10418f, 1.01839f, -0.588406f, -0.163287f, -0.00948245f, 0.0295395f, 0.0913539f, -0.597769f, -0.199139f, -0.736147f, -1.13063f, -0.966132f, 0.670015f, -0.384273f, -0.35121f, -0.452121f, 0.139313f, -0.752194f, -0.581573f, 1.20926f, 0.468125f, 0.0024432f, -0.864836f, 1.40619f, 0.248723f, -0.0319902f, 0.243259f, 0.719603f, 1.56375f, 0.582131f, 0.517324f, -0.558173f, -0.486479f, 0.240216f, -0.10745f, -0.600757f, -0.407625f, -0.026077f, 2.22213f, 0.964383f, -0.283648f, 0.242633f, -0.671491f, 0.247282f, 0.246633f, 0.569997f, -0.442304f, 0.711694f, 0.689518f, -0.270639f, -0.0341924f, 0.299518f, -0.221812f, 0.0267754f, -0.701543f, -0.256183f, -0.464542f, 0.533444f, 0.551868f, -0.156954f, -0.522106f, -0.947321f, -0.370692f, 0.302054f, -0.157298f, 0.220857f, -0.485616f, -0.304364f, 0.451741f, 0.226862f, 0.0889601f, -0.72402f, 0.0010362f, -0.0768618f, -0.602799f, -0.202045f, -0.731567f, 0.1843f, -0.019595f, -0.44772f, 1.08144f, -0.0849737f, -0.0383033f, 0.0770167f, 0.00544352f, -0.0513838f, 0.354596f, 0.803038f, 0.14348f, -0.586081f, 0.350211f, 0.445668f, -0.142114f, 0.559075f, -0.197881f, -0.485669f, 0.374767f, -0.529465f, -0.433189f, -0.381117f, 0.303766f, -0.0149781f, 0.259829f, 0.058601f, -0.273908f, -0.600653f, -0.189578f, -0.437372f, -0.0137133f, 0.325366f, -0.269418f, 0.337198f, 0.263951f, -0.216138f, -0.620022f, -0.112354f, 0.262422f, -0.0179674f, 0.942104f, 0.421509f, 0.458286f, -1.16175f, -0.0139678f, -0.103121f, -0.210449f, 1.87519f, 0.0331067f, -0.751383f, 0.222364f, 0.106374f, 0.0638171f, -0.167853f, 0.139778f, 0.38963f, 0.274968f, 0.155153f, -0.34655f, -0.0563739f, -0.261732f, 0.414308f, -0.593183f, -0.306091f, 0.042063f, 0.0501084f, -1.38946f, 0.40545f, -0.226405f, 0.00702765f, -0.194214f, 0.428538f, -0.455647f, 0.72176f, -0.497389f, 1.40647f, -0.173328f, 0.0971494f, 0.144964f, -0.0565212f, -0.0767172f, 0.505409f, 0.466856f, 0.226217f, -0.298469f, 0.587705f, -1.19975f, 0.451319f, -0.245376f, 0.0492834f, -0.227796f, 1.13696f, 0.20848f, 1.05685f, 0.305445f, -0.358505f, -0.297229f, -0.174603f, 0.0937863f, -0.118832f, -0.547926f, -0.233037f, 0.670064f, 0.432594f, 1.08319f, -0.0648255f, -0.242524f, -0.551126f, -0.997542f, -0.612246f, 0.784354f, 0.924871f, 0.0868394f, 0.00189777f, 0.451893f, -0.200028f, -0.456986f, 0.202478f, 0.358685f, 0.479158f, 0.923011f, 2.25015f, -0.577736f, -0.680415f, -0.405968f, 2.08862f, 1.7708f, -0.221745f, -0.668693f, -0.386576f, -0.0936857f, 0.880579f, -0.200297f, -0.182471f, 0.915206f, 0.561029f, -1.09806f, 0.738976f, 1.01242f, -0.84413f, 0.888704f, -0.0140932f, 0.683439f, 0.69737f, 0.909058f, -0.424791f, -0.723923f, 2.54434f, -0.459792f, 0.214831f, 0.538751f, 0.406171f, -0.164808f, 1.96384f, 0.426688f, -0.884862f, 1.96028f, 0.437135f, 1.31552f, 0.295632f, 1.20595f, -0.33993f, 0.41051f, -0.742935f, -0.528444f, -0.256337f, -0.165411f, -0.0731374f, -1.95086f, -1.16248f, -0.510701f, 1.78344f, 0.62322f, -0.397011f, -0.296941f, 0.519863f, 0.145054f, 0.773714f, 0.261809f, -0.121355f, -0.109046f, -0.255428f, -0.124878f, -0.544119f, 0.301598f, -1.87278f, -0.352883f, -0.0320303f, -0.502195f, 0.0743574f, 0.0359745f, 0.0942341f, -0.00728066f, 0.063997f, 0.687835f, 0.0469159f, -0.220356f, 0.361827f, 0.100022f, -0.168349f, -0.177127f, -0.83667f, 0.191707f, -0.584849f, -0.150654f, -0.402803f, -0.255429f, 0.212771f, 0.901497f, -0.422539f, -0.33554f, 0.158121f, -0.0110873f, -0.70106f, 0.84911f, -0.48385f, -0.34909f, -0.756153f, -0.127089f, -0.54675f, 0.233831f, -0.275361f, -0.0572444f, 0.524687f, 0.152529f, 0.0550876f, -0.103777f, -0.17179f, 0.0959539f, 0.336758f, 0.0242661f, 0.209466f, -0.532314f, -0.381342f, 0.881586f, 0.262059f, -0.239896f, -0.112729f, -0.240745f, 0.524678f, 0.635937f, 0.0749855f, -0.404162f, -0.219252f, 0.298954f, -0.362545f, -0.0425563f, 1.14806f, -0.497664f, -0.489604f, -0.541267f, 0.0938686f, -0.0829758f, -0.302335f, -0.354915f, -0.0567779f, 0.548323f, 0.0893113f, -0.171931f, 0.221819f, -0.444963f, -0.13688f, 0.0294968f, 0.61855f, 0.0477813f, -0.647976f, 0.134058f, 1.16525f, -0.0321262f, -0.360732f, -0.268031f, 0.0867808f, -0.28502f, 0.954255f, -0.158386f, -0.695564f, -0.244045f, 0.650121f, -0.532843f, 0.225883f, -1.0656f, 0.730367f, -0.108003f, 0.475861f, 0.427236f, -0.0965219f, 0.131015f, -0.93574f, -0.0239511f, -0.571369f, 0.214945f, 0.668269f, -0.264419f, 0.574199f, 0.209625f, 1.06012f, 0.479062f, -0.550203f, 0.786737f, -0.917411f, -0.802023f, 1.57227f, 0.643995f, -0.626247f, 1.3826f, -0.643308f, -0.296662f, -0.631958f, 0.125903f, -0.561165f, -0.354695f, -0.645927f, 0.529553f, 0.714097f, -0.208208f, -0.307469f, -0.0649088f, -0.672144f, 0.0743959f, -0.580105f, 1.32175f, -0.34053f, 0.213644f, 0.960989f, -0.369211f, -0.700574f, 0.542504f, -0.0307876f, -0.52194f, -1.04995f, 0.166939f, -0.644977f, 0.373263f, -0.293433f, -0.259692f, 0.662439f, -0.339301f, 1.1388f, -0.0593778f, -0.706105f, -0.789209f, 0.808238f, 0.749022f, 1.10028f, -1.14159f, -0.0990618f, 1.79632f, -0.906117f, -0.0451775f, -0.855292f, -0.272456f, -0.144439f, 0.49774f, -0.336441f, 0.198619f, -0.990211f, -0.152451f, 0.780138f, -0.237703f, 0.203953f, -0.109738f, -0.0133946f, -0.343127f, 0.644481f, 0.0697042f, 0.0927609f, 0.102066f, 0.488014f, 0.18753f, 0.160318f, -0.214566f, -0.428027f, 0.085759f, -0.0918024f, 1.19273f, -0.210594f, 0.283777f, -0.176787f, -0.253484f, 0.0706566f, 0.0444775f, -0.0274145f, 0.572465f, -0.245561f, 0.108852f, 0.262295f, 0.43359f, -0.312667f, -0.0226221f, -0.197633f, 0.383403f, -0.0244389f, -0.208731f, 0.202447f, 0.0624711f, -0.616221f, -0.140103f, -0.249181f, -0.389501f, -0.614766f, -0.362506f, 0.2265f, -0.330135f, -1.07509f, 0.146874f, -0.145657f, -0.0291293f, -0.642817f, -0.246684f, -0.630452f, 0.0672653f, 0.269267f, -0.940307f, -0.158987f, -0.305785f, 0.0163865f, 0.376522f, -0.472504f, -0.561235f, -0.436323f};
+  model->setOperandValue(op53, op53_init, sizeof(float) * 576);
+  static float op55_init[] = {1.07345f, -0.394695f, -0.0742894f, -0.383227f, 0.324794f, 0.418869f, 0.934568f, -1.90608f, 0.209722f, -0.224193f, -0.195225f, -0.0252866f, 0.404565f, 0.300348f, 0.357196f, 0.0298129f, 0.337042f, 0.475936f, -0.631903f, 0.0679197f, 0.65726f, 0.140373f, 0.508893f, 0.775208f, 0.445816f, -1.23974f, 0.0313992f, 0.169123f, 0.112667f, -0.581175f, -0.376066f, 0.885236f, 0.215963f, 0.438986f, -0.157146f, 0.0287784f, -0.757865f, 0.0841731f, 1.03121f, -0.271182f, 0.589192f, 0.976112f, 0.145576f, 0.092291f, 1.06837f, 0.119318f, 0.147453f, -0.525313f, 0.302458f, 0.984562f, 0.142083f, -0.513634f, -0.498019f, 1.29289f, -0.676165f, -0.777563f, 0.0133348f, -1.3991f, 0.416201f, 1.29946f, 0.735901f, -0.407577f, 0.0395284f, -0.244576f};
+  model->setOperandValue(op55, op55_init, sizeof(float) * 64);
+  static float op56_init[] = {0.113075f, -0.0541261f, -0.00254935f, 0.0902875f, -0.32416f, -0.010111f, -0.221566f, -0.0446467f, 0.025913f, 0.0487722f, -0.180431f, -0.0793264f, 0.129554f, -0.0131898f, -0.246616f, 0.0261182f, 0.195068f, 0.0110834f, -0.268252f, -0.0556206f, 0.152303f, -0.159758f, 0.00937392f, 0.0980935f, 0.325152f, -0.115004f, -0.350504f, 0.0197425f, -0.11301f, -0.0753603f, -0.175782f, -0.134789f, 0.00631809f, -0.0891922f, -0.239375f, 0.160609f, -0.0435589f, -0.0562327f, -0.350046f, -0.0121122f, -0.140865f, 0.0352316f, -0.0174294f, 0.110653f, -0.139081f, -0.0948299f, -0.0264269f, -0.029115f, 0.137921f, 0.13543f, -0.0189765f, -0.0165422f, -0.0823839f, -0.256189f, -0.121788f, -0.216157f, 0.00363343f, -0.151778f, 0.252971f, -0.173452f, 0.182134f, -0.156715f, 0.14355f, 0.121809f, -0.0304927f, 0.599508f, 0.041677f, 0.097244f, 0.125037f, -0.133955f, 0.173185f, 0.0350644f, -0.145842f, 0.0234546f, -0.0706621f, -0.132305f, -0.0380816f, -0.16649f, -0.105998f, 0.0139125f, -0.0896661f, 0.149856f, 0.132628f, -0.0480307f, 0.138173f, 0.0411969f, 0.148886f, -0.00950225f, -0.0722613f, 0.0126559f, 0.107946f, -0.09147f, 0.0730902f, 0.125814f, 0.281345f, -0.128981f, -0.0151615f, 0.114928f, 0.0109224f, 0.0134429f, 0.0731687f, -0.014135f, 0.357557f, 0.0469398f, 0.0442583f, 0.0772733f, 0.0690856f, 0.17982f, -0.133452f, 0.0745796f, 0.122212f, -0.0208794f, 0.020065f, 0.0295544f, -0.171575f, 0.0622467f, -0.0769533f, -0.00222684f, -0.0404518f, -0.0317308f, -0.331273f, -0.16373f, 0.156179f, 0.00540106f, -0.0322326f, 0.0850205f, 0.0480989f, -0.152385f, 0.0694411f, 0.229565f, -0.0611579f, 0.0585534f, 0.095432f, -0.023594f, 0.079468f, -0.118917f, -0.0132471f, -0.00255374f, 0.0104798f, 0.584729f, 0.14753f, -0.0907179f, -0.163356f, -0.111535f, 0.14899f, -0.0385063f, 0.0277369f, -0.190452f, -0.0012917f, 0.1646f, 0.0322249f, 0.246906f, 0.123279f, -0.0258971f, 0.00786738f, 0.0542629f, 0.0694776f, 0.150078f, -0.16412f, 0.191585f, 0.049951f, -0.159397f, -0.0137556f, 0.174186f, -0.0435317f, -0.307162f, 0.182426f, -0.177937f, -0.115525f, 0.0298391f, -0.368494f, -0.221122f, -0.0168894f, -0.0401771f, 0.109005f, -0.0733102f, -0.025999f, 0.00781864f, 0.00232855f, 0.00959035f, 0.0469935f, -0.299108f, -0.171356f, -0.0674005f, 0.149625f, -0.0230295f, -0.0455517f, 0.0233079f, 0.205671f, 0.0393789f, -0.287905f, 0.141024f, 0.0859168f, -0.179896f, 0.0601555f, -0.121133f, 0.159868f, 0.0623252f, 0.104785f, -0.188308f, -0.146959f, -0.134704f, -0.319101f, 0.0808484f, 0.344271f, 0.0113916f, 0.175252f, 0.0849976f, -0.0352785f, 0.0743872f, -0.165385f, -0.0677743f, 0.0751335f, -0.00489914f, -0.0963297f, -0.0482092f, -0.135487f, -0.0115389f, -0.0197858f, -0.0754902f, 0.194723f, -0.0186476f, -0.0349434f, 0.189749f, 0.0227529f, 0.0180564f, 0.129332f, -0.0349466f, -0.106948f, 0.0585846f, -0.131004f, -0.0161526f, 0.0149128f, 0.0490677f, 0.0892119f, 0.0442311f, -0.102199f, 0.172912f, -0.153624f, 0.143834f, -0.0421306f, 0.142092f, 0.0772596f, 0.0888918f, 0.102791f, -0.0272839f, 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0.266339f, -0.0353262f, 0.158417f, -0.285848f, 0.120186f, 0.0548689f, -0.0326603f, -0.383041f, -0.182191f, -0.0167416f, -0.0360491f, -0.0325039f, 0.0518329f, 0.115549f, 0.130139f, 0.152888f, -0.170668f, -0.143866f, 0.0448703f, -0.0423743f, -0.118023f, 0.226404f, 0.00380555f, -0.0556225f, 0.111643f, -0.000808296f, 0.221888f, -0.0465153f, -0.0175943f, -0.222517f, -0.156542f, 0.162187f, -0.000673403f, 0.183668f, 0.0201649f, -0.0564224f, 0.0668854f};
+  model->setOperandValue(op56, op56_init, sizeof(float) * 4096);
+  static float op58_init[] = {-0.123297f, 1.03112f, -0.605606f, -0.00193548f, 0.930903f, 0.00530672f, 0.0289674f, 0.0371349f, 0.0378613f, 0.0165883f, 1.03057f, 1.32473f, 0.00546759f, 1.61818f, 1.17308f, 1.15808f, 0.121822f, -0.000576973f, -0.754154f, -0.0371096f, -0.64391f, 0.00522935f, 1.5031f, -0.151665f, 0.0318197f, 1.04132f, -0.000814885f, 0.00560421f, 0.00324315f, -0.665056f, 1.39725f, 0.895453f, 0.43012f, -0.19119f, 0.00455064f, -0.0945014f, -0.00135079f, 1.15827f, 1.27354f, 0.064009f, -0.00115699f, 1.73396f, 1.1265f, -0.000266075f, -0.0288338f, 0.00843227f, 1.43842f, -0.0304834f, 1.27166f, -0.0468991f, 0.00850764f, 0.00357342f, 0.0125746f, 1.28928f, 0.0119823f, -0.734399f, -0.59924f, -0.61645f, 0.0474129f, 0.996462f, 1.90151f, 0.0524316f, 1.28534f, 0.120804f};
+  model->setOperandValue(op58, op58_init, sizeof(float) * 64);
+  static float op59_init[] = {0.156719f, -0.365274f, 0.46557f, 0.194803f, -0.196279f, 0.140896f, 0.048415f, 0.0850183f, 0.121988f, 0.113677f, -0.0442027f, -0.301051f, 0.127761f, -0.242727f, -0.0352292f, -0.174421f, 0.129519f, 0.0561737f, 0.512661f, 0.169123f, 0.0472558f, -0.0649848f, -0.114959f, 0.0635479f, 0.172206f, -0.0733962f, 0.27192f, 0.0156798f, -0.188786f, 0.418895f, -0.197189f, -0.132645f, -0.239554f, 0.0477091f, 0.0892152f, 0.217369f, 0.196861f, -0.223356f, -0.0580539f, 0.0847171f, 0.12474f, -0.239668f, -0.132419f, 0.188901f, 0.134479f, 0.153927f, -0.267787f, 0.0921442f, -0.253014f, 0.166386f, 0.161665f, 0.130119f, 0.0325234f, -0.0883673f, 0.141165f, -0.114373f, 0.337908f, 0.422624f, 0.120521f, -0.272987f, -0.0879027f, 0.39587f, -0.0924423f, 0.383058f, 0.236604f, -0.296603f, 0.606555f, 0.15836f, -0.218761f, 0.217377f, 0.250057f, 0.190977f, 0.265866f, 0.184472f, -0.0895751f, -0.31142f, 0.302541f, -0.426601f, -0.205388f, -0.319032f, 0.176047f, 0.108955f, 0.47963f, 0.217736f, 0.169026f, -0.0729668f, -0.310251f, 0.134645f, 0.279504f, -0.255052f, 0.408038f, 0.122761f, 0.0185433f, 0.409245f, -0.410897f, -0.195616f, -0.0545787f, 0.212299f, 0.16841f, 0.449203f, 0.313798f, -0.43426f, -0.244359f, 0.162991f, 0.162584f, -0.218486f, -0.331835f, 0.31621f, 0.246989f, 0.283238f, -0.546161f, 0.247583f, -0.212179f, 0.275593f, 0.468498f, 0.318836f, 0.206248f, -0.341647f, 0.209406f, 0.529377f, 0.514118f, 0.679407f, 0.232351f, -0.173954f, -0.291855f, 0.601301f, -0.230597f, 0.295756f, 0.148746f, -0.0206303f, 0.30146f, -0.00565797f, -0.134681f, 0.139712f, 0.203158f, 0.166793f, 0.167439f, 0.0876717f, 0.0390046f, -0.0658044f, 0.202852f, -0.434664f, -0.216976f, -0.159045f, 0.0890226f, 0.0870474f, 0.101252f, 0.0657062f, 0.0714723f, -0.0286613f, -0.233553f, 0.0811676f, 0.156996f, -0.149108f, 0.155671f, 0.130916f, 0.0883327f, 0.372619f, -0.300563f, -0.165772f, 0.131113f, 0.160236f, 0.115812f, 0.382637f, 0.176239f, -0.295282f, -0.241622f, 0.122368f, 0.0595133f, -0.053039f, -0.159197f, 0.166583f, 0.136762f, 0.136108f, -0.346738f, 0.198406f, -0.0226704f, 0.140314f, 0.332062f, 0.209204f, 0.200125f, -0.319958f, 0.127433f, -0.307969f, 0.373432f, 0.42893f, 0.159448f, 0.043322f, -0.237465f, 0.418199f, -0.135938f, -0.120479f, 0.250778f, -0.337925f, 0.097704f, 0.35875f, -0.213009f, 0.228708f, 0.0488628f, 0.125034f, 0.199651f, 0.210063f, -0.343646f, -0.400311f, 0.191584f, -0.203307f, -0.157494f, -0.308041f, 0.15821f, 0.174559f, 0.468329f, 0.309438f, 0.247248f, 0.130968f, -0.0867318f, 0.206511f, 0.30064f, -0.171905f, 0.435259f, 0.123804f, -0.253817f, 0.342408f, -0.184797f, -0.255919f, -0.396232f, 0.194991f, 0.218345f, 0.111341f, 0.2816f, -0.204434f, -0.221971f, 0.143186f, 0.24028f, -0.221973f, -0.291024f, 0.283368f, 0.214397f, 0.266395f, -0.118249f, 0.188255f, -0.265134f, 0.262492f, 0.209908f, 0.3002f, 0.169594f, -0.235555f, 0.225255f, -0.228316f, 0.251338f, -0.0592531f, 0.194377f, -0.297403f, -0.282513f, 0.811137f, -0.231202f, 0.369398f, 0.390241f, -0.370919f, 0.279303f, 0.319676f, -0.331098f, 0.314811f, 0.338441f, 0.285473f, 0.431892f, 0.411534f, -0.429208f, -0.423523f, 0.339615f, -0.425702f, -0.406956f, -0.403893f, 0.274328f, 0.292235f, 0.440492f, 0.350801f, 0.333076f, 0.291294f, -0.395539f, 0.376256f, 0.41386f, -0.328553f, 0.295611f, 0.317178f, 0.251311f, 0.28074f, -0.367861f, -0.367438f, -0.0140023f, 0.386603f, 0.351703f, 0.113581f, 0.504158f, -0.390251f, -0.395837f, 0.315225f, 0.314305f, -0.349378f, -0.403343f, 0.481539f, 0.430096f, 0.510183f, -0.338992f, 0.327904f, -0.358538f, 0.626967f, 0.420674f, 0.422722f, 0.341068f, -0.412864f, 0.351495f, 0.53941f, 0.579613f, -0.191784f, 0.378605f, -0.358006f, -0.479399f, 0.996936f, -0.387605f, 0.108954f, 0.221572f, -0.122325f, 0.284289f, 0.0357301f, -0.134014f, 0.1424f, 0.337351f, 0.214974f, 0.27791f, 0.231705f, -0.121512f, -0.0962304f, 0.177933f, -0.38048f, -0.305226f, -0.240732f, 0.196756f, 0.162702f, 0.269918f, 0.104865f, 0.185338f, 0.229805f, -0.404439f, 0.23318f, 0.186489f, -0.264237f, -0.0833724f, 0.282605f, 0.358322f, 0.363139f, -0.252312f, -0.272217f, 0.391736f, 0.206354f, 0.185641f, -0.0126735f, 0.327625f, -0.270849f, -0.221633f, 0.238607f, 0.125709f, -0.266263f, -0.142663f, 0.28435f, 0.256496f, 0.342364f, -0.29405f, 0.211074f, -0.168167f, 0.403277f, 0.227939f, 0.181339f, 0.222679f, -0.209901f, 0.221502f, -0.237734f, 0.481628f, -0.220895f, 0.22485f, -0.0592914f, -0.274332f, 0.666573f, -0.192692f, -0.410142f, 0.115178f, -0.0784163f, -0.0486908f, 0.214595f, -0.168477f, 0.101383f, 0.0139011f, 0.103151f, 0.137509f, 0.147913f, -0.231564f, -0.145663f, 0.0984321f, -0.00238841f, -0.147452f, -0.250834f, 0.0683556f, 0.170684f, 0.445099f, 0.168504f, 0.282291f, 0.18098f, 0.0124517f, 0.162016f, 0.179294f, -0.135994f, 0.180023f, 0.13271f, -0.108859f, -0.0147587f, -0.0215866f, -0.200777f, -0.673948f, 0.127962f, 0.163465f, -0.258157f, 0.0837923f, -0.0756665f, -0.305415f, 0.0867349f, 0.158782f, -0.0837804f, -0.180023f, 0.109462f, 0.127051f, 0.142069f, 0.143861f, 0.128167f, -0.118189f, 0.153459f, -0.0121548f, 0.231083f, 0.168402f, -0.222204f, 0.128066f, -0.190775f, -0.0652145f, -0.0485893f, 0.156782f, -0.122296f, -0.30449f, 0.64902f, -0.210956f, 0.0574174f, 0.234389f, -0.208773f, -0.145177f, 0.227716f, -0.266999f, 0.125867f, 0.184588f, 0.133689f, 0.285285f, 0.319349f, -0.396718f, -0.179921f, 0.0997811f, -0.142402f, -0.247277f, -0.319458f, 0.18121f, 0.223002f, -0.0734019f, 0.180704f, 0.497347f, 0.385627f, -0.208561f, 0.275091f, 0.19304f, -0.253147f, -0.110287f, 0.290269f, 0.241253f, -0.0563772f, -0.0296443f, -0.276056f, -0.248907f, 0.207276f, 0.2393f, -0.350156f, 0.214404f, -0.0767594f, -0.250012f, 0.20857f, 0.221042f, -0.225087f, -0.190393f, 0.251928f, 0.237866f, 0.330792f, 0.117291f, 0.149372f, -0.262906f, 0.405511f, 0.0345566f, 0.20271f, 0.197317f, -0.273887f, 0.22686f, 0.531326f, 0.153736f, 0.00288367f, 0.218847f, -0.308928f, -0.292032f, 0.659711f, -0.275348f, -0.222431f, 0.165082f, -0.149484f, 0.0457284f, 0.0355357f, -0.0642681f, 0.0418851f, 0.223436f, 0.0792975f, 0.212354f, 0.186616f, -0.222066f, -0.0531161f, -0.00979124f, -0.113867f, -0.123542f, -0.193267f, 0.16783f, 0.0824869f, -0.0106096f, 0.0758056f, 0.329999f, 0.257932f, -0.214898f, 0.168143f, 0.0229075f, -0.209178f, -0.342465f, 0.202302f, 0.299346f, 0.25869f, -0.03226f, -0.167826f, 0.204429f, 0.125327f, 0.0956765f, -0.306913f, 0.165133f, -0.0404995f, 0.00542095f, 0.160975f, 0.097063f, -0.27302f, -0.0479996f, 0.172678f, 0.133329f, 0.240162f, -0.0707717f, 0.0715785f, -0.149838f, 0.302035f, -0.0312277f, 0.0150638f, 0.0953851f, -0.0633347f, 0.141286f, -0.323627f, 0.0918484f, 0.132915f, 0.0733498f, -0.124731f, -0.16095f, 0.403907f, -0.0907782f, -0.305642f};
+  model->setOperandValue(op59, op59_init, sizeof(float) * 576);
+  static float op61_init[] = {-0.177357f, -0.172575f, 0.420523f, 0.408536f, 0.0945462f, 0.823321f, 0.190204f, -0.372994f, 1.65173f, -0.167175f, 0.917709f, 0.954723f, 1.42432f, 0.403654f, 0.262092f, 1.04362f, 0.410467f, 0.524981f, 0.298542f, 0.199161f, 0.46461f, -0.0522062f, -0.0135337f, 1.47301f, -0.217844f, 0.813746f, 1.6661f, 0.120697f, 0.533689f, 0.0370758f, 0.292968f, 0.582308f, -0.170719f, 0.2191f, 0.20729f, -0.00339969f, -0.0205846f, 1.16228f, 1.13561f, 0.0840446f, 0.641917f, -0.698399f, 0.926493f, 0.994014f, 0.307775f, -1.16438f, 0.0498876f, 0.0659915f, 0.851326f, -0.27261f, 0.0224912f, 0.188224f, 0.514921f, 1.66756f, 0.222884f, 0.49327f, 0.657591f, 0.859542f, 1.33821f, -0.109509f, 0.630131f, 0.407995f, 0.0164108f, 1.03597f, 0.405228f, 0.285473f, 1.25656f, 0.442834f, 1.16541f, -0.147579f, 0.234518f, 0.564133f, -0.672565f, -0.272256f, -0.843866f, 0.548911f, -0.145986f, -0.401038f, 0.016665f, 0.260142f, 0.58887f, 1.14477f, 0.883501f, 0.161531f, 0.997724f, 0.0126923f, 0.0445706f, -0.680047f, 1.00268f, 0.48881f, 0.556223f, 0.504591f, 0.917035f, 0.0473247f, 0.191936f, 0.804381f, 0.49664f, -0.0397248f, 0.92709f, -0.139789f, 0.415914f, -0.0327383f, -1.44135f, 0.67827f, 0.814107f, 0.656546f, -1.07413f, -0.0251088f, 0.414193f, 0.0932675f, 0.0132784f, 0.292683f, 0.329189f, 1.05858f, -0.998873f, 0.42996f, -0.197071f, 0.698117f, 0.622712f, 0.231817f, 0.0806911f, 0.0574902f, 0.227412f, 0.182395f, 0.478429f, 1.13242f, 0.602f, 0.848106f};
+  model->setOperandValue(op61, op61_init, sizeof(float) * 128);
+  static float op62_init[] = {-0.0953387f, -0.0241844f, -0.245502f, 0.223093f, -0.00234177f, 0.0567266f, 0.141229f, 0.0298321f, 0.0805704f, -0.332235f, -0.0699764f, 0.140453f, 0.191067f, 0.0697032f, -0.0457525f, -0.173236f, -0.143561f, -0.0576257f, 0.145713f, -0.159888f, 0.110944f, -0.0165625f, 0.149536f, 0.0979629f, 0.193839f, -0.101296f, 0.220719f, 0.152941f, 0.12349f, -0.178112f, -0.137191f, 0.110603f, 0.104661f, -0.11074f, 0.0687107f, -0.00464365f, 0.191844f, -0.305179f, 0.106459f, -0.283352f, -0.160429f, 0.143435f, 0.264719f, 0.401874f, 0.0653386f, -0.144139f, -0.0904675f, 0.215576f, -0.026088f, -0.0908799f, 0.00507214f, -0.0940384f, -0.240861f, 0.171879f, 0.0145143f, 0.0972819f, 0.170262f, 0.0256994f, -0.199153f, 0.120436f, -0.124941f, -0.0445037f, 0.150898f, -0.0594313f, 0.0442631f, -0.0491294f, -0.0957917f, -0.110671f, 0.0988712f, -0.048392f, -0.0406623f, -0.0533968f, 0.156252f, -0.0346959f, 0.207246f, -0.100856f, 0.0313422f, 0.00839215f, 0.193575f, 0.119389f, 0.130725f, -0.0987341f, -0.0147687f, -0.0253771f, 0.0580884f, -0.0174773f, 0.0859878f, 0.00799177f, 0.0880935f, 0.0876891f, -0.011503f, 0.00780917f, -0.174531f, -0.135223f, 0.148092f, -0.127871f, -0.041436f, 0.30698f, -0.127153f, -0.0786735f, -0.113721f, -0.109395f, 0.218485f, 0.0407013f, 0.00677337f, 0.0606415f, -0.0847764f, -0.0283162f, 0.0375975f, 0.235108f, 0.0247004f, -0.0103627f, 0.0494522f, -0.15386f, 0.0450112f, -0.00381239f, 0.057318f, -0.0486842f, 0.0650243f, -0.298533f, -0.216992f, -0.0383228f, -0.0980228f, 0.0827745f, -0.0488783f, -0.146196f, 0.111419f, -0.00390476f, 0.0590826f, 0.129497f, -0.0461442f, 0.199943f, -0.157626f, 0.0503393f, -0.0235719f, 0.0704844f, -0.0351197f, 0.116875f, -0.0868494f, 0.238092f, -0.0606355f, -0.0532538f, -0.190276f, -0.0214113f, 0.00628937f, 0.0136869f, -0.438307f, -0.00920097f, 0.0381332f, 0.298624f, 0.201758f, 0.180181f, -0.223815f, -0.0588913f, 0.0905753f, -0.0121884f, 0.0994635f, -0.194738f, -0.125678f, 0.017789f, -0.256984f, -0.194566f, 0.127923f, 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0.303827f, 0.00298885f, -0.0288222f, -0.327243f, 0.0416066f, 0.0929254f, 0.0824386f, 0.0887793f, 0.131717f, -0.112818f, -0.0831022f, 0.0279246f, -0.0888921f, 0.594349f, 0.145838f, -0.274566f, 0.0061455f, -0.142662f, 0.139786f, -0.0117981f, -0.304432f, -0.0508933f, -0.00713381f, 0.114088f, -0.0224593f, -0.13497f, 0.139286f, 0.226299f, 0.0280619f, -0.189189f, 0.230914f, 0.0649094f, 0.161876f, -0.16638f, 0.00781005f, -0.0586318f, -0.0860317f, 0.312927f, -0.0240292f, -0.213285f, -0.00397267f, 0.0305681f, 0.134347f, 0.17009f, 0.258306f, 0.001493f, -0.278121f, 0.0217202f, 0.201947f, -0.192522f, -0.197734f, -0.155724f, 0.471395f, -0.197251f, -0.180739f, -0.229856f, 0.00674667f, -0.158687f, 0.0421946f, -0.144679f, -0.0483309f, -0.159024f, 0.00521026f, -0.270254f, 0.125091f, -0.114965f, -0.0364783f, 0.104376f, 0.199512f, -0.071344f, -0.143244f, -0.0862187f, 0.0365439f, 0.0540296f, -0.170022f, -0.0647209f, 0.00138709f, -0.124052f, 0.0865322f, -0.0750979f, 0.0355845f, 0.14087f, 0.129696f, 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0.0357709f, 0.0311819f, -0.0311085f, -0.0034198f, -0.0888575f, 0.181367f, -0.108846f, 0.0686013f, 0.0850214f, 0.1259f, 0.0367409f, 0.0489611f, 0.097353f, -0.0748888f, 0.00652804f, -0.0922444f, -0.224247f, -0.139533f, -0.181804f, 0.158788f, 0.0688036f, 0.0281373f, -0.241919f, -0.120243f, -0.0755403f, 0.0101523f, 0.0891032f, -0.0709929f, 0.0783334f, 0.0598745f, -0.131034f, 0.0540704f, 0.0244353f, -0.00768915f, 0.127424f, -0.0350807f, 0.0916208f, -0.0437018f, -0.0783366f, -0.0194805f, -0.00660209f, 0.120222f, -0.0716312f, -0.133559f, -0.0660132f, -0.0523321f, 0.0777872f, 0.078556f, -0.0943289f, 0.0650363f, 0.0252414f, -0.0615306f, 0.0416974f, 0.0348374f, -0.0438491f, -0.0169788f, 0.000152442f, -0.0191791f, 0.0607947f, 0.00354985f, -0.0225873f, -0.0219833f, 0.0827315f, 0.013295f, 0.0914269f, 0.031885f, -0.0117931f, 0.0092629f, -0.0934048f, -0.00386388f, 0.0578351f, 0.0620751f, -0.0956425f, -0.0642356f, 0.0293362f, 0.00293314f, -0.0946314f, 0.0612171f, -0.0560762f, -0.173374f, -0.174298f, -0.240948f, -0.0462546f, 0.051344f, 0.101441f, -0.0463354f, -0.0692051f, -0.0353188f, 0.0079918f, -0.123598f, 0.126848f, -0.0576181f, 0.113737f, 0.090959f, 0.114875f, 0.0626428f, -0.024224f, -0.0168703f, -0.18337f, 0.00664052f, -0.1582f, -0.134172f, -0.00927527f, 0.208195f, 0.0573715f, -0.029493f, 0.00595995f, -0.177518f, -0.0251843f, -0.191298f, 0.0224643f, -0.0117011f, -0.0116604f, 0.0171215f, 0.0308808f, 0.0927838f, -0.0920461f, -0.0677266f, 0.0173152f, -0.15957f, -0.0603283f, -0.014207f, 0.178358f, -0.164462f, 0.0250456f, 0.170475f, -0.18779f, 0.133631f, 0.155633f, -0.109469f, 0.0143599f, -0.189536f, 0.0223753f, -0.00895611f, -0.110337f, -0.0689706f, 0.142157f, -0.143697f, -0.141122f, -0.1111f, 0.038711f, -0.0376521f, 0.123297f, -0.149835f, -0.144181f, -0.263992f, -0.123737f, -0.0371692f, -0.148178f, -0.103932f, 0.0424576f, 0.164843f, -0.0927986f, -0.0254294f, -0.0504124f, 0.0800334f, 0.0759776f, 0.0911205f, -0.127232f, -0.0123953f, -0.123989f, 0.072275f, -0.0473754f, -0.00992859f, -0.00908165f, 0.016614f, -0.0338616f, 0.0451948f, -0.00216397f, 0.0791774f, -0.00997479f, -0.204469f, 0.0979367f, -0.0252921f, 0.0806364f, -0.0604877f, 0.35678f, 0.00328074f, 0.000862833f, -0.0423269f, 0.00370664f, 0.0036703f, -0.0456574f, -0.00532339f, -0.0300424f, -0.0847339f, 0.111297f, -0.0276301f, 0.0312098f, -0.00572812f, -0.152074f, -0.143677f, 0.0184641f, 0.0233959f, 0.0783838f, -0.0261117f, 0.058812f, -0.0694083f, -0.0814572f, -0.0732864f, 0.0134815f, 0.0401563f, -0.0683509f, -0.00795014f, -0.0579334f, 0.0152749f, 0.0201549f, -0.166492f, -0.105059f, -0.20479f, -0.134313f, 0.0255906f, 0.0594173f, -0.0898327f, -0.0590535f, -0.0108681f, 0.0314731f, -0.168973f, -0.118293f, 0.255022f, -0.0750191f, 0.0726015f, -0.147087f, -0.00603523f, 0.267165f, -0.255247f, -0.0412965f, 0.0288737f, 0.132844f, -0.0326177f, -0.0856135f, -0.2972f, 0.155763f, 0.28698f, 0.0412092f, -0.224144f, -0.210393f, -0.342643f, 0.0719187f, 0.158874f, 0.226267f, -0.133495f, -0.0857504f, 0.0611778f, -0.0589801f, 0.110317f, -0.0190942f, 0.1773f, 0.00961829f, 0.0677457f, -0.0899815f, -0.138899f, -0.05035f, 0.193441f, -0.139859f, -0.270932f, -0.115539f, -0.316846f, 0.075208f, 0.0431652f, 0.146713f, 0.0285186f, 0.10137f, -0.187721f, -0.0891028f, -0.25393f, 0.106163f, -0.165763f, 0.0463147f, 0.194327f, -0.0429842f, -0.112328f, -0.281324f, -0.00156711f, -0.159594f, 0.00456123f, 0.0655478f, 0.136689f, -0.0740155f, -0.0616994f, 0.254053f};
+  model->setOperandValue(op62, op62_init, sizeof(float) * 8192);
+  static float op64_init[] = {1.27791f, -0.896893f, -0.0904288f, -0.367291f, -0.255839f, -0.584457f, 0.359154f, -0.651333f, -0.599677f, 0.35768f, 1.10981f, -0.620459f, 0.21688f, 0.173693f, -0.860731f, 1.62973f, -0.0480904f, 0.931926f, -0.0432689f, -0.649775f, -0.886409f, -0.419683f, 0.974362f, -0.860229f, -0.222268f, -0.290182f, 0.1913f, -0.356828f, 0.557647f, 1.52403f, -0.593978f, -0.517028f, -0.445634f, 0.28466f, -1.16102f, 1.12105f, -0.285626f, -0.286889f, 0.171823f, -0.836316f, -0.472779f, 0.00341682f, -0.00346886f, -0.262715f, -0.808707f, -0.710406f, 0.10792f, 1.15153f, 0.324643f, -0.0285354f, 0.0859959f, -0.209573f, -0.0140537f, -0.0960617f, -0.0413799f, -0.887105f, 1.3194f, -0.265272f, 1.38463f, -0.279711f, 0.0327209f, -0.0295412f, -0.415826f, 0.972281f, -0.574921f, 1.09703f, -0.302285f, -0.317815f, -0.114017f, -0.437542f, 0.0160477f, 1.4915f, -0.568098f, 0.820527f, -0.687973f, -0.1323f, -0.0332663f, 0.576985f, 0.06609f, 0.745705f, 0.191202f, -0.345881f, -0.472346f, -0.329724f, -0.892812f, -0.616852f, -0.00505598f, -0.270389f, -0.216163f, -0.172727f, -0.44142f, 1.19072f, -0.209099f, -0.0503139f, 0.288438f, 1.03214f, -0.344693f, -0.338285f, 1.43376f, 0.0838178f, -0.137882f, 0.0360903f, -0.588352f, 0.0101241f, 1.33968f, -0.325155f, -0.411048f, 1.6552f, -0.629519f, 0.647605f, -0.208642f, -0.518543f, 1.01164f, -0.36279f, 0.24322f, -0.616136f, 0.0506595f, -0.76616f, -0.405525f, -0.381892f, -0.582617f, -0.506614f, -0.0410523f, 0.0965909f, -0.659473f, -1.02532f, -0.325496f, -0.486067f};
+  model->setOperandValue(op64, op64_init, sizeof(float) * 128);
+  static float op65_init[] = {-0.0709381f, -0.128049f, 0.34379f, 0.147408f, -0.1438f, 0.0135833f, -0.759943f, -0.384337f, -0.239562f, -0.0991685f, 0.642744f, 0.277097f, -1.09486f, -0.560633f, 0.216758f, -0.888341f, -0.518082f, -0.279118f, 0.680989f, -0.492512f, 1.2603f, 0.0466598f, -0.213212f, 0.384692f, -0.651653f, -0.169377f, -0.398121f, -0.0391595f, 0.490388f, -0.672391f, 0.0497536f, -0.245464f, -0.625069f, -0.230214f, 0.288063f, 0.0303378f, -0.0401801f, 0.541154f, 0.329236f, 0.0499154f, 0.159806f, 0.941858f, -0.187031f, 0.214894f, -0.468224f, 0.999631f, -0.354627f, -0.161143f, -0.518824f, 0.271098f, -0.106679f, -0.469782f, 0.336682f, 0.260217f, -0.382269f, -0.238424f, -0.15755f, 0.0634591f, 0.0461773f, -0.0368848f, -0.160486f, -0.261701f, -0.0579005f, -0.561818f, 0.943888f, -0.53118f, -0.0525675f, 0.460865f, -0.572441f, -0.170843f, -0.0466553f, -0.474068f, 0.0738518f, 0.185746f, -0.454275f, -0.495732f, 0.141482f, 0.765303f, 0.318613f, -0.232587f, -0.260385f, -0.654987f, 0.504436f, 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+  model->setOperandValue(op65, op65_init, sizeof(float) * 1152);
+  static float op67_init[] = {-0.305398f, -0.685788f, -0.525249f, 0.301772f, 0.289891f, 0.630685f, -0.209829f, -0.79012f, 0.24649f, -0.608516f, -0.563271f, 0.0645603f, 1.55794f, 1.00103f, 0.880371f, -0.118016f, -0.0790257f, 0.956679f, 0.278375f, -0.625173f, -0.0493856f, 0.87827f, 0.253075f, 0.0546886f, 0.355621f, 0.178734f, 0.478416f, 0.0492583f, 0.293355f, 0.543042f, -0.724245f, 0.990581f, 1.46284f, 0.446866f, -0.79063f, 0.652788f, 0.597898f, 0.917416f, 0.0871194f, -0.284282f, 0.324214f, -0.1572f, 0.0399736f, 0.769288f, -0.960233f, -0.00885646f, -0.643283f, 0.721671f, 1.19157f, -0.721341f, -0.236599f, -0.149836f, 0.213326f, -0.0532691f, 1.27426f, 0.226731f, 0.77594f, 1.29236f, 0.792703f, 0.532026f, 0.153868f, -1.30736f, -0.16838f, 0.0649575f, -0.211678f, -0.0951798f, 0.215633f, -0.501761f, 0.512893f, 0.134215f, -0.124359f, 1.09245f, 0.668202f, -0.251388f, 0.558093f, -0.0925646f, 0.167238f, 0.572327f, -0.754583f, 0.831167f, -0.152979f, 0.445553f, -0.23448f, -0.120027f, 1.47701f, 0.761829f, 0.721299f, -0.123061f, 1.02031f, 0.206746f, 0.605342f, 0.272333f, -0.313723f, -0.415643f, 0.867801f, 0.0943753f, 0.267981f, 0.182397f, -0.311686f, -0.0201961f, 0.135552f, -0.89852f, -0.38088f, 0.504533f, 0.409304f, 0.0599384f, 0.271603f, -0.153014f, 0.395172f, 0.659796f, 0.518529f, 0.550892f, -0.396646f, -1.35361f, 0.502179f, 0.0585412f, 0.658f, -0.330476f, 0.361273f, 0.474181f, 0.626912f, 0.657814f, 0.380077f, 0.90833f, -0.168524f, -0.049237f, 0.177989f, -0.447172f};
+  model->setOperandValue(op67, op67_init, sizeof(float) * 128);
+  static float op68_init[] = {-0.0241622f, 0.0617369f, 0.00313696f, -0.0361745f, 0.0089011f, -0.0771454f, -0.0184935f, 0.0252865f, -0.0486987f, -0.0406999f, -0.0799738f, -0.0141762f, 0.00437186f, -0.0573011f, -0.00957927f, 0.046172f, 0.0570609f, 0.00471992f, 0.0971188f, 0.0576618f, 0.103793f, 0.0197602f, 0.122559f, -0.00102334f, -0.0784559f, 0.155006f, -0.111748f, 0.101551f, 0.0827965f, -0.1318f, 0.0495612f, -0.115198f, 0.15614f, 0.101033f, 0.0604104f, -0.209218f, 0.0122279f, 0.105561f, -0.0860308f, -0.0634802f, -0.0399273f, -0.015346f, -0.0853545f, -0.0609623f, 0.0339712f, 0.0696919f, 0.0744721f, -0.00465823f, -0.146284f, 0.104007f, 0.0193562f, 0.00289296f, 0.0756617f, -0.0586377f, 0.00066429f, -0.0160939f, -0.157602f, 0.105187f, 0.0278241f, 0.156465f, 0.0953226f, -0.0423266f, 0.00946264f, 0.0967963f, -0.0094248f, 0.1983f, -0.0606185f, 0.0422851f, -0.0475956f, -0.209028f, -0.11849f, 0.0630176f, -0.0602975f, 0.0253162f, -0.152982f, -0.186771f, 0.122462f, -0.0890817f, 0.0114347f, 0.0382302f, -0.0130611f, 0.0985855f, 0.106371f, -0.0704771f, 0.13717f, -0.125649f, 0.0763975f, -0.0448528f, -0.116665f, -0.0059271f, 0.0596776f, -0.175521f, 0.320232f, 0.262752f, -0.0392024f, -0.145799f, 0.024413f, -0.104194f, 0.0707348f, 0.108472f, 0.139796f, 0.0529258f, 0.0417071f, -0.0210183f, 0.0914108f, -0.0426374f, 0.00167011f, 0.00624434f, 0.0219409f, -0.029013f, 0.0858393f, -0.0919931f, 0.0904368f, 0.0253718f, 0.00171692f, -0.111899f, 0.0305154f, 0.00299299f, -0.039191f, -0.0160044f, 0.0847733f, -0.125573f, 0.105723f, 0.16296f, 0.163106f, 0.0522193f, 0.148685f, -0.297328f, 0.112013f, 0.0608458f, -0.0468526f, 0.0128562f, 0.130168f, -0.00475011f, -0.04122f, 0.00571167f, 0.039733f, 0.0287809f, 0.0246061f, -0.0382114f, 0.0746748f, 0.0333747f, -0.0387475f, -0.0495416f, 0.0740873f, 0.0629346f, -0.135296f, 0.0120287f, -0.0443212f, 0.100788f, -0.198717f, -0.106631f, -0.0282614f, -0.0405018f, -0.0121696f, -0.0400817f, 0.108328f, -0.0531403f, 0.0146126f, 0.113285f, -0.140269f, 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-0.0281248f, 0.0156918f, -0.0661482f, -0.119143f, 0.0465679f, -0.0339065f, -0.0951787f, -0.0562389f, 0.0559667f, 0.0518762f, -0.0682929f, 0.0191444f, -0.128547f, -0.00657256f, -0.214175f, -0.0121716f, -0.0717781f, -0.0367771f, -0.106917f, 0.019522f, 0.0423303f, -0.0450538f, 0.0378311f, -0.0163635f, 0.224801f, -0.0400332f, 0.0944241f, -0.0316837f, -0.247674f, -0.00152802f, 0.128709f, -0.0530434f, 0.0353833f, -0.188078f, 0.0513568f, 0.165853f, 0.125401f, 0.134201f, 0.0529175f, -0.0595631f, 0.208253f, -0.103614f, -0.086495f, -0.055682f, 0.0678675f, 0.117055f, -0.0797268f, -0.218714f, 0.124429f, -0.0958211f, -0.00746179f, 0.0867841f, 0.0976386f, 0.0974799f, -0.0476189f, 0.0403744f, -0.0532951f, 0.103452f, -0.0561135f, -0.0570386f, 0.0447333f, 0.0284468f, -0.0123736f, -0.152071f, 0.139504f, -0.150434f, -0.236809f, -0.00543498f, 0.179178f, 0.101994f, -0.103473f, 0.171231f, 0.112571f, 0.0470716f, 0.00134852f, 0.0113634f, 0.028328f, -0.0192983f, 0.0615877f, 0.140765f, 0.0691371f, -0.100562f, 0.0634575f, 0.172931f, -0.0278804f, -0.107884f, -0.12921f, 0.144709f, -0.0502041f, 0.26471f, -0.0733277f, 0.0727419f, -0.18533f, 0.0812649f, 0.0574974f, -0.0994873f, -0.108572f, -0.00125924f, -0.0570891f, -0.0564541f, -0.208029f, 0.050427f, -0.388047f, -0.0492397f, 0.0281477f, 0.07582f, 0.231701f, -0.0238934f, -0.0127706f, -0.0947514f, -0.0537848f, -0.378793f, -0.0294461f, -0.130599f, 0.0504004f, -0.00140555f, 0.154203f, 0.00100233f, -0.158577f, 0.0884011f, -0.119132f, -0.109142f, 0.218508f, -0.0235336f, -0.115687f, -0.0622109f, -0.0530095f, -0.00247333f, -0.0040968f, 0.467918f, 0.0968093f, -0.0822504f, -0.283234f, 0.0335439f, 0.190095f, 0.0845923f, 0.203457f, -0.179509f, -0.0774762f, -0.174176f, -0.0256955f, -0.0675088f, 0.0378122f, 0.01191f, -0.00550909f, -0.0197953f, 0.0619587f, -0.010253f, 0.126631f, 0.250306f, 0.0288037f, 0.0906605f, 0.0615545f, 0.079101f, -0.180439f, 0.192944f, 0.0781765f, -0.0304704f, -0.0804992f, -0.214004f, -0.100559f, -0.0197503f, -0.0635601f, 0.0344422f, 0.206626f, -0.113922f, 0.167333f, 0.042957f, 0.072754f, 0.0165848f, 0.161062f, 0.131324f, -0.0806729f, -0.241418f, 0.0882478f, 0.0560616f, 0.11652f, 0.0387292f, -0.210602f, -0.0811962f, 0.00595869f, 0.0906331f, -0.0257964f, 0.0262241f, -0.0583798f, -0.168545f, -0.0824084f, -0.0540559f, 0.055865f, -0.14463f, 0.0536092f, 0.00479177f, -0.0521163f, 0.114327f, -0.087216f, 0.12057f, 0.0343528f, -0.159405f, -0.0428211f, -0.00926862f, 0.204067f, -0.0982124f, -0.00597636f, 0.0857122f, -0.0434118f, 0.0350282f, 0.0122245f, 0.0143983f, -0.065527f, -0.00821878f, -0.0869701f, -0.142122f, 0.0224319f, -0.115208f, -0.00811133f, -0.0997508f, -0.0214029f, -0.0734632f, -0.0765375f, 0.124415f, -0.0181815f, 0.121771f, 0.0431451f, -0.114346f, 0.0580838f, -0.166955f, -0.108603f, -0.0180719f, 0.0187707f, 0.142396f, 0.125052f, 0.0445839f, -0.0869693f, 0.100758f, 0.0827412f, -0.0503467f, 0.0750536f, -0.107036f, -0.0859819f, 0.0949795f, -0.00923993f, 0.137961f, -0.0385899f, -0.0261251f, 0.0364985f, 0.147038f, 0.096688f, -0.036745f, 0.209835f, 0.217248f, -0.149919f, 0.00545082f};
+  model->setOperandValue(op68, op68_init, sizeof(float) * 16384);
+  static float op70_init[] = {-0.66364f, 0.0184158f, 0.52283f, -0.355377f, 1.1477f, -0.584167f, -0.148238f, -0.370158f, -0.863358f, -0.920222f, -0.232067f, -0.392408f, -0.370706f, -0.582042f, 1.07807f, -0.739755f, -0.868499f, 0.849338f, 1.00954f, -0.559628f, -1.00847f, -0.363234f, -0.777592f, -0.361464f, -0.524833f, -0.51576f, 1.09786f, -0.602967f, -0.460839f, -0.0461734f, -0.640552f, -0.550366f, 0.0366958f, 1.41672f, -0.0482828f, 1.01145f, -0.661914f, -0.476727f, -0.420703f, -0.333822f, -0.474296f, -0.325794f, -0.37077f, -0.183918f, 0.7784f, -0.905561f, 1.04277f, 1.13302f, -0.611757f, -0.454366f, 1.04722f, 0.213438f, -0.812226f, 0.415241f, 0.134023f, 0.0181792f, -0.725888f, -0.667944f, 0.14743f, 1.38813f, -0.758548f, -0.0950601f, -0.110067f, 1.08892f, 1.25227f, -0.65893f, -0.258646f, 1.1129f, 0.785756f, -0.573376f, -0.562164f, 0.648412f, -0.650372f, -0.198207f, 1.32062f, -0.446544f, -0.375616f, 0.832923f, 0.515747f, 1.4061f, 0.967074f, -0.545499f, -0.0706069f, 0.594321f, -0.645749f, -0.528063f, 1.13031f, -0.572182f, -0.127073f, -0.797284f, -0.702862f, -0.0707006f, -0.615686f, -0.52278f, 0.253001f, 1.1845f, -0.387047f, -0.0304347f, 0.380325f, -0.40854f, -0.549549f, -0.513802f, -0.813182f, -0.697618f, 0.235504f, -0.408502f, 1.44695f, -0.782359f, 0.764666f, -0.376841f, -0.307161f, -0.436902f, -0.439395f, -0.00343463f, -0.705699f, -0.557165f, -0.443319f, 1.1431f, -0.503291f, -0.611081f, -0.120243f, 1.15355f, -0.372295f, -0.474172f, 1.23777f, -0.441865f, -0.00485877f, -0.540569f};
+  model->setOperandValue(op70, op70_init, sizeof(float) * 128);
+  static float op71_init[] = {0.190358f, 0.76666f, 0.00328711f, 0.564753f, -0.350922f, -0.129309f, -0.3002f, 0.0597919f, 0.426195f, 0.396956f, -0.0503945f, -0.0959898f, 0.7998f, 0.20007f, -0.470447f, -0.0882118f, 0.387503f, -0.154394f, -0.527967f, -0.382423f, 0.439986f, -0.26216f, 0.675393f, 0.600835f, 0.710669f, -0.144166f, -0.623441f, -0.25641f, 0.146244f, 0.0956447f, 0.530404f, -0.0558362f, -0.228722f, -0.615698f, -0.232535f, -0.188218f, 0.463525f, 0.208408f, 0.202256f, -0.459553f, 0.290275f, -0.0482571f, 0.0479941f, -0.480289f, -0.359739f, 0.29264f, -0.189077f, -0.101516f, -0.327849f, 0.0132966f, -0.478556f, -0.667986f, -0.00429771f, -0.395361f, 0.591137f, 0.438846f, 0.270845f, 0.22185f, -0.114037f, -0.242702f, 0.163454f, 0.134378f, -0.125448f, 0.0916562f, -0.174708f, 0.0403809f, 0.561983f, -0.536697f, 0.837897f, -0.102087f, 0.195032f, 0.642412f, -0.00309444f, 0.152015f, -0.278766f, -0.0803865f, -0.149121f, -0.404437f, -0.277375f, -0.463219f, 0.455272f, 0.645321f, 0.712899f, 0.440117f, 0.00296985f, -0.370598f, -0.305418f, 0.350335f, 0.256088f, -0.505846f, 0.141766f, 0.683693f, 0.189428f, 0.384547f, 0.520508f, -0.0903593f, -0.466102f, 0.119247f, -0.31008f, 0.268459f, 0.541718f, 0.565971f, -0.0766391f, -0.242424f, -0.0208426f, 0.615597f, -0.0939945f, 0.355455f, -0.47433f, -0.0974868f, -0.111173f, 0.00675133f, -0.331637f, -0.288407f, 0.277921f, -0.00905987f, 0.449155f, -0.23387f, -0.0123091f, -0.106995f, 0.000705794f, -0.174747f, -0.290359f, -0.15716f, -0.342961f, -0.318778f, -0.244923f, 0.41067f, 0.600289f, 1.11803f, 0.0108391f, 0.562716f, -0.0486975f, -0.25541f, 0.0325754f, 0.556536f, -0.115194f, 0.119986f, -0.172908f, 0.19715f, 0.237946f, 0.657477f, -0.288834f, 0.693158f, 0.599522f, -0.176689f, -0.328313f, 0.642065f, 0.295767f, -0.268138f, 0.50916f, 0.541139f, 0.575437f, -0.308893f, -0.416536f, 0.114128f, -0.0474224f, -0.0862949f, 0.417725f, -0.231729f, 0.724209f, -0.194049f, -0.517304f, -0.652919f, 0.433762f, 0.912894f, -0.483609f, -0.296952f, 0.0126445f, 1.20907f, 0.337168f, -0.0322295f, -0.132569f, 0.116397f, 0.370504f, -0.448363f, 0.720829f, 0.879811f, -0.648568f, 0.515107f, -0.052637f, -0.388975f, 0.421326f, -0.989203f, -0.341183f, 0.286548f, 0.0134756f, -0.782349f, 0.11126f, 0.972077f, -0.0604684f, 0.160813f, -0.080907f, -0.508684f, 0.649636f, -0.472908f, -0.633012f, -0.109733f, -0.301114f, -0.712373f, 0.4899f, -0.165437f, -0.343757f, 0.859791f, -0.221293f, -0.755234f, -0.51916f, 0.00321254f, -0.14699f, 1.34957f, 0.906992f, -0.796848f, 0.960862f, -0.243892f, -0.149225f, 0.29761f, -0.0732879f, 0.590636f, 0.446738f, -0.498876f, 0.268498f, 0.841365f, -0.829389f, -0.339174f, 0.55688f, -0.820046f, -0.294324f, 0.218061f, 1.07041f, 0.647936f, -0.00319098f, 0.637792f, 0.2681f, 0.408708f, -0.281842f, 0.563577f, 0.248457f, -0.173597f, 0.857762f, 0.0828917f, -0.236691f, 0.367459f, 0.36482f, 0.335563f, 0.469174f, -0.492988f, 0.102047f, 0.0864881f, -0.154285f, -0.209307f, -0.384697f, -0.408656f, -0.324157f, -0.11449f, -0.302919f, 0.811304f, -0.071401f, -0.194882f, 0.877613f, 0.7679f, -0.425736f, -0.0927369f, -0.177047f, 0.652595f, 0.145123f, -0.0892876f, -0.165002f, 0.128822f, -0.234167f, 0.0364328f, -0.553999f, 0.506505f, 0.110685f, -0.281018f, 0.185106f, 0.240167f, 0.404976f, 0.161763f, 0.177268f, 0.426034f, -0.311109f, -0.132578f, -0.134164f, 0.832055f, -0.0668457f, -0.381313f, -0.0599468f, -0.0109465f, 0.396031f, -0.71884f, -0.095649f, -0.250095f, -0.172813f, 0.269057f, -0.109603f, 0.192561f, 0.277378f, -0.0390484f, -0.180217f, 1.28994f, 0.122155f, 0.232436f, -0.0340455f, -0.252908f, 0.389663f, 0.0565574f, -0.399774f, 0.887266f, 0.310494f, -0.362899f, -0.319276f, 0.10574f, 0.127307f, -0.494444f, -0.112868f, -0.2034f, 0.501617f, 0.124677f, -0.235599f, 0.344745f, -0.467707f, 0.0463722f, -0.607921f, -0.081456f, -0.760228f, -0.200317f, 0.259661f, -0.344715f, 0.00404537f, -0.195673f, 0.301249f, 0.384962f, -0.0361301f, -0.305219f, 0.198748f, 0.0795681f, 0.0443111f, -0.374283f, -0.46018f, -0.0992139f, 0.530139f, 0.235449f, 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-0.593003f, -0.0868912f, 0.131847f, 0.0749275f, -0.197579f, -0.111212f, 0.0223139f, 0.243874f, 0.156878f, 0.190403f, 0.450317f, -0.150603f, -0.246352f, -0.128152f, 0.115508f, 0.493985f, -0.222931f, 0.452042f, -0.242511f, -0.215531f, -0.15448f, 0.105351f, 0.219143f, -0.0308257f, 0.486673f, -0.283853f, -0.163485f, -0.274629f, 0.247168f, 0.465471f, -0.047011f, 0.130996f, 0.5783f, -0.236574f, -1.03715f, 0.12173f, -0.257977f, -0.102828f, -0.165848f, -0.0104392f, 0.378396f, 0.273506f, 0.113921f, 0.078316f, -0.405008f, -0.0091235f, -0.0771289f, -0.43577f, 0.373244f, -0.396689f, -0.118428f, -0.124698f, -0.163262f, -0.539655f, -0.487564f, 0.0727633f, -0.102938f, -0.415128f, -0.222664f, 0.920234f, -0.177296f, -0.515815f, 0.0770235f, -0.37286f, -0.401904f, 0.0224006f, 0.350639f, 0.262495f, 0.375316f, 0.00518776f, -0.373577f, 0.0238316f, -0.171652f, -0.54584f, 0.200506f, -0.166763f, -0.17752f, 0.22408f, -0.335509f, 0.249634f, 0.101166f, -0.149211f, 0.298221f, -0.316278f, -0.167293f, -0.34354f, -0.166304f, 0.156108f, -0.197453f, -0.0979077f, -0.00206543f, 0.0643555f, 0.253949f, 0.857866f, 0.426089f, -0.101682f, -0.214549f, 0.202225f, -0.379808f, 0.291689f, -0.0552537f, 0.638515f, 0.0758169f, -0.254243f, -0.176746f, 0.909293f, -0.06176f, -0.185409f, -0.000147814f, -0.122751f, 0.411986f, -0.229916f, -0.231603f, 0.0380824f, -0.0611861f, 0.171022f, 0.391192f, 0.192886f};
+  model->setOperandValue(op71, op71_init, sizeof(float) * 1152);
+  static float op73_init[] = {-0.459464f, -0.0353652f, 0.65298f, 0.492282f, -0.434366f, -0.0646238f, 0.168169f, 0.841487f, 0.821593f, 0.0824923f, 0.324534f, 0.244733f, 0.687792f, 0.679983f, 1.20542f, -0.0494685f, 0.580938f, -0.125653f, 0.979836f, 0.518563f, -0.230283f, 0.0469813f, 0.293084f, -0.718912f, -1.0622f, 0.113178f, -0.0678228f, 0.916626f, 0.0892698f, 0.474777f, 0.352559f, -0.518444f, 0.298361f, 0.152684f, 1.02351f, 0.858021f, -0.138064f, 0.432028f, 0.262955f, 0.410308f, -0.175447f, 0.437843f, 0.290894f, -0.251734f, -0.156011f, 0.395701f, 0.683667f, 0.13276f, 0.649738f, -0.0994671f, 0.862117f, 0.679516f, 0.626916f, 0.591512f, 0.349128f, 0.647349f, 0.321387f, -0.39079f, 0.130351f, 0.373571f, 0.0105721f, 0.139855f, 0.288337f, 0.00182344f, 0.492347f, 0.395679f, 0.063744f, 0.591242f, -0.105116f, 0.568728f, 0.893553f, 0.830799f, -0.786496f, 0.308447f, -0.304133f, 0.713135f, -0.664118f, 0.0611865f, 0.317401f, -0.209737f, -0.0484893f, 0.404629f, 0.56469f, -0.461555f, 0.163955f, 0.376575f, 0.965699f, -0.0480532f, 0.186419f, 1.13773f, 0.266542f, 0.402838f, -0.423273f, -0.647047f, 1.55817f, -0.330907f, 0.103328f, 0.505363f, 0.156278f, 0.3413f, 0.792374f, -0.115844f, -0.365503f, -0.418147f, -0.402983f, 0.228505f, 0.70761f, 0.260362f, 0.703803f, 0.584213f, -0.312215f, 0.22878f, 0.916701f, -0.740095f, 0.555479f, 0.60881f, 0.638773f, 0.308882f, 0.515022f, 0.0501348f, -0.0876003f, 0.527447f, -0.310391f, 0.354625f, 0.119797f, 0.541051f, -0.176547f, -0.32494f};
+  model->setOperandValue(op73, op73_init, sizeof(float) * 128);
+  static float op74_init[] = {0.181329f, -0.0840758f, -0.0933245f, 0.0235837f, 0.0135975f, 0.326603f, -0.0139708f, -0.112846f, 0.181431f, 0.300608f, 0.0366979f, -0.00359797f, 0.0227877f, 0.00927314f, -0.18318f, 0.0122945f, 0.124818f, 0.00987374f, 0.156316f, -0.289415f, 0.10349f, 0.0364732f, 0.0231318f, 0.0581194f, -0.100904f, 0.13513f, -0.0616679f, 0.08791f, -0.0899955f, -0.0814202f, 0.0770271f, -0.0352028f, 0.0505355f, 0.0157475f, -0.174024f, 0.0321904f, 0.0789286f, 0.0553437f, -0.0721803f, -0.124891f, -0.0141911f, -0.0998818f, 0.0907457f, -0.0333116f, -0.0323912f, 0.0260731f, 0.0414896f, -0.0498239f, 0.0463238f, -0.0758002f, -0.0464296f, 0.036594f, 0.218559f, -0.021053f, -0.10772f, 0.148092f, 0.00719467f, 0.166783f, 0.202187f, 0.00202994f, -0.0944071f, 0.091252f, -0.0095911f, 0.280841f, -0.134233f, 0.0669713f, 0.0791813f, 0.167962f, 0.0732689f, 0.0647677f, 0.021687f, -0.0849598f, -0.0170565f, -0.0668448f, 0.0414721f, 0.0164082f, 0.128536f, 0.0603419f, 0.111924f, 0.0195282f, 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0.0666378f, 0.0391409f, -0.0565035f, 0.0961659f, -0.136477f, -0.0432741f, 0.151737f, -0.00998722f, -0.0747038f, -0.138342f, -0.0364102f, -0.170901f, -0.0621025f, -0.0253327f, -0.0370147f, 0.0468679f, -0.0193059f, 0.180075f, 0.0947352f, -0.0790074f, 0.0908916f, 0.0495844f, -0.0512141f, -0.101972f, -0.187381f, -0.0234408f, -0.144917f, 0.0912873f, 0.137953f, -0.0881145f, 0.155221f, 0.0710232f, 0.148847f, -0.0598482f, 0.206454f, 0.0319354f, -0.113567f, 0.0103158f, 0.151559f, -0.189436f, 0.128234f, 0.0877855f, -0.0637323f, -0.0778795f, 0.0376895f, -0.0511335f, -0.108678f, -0.158048f, 0.108506f, 0.0246635f, 0.0169756f, 0.10831f, 0.026912f, -0.00203766f, 0.0312686f, 0.0894737f, 0.0162477f, -0.0618999f, -0.0265796f, 0.114227f, -0.15638f, -0.0510761f, -0.0377173f, 0.0226881f, 0.0418164f, -0.0366621f, -0.035809f, -0.0266003f, 0.0467199f, 0.171896f, -0.0271323f, -0.0163066f, 0.028144f, 0.0436655f, 0.128942f, -0.0194696f, -0.105502f, 0.0681745f, -0.0502478f, 0.0555929f, -0.05233f, -0.0198393f, 0.132248f, 0.126557f, 0.00828652f, -0.090131f, -0.0212319f, -0.0250166f, -0.0118503f, -0.0875313f, 0.0768847f, 0.0485072f, -0.019315f, 0.284054f, 0.100281f, 0.108431f, -0.0830946f, -0.023745f, 0.0625827f, -0.0561233f, 0.0932393f, 0.0275348f, -0.1307f, -0.0600125f, -0.0451818f, -0.102182f, 0.165792f, -0.130795f, -0.0328623f, -0.241256f, -0.1522f, 0.13973f, -0.0225733f, -0.0121984f, -0.0512724f, 0.0964481f, -0.112301f, -0.147525f, 0.258343f, 0.0169823f, 0.038229f, 0.0942557f, -0.0375277f, 0.0529383f, 0.0917328f, -0.106428f, -0.00183135f, -0.0535075f, 0.011453f, 0.0899797f, -0.00914698f, 0.0447383f, 0.0399944f};
+  model->setOperandValue(op74, op74_init, sizeof(float) * 16384);
+  static float op76_init[] = {1.2227f, 0.664689f, -0.697727f, -0.607951f, 1.29794f, -0.073003f, -0.811291f, 1.23139f, 1.26409f, -0.384498f, 1.08346f, -0.668803f, -0.435764f, 1.3942f, -0.371175f, 1.2419f, 1.24256f, -0.621671f, 0.0760495f, -0.765654f, 0.196979f, 0.214335f, -0.58529f, 1.2814f, -0.120833f, -0.844234f, -0.455902f, -0.965084f, -0.586658f, 1.11645f, 1.24002f, -0.565542f, -0.540129f, 1.22517f, -0.544301f, -0.591493f, 0.403981f, -0.113213f, -0.0999279f, -0.508504f, -0.361916f, -0.666335f, 1.19214f, 0.180251f, -0.793999f, -0.0519839f, 0.243307f, 0.488556f, -0.5879f, -0.68376f, 1.20553f, 0.855387f, 1.32818f, -0.668094f, -0.432518f, -0.730011f, -0.825747f, 1.08466f, -0.689586f, -0.46422f, -0.608787f, -0.436489f, -0.52064f, -0.699725f, 0.262406f, -0.617448f, -0.73687f, -0.799998f, -0.0571513f, 0.0468143f, 0.826328f, -0.361061f, -0.636886f, 1.059f, -0.588544f, 1.1137f, 0.737585f, -0.896787f, -0.209556f, 0.201041f, -0.0373591f, -0.49788f, 1.02235f, -0.42106f, -0.61662f, -0.0805732f, -0.500747f, 0.549504f, -0.0802444f, -0.517048f, -0.975228f, -0.374565f, -0.310484f, 1.02079f, -0.465238f, 0.877757f, -0.00396147f, -0.467624f, -0.467418f, -0.672751f, -0.255117f, -0.619892f, -0.743825f, 1.06921f, -0.667405f, 0.997503f, -0.877923f, -0.697879f, 0.385421f, -0.496918f, 0.223972f, 1.11902f, -1.05091f, 0.614654f, 0.849332f, -0.454338f, -0.412169f, -0.688757f, -0.551979f, -0.0854241f, -0.195676f, -0.542179f, -0.701308f, -0.446594f, -0.435718f, -0.867095f, 1.29558f, -0.85324f};
+  model->setOperandValue(op76, op76_init, sizeof(float) * 128);
+  static float op77_init[] = {-0.232485f, 0.750123f, 0.158505f, 0.452319f, -0.340535f, 0.304917f, 0.601414f, -0.213319f, -0.527085f, 0.51019f, -0.266959f, 0.367842f, -0.206907f, -0.323959f, -0.159575f, -0.177844f, -0.178491f, -0.143209f, -0.744888f, 0.171007f, -0.056294f, 0.0066854f, -0.0159956f, -0.338152f, 0.595454f, 0.0494067f, -0.242471f, 0.395647f, -0.0994157f, -0.1077f, -0.690943f, 0.298448f, -0.0125066f, 0.189733f, -0.257466f, -0.0827938f, -0.480399f, -0.300462f, -0.335141f, 0.0223836f, 0.550395f, 0.0419619f, 0.226111f, -0.176909f, 0.127377f, -0.0545993f, -0.387069f, -0.768176f, -0.0824907f, 0.0591839f, -0.0952336f, -0.355136f, -0.498724f, 0.0494056f, 0.0379881f, 0.225825f, 0.173812f, -0.544722f, -0.133118f, -0.0791841f, 0.0940735f, -0.135813f, 0.381779f, 0.150541f, -0.218683f, 0.0192335f, 0.0824092f, 0.0248153f, 0.767578f, 0.0404393f, -0.870468f, 0.278391f, 0.431434f, 0.153796f, -0.129333f, -0.532381f, -0.253057f, 0.631776f, -0.252957f, -1.17293f, 0.684977f, 0.0593484f, 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0.227674f, -0.512324f, -0.192572f, -0.51508f, 0.694937f, 0.432446f, 0.734156f, 0.0599805f, 0.0451104f, 0.387917f, 0.52736f, 0.0150681f, 0.653797f, 0.0555282f, 0.295022f, 0.116211f, 0.282033f, 0.127456f, 0.562138f, 0.864882f, 0.562918f, 0.226986f, -0.732976f, -0.125189f, -0.356436f, 0.773513f, 0.00784227f, 0.0959714f, 0.202602f, 0.635033f, 0.285615f, -0.588955f, 1.16024f, -0.526163f, 0.524461f, 0.296178f, -0.285337f, 0.250037f, -0.448641f, 1.12717f, -0.40796f, 0.913023f, -0.310407f, -0.198584f, -0.420773f, 0.110765f, -0.348902f, -0.391878f, 0.0488817f, -0.519489f, 0.385946f, -0.123989f, 0.419801f, 0.333858f, 0.0667859f, 0.237291f, -0.208133f, 0.376354f, 0.219975f, 0.401764f, 0.2236f, 0.172458f, 0.254095f, 0.0944153f, -0.577605f, 0.215535f, 0.982192f, 1.20196f, 0.252205f, 0.456823f, -0.17214f, 0.596597f, 0.374121f, 0.21441f, 0.22223f, 0.306031f, 0.250367f, -0.414704f, 0.512144f, -0.285307f, -0.493507f, 0.689128f, 0.134251f, -0.422183f, 0.302675f, 0.1381f, -0.305875f, 0.00499852f, -0.232788f, -0.266377f, 0.118899f, -0.0735813f, -0.400083f, 0.457611f, -0.124106f, -0.525283f, 0.195735f, 0.255211f, 0.163252f, 0.603786f, -0.945585f, 0.23017f, -0.143815f, -0.411882f, 0.0274922f, 0.594628f, -0.165145f, 0.0458463f, 0.0792487f, 0.151905f, -0.430532f, 0.361895f, -0.386514f, -0.055938f, 0.724818f, -0.314764f, 0.662356f, -0.321182f, 0.278372f, -0.508936f, 0.510272f, -0.358697f, 0.450372f, 0.326299f, -0.564039f, 0.649753f, 0.255396f, 0.226893f, 0.193944f, -0.0455373f, -0.637073f, -0.406078f, 0.247549f, 0.2822f, 0.461711f, 0.0955357f, -0.261276f, 0.548638f, -0.0557388f, 0.182164f, 0.551088f, -0.131262f, -0.192677f, 0.743369f, 0.496859f, -0.110602f, 0.665807f, -0.341119f, -0.574006f, 0.253317f, -0.0412391f, -0.187952f, -0.549984f, -0.380044f, -0.30571f, 0.0611864f, 0.245165f, 0.221235f, 0.508958f, -0.151121f, 0.397989f, 0.00208155f, -0.154384f, -0.084145f, -0.459448f, 0.254966f, -0.01605f, 0.613941f, -0.0170916f, 0.208544f, -0.182594f, -0.0684111f, 0.189469f, -0.00860068f, -0.331824f, -0.523698f, -0.0657233f, -0.252375f, 0.612957f, 0.0379591f, 0.209828f, 0.297172f, -0.402651f, -0.174693f, -0.138906f, 0.395919f, -0.200965f, -0.550715f, -0.529917f, 0.181403f, -0.457216f, 0.688771f, 0.73705f, 0.317982f, -0.128821f, -0.48089f, 0.612106f, -0.172449f, -0.450366f, 0.796766f, 0.665507f, 0.813123f, 0.555636f, -0.362653f, -0.316043f, -0.17264f, -0.229654f};
+  model->setOperandValue(op77, op77_init, sizeof(float) * 1152);
+  static float op79_init[] = {-0.108669f, -0.24239f, 0.892824f, 0.100496f, -0.175517f, -0.0614264f, 0.896133f, -0.142274f, -0.0590312f, 0.125f, 0.864931f, -0.283458f, -0.13665f, -0.0803576f, -0.146452f, -0.195702f, -0.582552f, -0.339264f, -1.01993f, 0.447734f, -0.917057f, 0.225414f, -0.306775f, 0.594087f, 0.556081f, -0.327338f, -0.0957925f, -0.309899f, 0.650205f, 0.348621f, 0.255781f, 0.371079f, 0.915888f, 0.978555f, 0.799558f, -0.32679f, -0.427624f, -0.0823039f, 0.369625f, -0.57637f, -0.0263745f, -0.282986f, 0.635218f, 0.378849f, -0.155068f, 0.707911f, 0.0484146f, -0.726708f, -0.212411f, 0.0321696f, 0.0862673f, -0.0752373f, -0.778846f, -0.0985055f, 0.452711f, 0.608385f, 0.616601f, -0.33512f, 0.409252f, 0.778583f, 0.181552f, -0.955649f, -0.456805f, 0.0249269f, 0.30359f, 0.823123f, 0.711778f, 0.600027f, -0.352327f, 0.512934f, 0.34219f, -0.29652f, 0.505236f, 0.175734f, 0.874702f, -0.275469f, 0.580716f, 0.635559f, -0.546206f, 0.457047f, 0.461714f, 0.346941f, 0.637959f, -0.0761546f, 0.555644f, 0.542373f, 0.292184f, 0.784725f, -0.502565f, 0.582605f, -0.178634f, -0.627065f, -0.08808f, -0.801258f, 0.225673f, 0.672628f, 0.596107f, -0.159289f, -0.652513f, 0.538379f, -0.145736f, 0.317523f, 0.695517f, 1.03021f, -0.495469f, -0.164966f, 0.740315f, -0.159693f, 0.504333f, 0.386047f, -0.121875f, -0.222074f, 0.59883f, -0.149101f, -0.71422f, 0.54467f, 0.694151f, -0.447638f, 0.090233f, -0.220637f, 0.724413f, 0.366921f, 0.136273f, 0.615985f, 0.185512f, 0.0515735f, -0.342775f, 0.584152f};
+  model->setOperandValue(op79, op79_init, sizeof(float) * 128);
+  static float op80_init[] = {0.143542f, -0.139317f, -0.0557127f, 0.00193462f, -0.0166539f, 0.216436f, 0.0694379f, 0.0774276f, -0.061387f, 0.193228f, -0.0234282f, 0.0303868f, -0.10475f, 0.225842f, -0.0953071f, 0.0518284f, -0.177148f, 0.0706816f, -0.116163f, 0.23116f, 0.0276252f, 0.361075f, 0.114999f, -0.179934f, 0.0362276f, 0.098386f, 0.160729f, -0.203046f, -0.0214891f, -0.0217361f, -0.0319598f, -0.0163527f, 0.0405451f, -0.0441358f, -0.0010904f, -0.219479f, -0.0129676f, 0.0840713f, -0.334326f, -0.275725f, 0.00787852f, 0.102421f, 0.0265449f, -0.0439835f, -0.160807f, 0.128618f, 0.00937286f, 0.0634051f, 0.17013f, -0.149011f, -0.148228f, -0.185353f, -0.230108f, 0.0953904f, -0.0328099f, 0.08806f, 0.164153f, -0.155663f, 0.00662038f, 0.106636f, -0.110083f, -0.123108f, -0.0422361f, 0.00699063f, 0.0286107f, 0.0872556f, 0.0372735f, 0.129417f, 0.0114595f, 0.127069f, 0.0845895f, -0.103232f, -0.084375f, 0.0507973f, 0.0924024f, -0.0443189f, -0.0373084f, -0.0547004f, -0.107631f, -0.0137342f, 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-0.0833115f, 0.132745f, -0.0764369f, -0.0667909f, 0.0471235f, -0.0951605f, 0.0251998f, 0.109606f, -0.0551212f, 0.0423476f, -0.0914923f, 0.104139f, -0.166891f, -0.144794f, 0.00263478f, 0.0549706f, -0.0192015f, -0.094959f, -0.0470626f};
+  model->setOperandValue(op80, op80_init, sizeof(float) * 16384);
+  static float op83_init[] = {-0.0293549f, -0.0835053f, -0.228576f, -0.0980885f, -0.0370638f, -0.195879f, -0.0452258f, 0.0371641f, -0.0585841f, -0.0984154f, -0.141293f};
+  model->setOperandValue(op83, op83_init, sizeof(float) * 11);
+  static float op84_init[] = {0.0984852f, 0.672424f, 0.392549f, -0.262182f, 0.303914f, -0.0118188f, 0.027943f, 0.0164078f, 0.200583f, -0.808626f, 0.234772f, -0.0253635f, -0.198519f, -0.176824f, -0.580674f, 0.0681573f, -0.0134279f, 0.172173f, -0.284882f, -0.0895141f, 0.0142356f, -0.0479431f, 0.0736678f, 0.00298977f, 0.152355f, -0.0370715f, 0.463201f, 0.0146613f, 0.0971624f, -0.0791196f, 0.556621f, -0.00950762f, 0.0160531f, 0.091037f, 0.376353f, -0.0996081f, -0.0418334f, -0.427482f, -0.202679f, -0.197079f, 0.021873f, -0.105617f, 0.36447f, 0.389277f, 0.0429815f, 0.0480496f, -0.170086f, -0.191548f, -0.237921f, 0.155838f, -0.100796f, 0.0539355f, 0.103154f, 0.0441985f, -0.20672f, 0.358565f, -0.105794f, -0.635905f, 0.193301f, 0.112419f, -0.184668f, 0.157954f, -0.301095f, -0.153072f, -0.0535615f, -0.0661999f, -0.197056f, -0.0835003f, -0.074932f, -0.111766f, -0.356266f, 0.649165f, -0.0527003f, -0.0597135f, 0.109839f, -0.270809f, 0.0333183f, -0.211454f, 0.0594729f, -0.166949f, 0.21057f, 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-0.182135f, 0.112932f, -0.32439f, 0.294457f, -0.0818895f, 0.0914322f, 0.185025f, 0.0543957f, -0.0167575f, 0.504046f, -0.0647153f, -0.166975f, 0.0248059f, 0.0379442f, 0.0980366f, -0.178135f, 0.143822f, 0.45732f, -0.0912428f, -0.179338f, 0.349726f, -0.0596313f, -0.299861f, 0.112567f, 0.0666395f, 0.345303f, 0.164124f, -0.00265316f, -0.0732412f, 0.348079f, -0.249414f, 0.0465329f, 0.0693596f, 0.0799214f, 0.000123214f, 0.180679f, 0.0912923f, -0.300121f, -0.288428f, 0.150135f, 0.112936f, 0.104813f, -0.0555879f, -0.00205972f, -0.0251151f, -0.0788264f, -0.016778f, -0.110796f, -0.083048f, -0.212734f, 0.288568f, -0.114228f, -0.113358f, 0.110789f, 0.118645f, 0.133466f, -0.0298552f, -0.241374f, 0.157257f, 0.0861554f, -0.0909277f, 0.00156177f, 0.106539f, -0.209104f, -0.106974f, 0.0203283f, -0.18111f, -0.311602f, -0.00371812f, 0.0711113f, -0.206721f, 0.286076f, 0.139713f, 0.116621f, 0.182792f, 0.0246107f, -0.17972f, 0.041917f, 0.0724635f, 0.266344f, 0.0989191f, 0.0723898f, 0.0257298f, 0.104898f, 0.0681826f, -0.0704781f, 0.00212139f, -0.363547f, 0.0274255f, -0.106295f, -0.363965f, 0.127051f, -0.0575343f, -0.200952f, -0.0666189f, -0.139465f, -0.0171747f, 0.253794f, -0.258602f, -0.166356f, -0.107649f, 0.267331f, 0.104521f, -0.020921f, -0.0780469f, 0.125002f, 0.0202556f, -0.0899181f, -0.126559f, -0.297855f, 0.121539f, -0.0671643f, -0.0444782f, 0.334408f, 0.0882725f, -0.0879492f, -0.00277655f, -0.0616985f, 0.0564236f, -0.11618f, -0.22836f, 0.112953f, 0.176082f, 0.09988f, -0.00635589f, -0.114234f, 0.241135f, 0.0966775f, -0.0961065f, 0.137214f, -0.0832349f, -0.54299f, -0.2335f, -0.033801f, -0.11505f, -0.366386f, -0.238099f, -0.0951656f, 0.263106f, 0.129292f, -0.14762f, 0.0700404f, 0.0195349f, -0.286227f, -0.273371f, 0.0587288f, -0.257152f, -0.136248f, -0.13336f, -0.248086f, 0.273973f, -0.302625f, -0.085841f, -0.0839808f, -0.130464f, 0.252972f, -0.0415149f, -0.0695038f, -0.091557f, -0.262375f, -0.0645785f, 0.188566f, -0.202261f, -0.112712f, 0.00631479f, 0.0132917f, -0.0130675f, -0.302285f, 0.0556928f, -0.0211812f, -0.0555546f, 0.0291112f, 0.168815f, 0.143654f, -0.00564186f, -0.0614248f, -0.0939664f, 0.0959667f, -0.209823f, -0.103889f, -0.206011f, -0.0394793f, 0.0545815f, -0.0348762f, -0.132075f, -0.0489917f, -0.177563f, -0.164591f, -0.0174372f, -0.276844f, -0.132214f, -0.236278f, -0.0614254f, -0.230962f, -0.409367f, -0.08959f, 0.182197f, -0.341314f, -0.0645579f, -0.0161434f, -0.166644f, -0.0784324f, -0.387537f, 0.236617f, -0.115318f, -0.11315f, -0.109817f, -0.0949309f, -0.253715f, -0.254404f, -0.0876592f, -0.243118f, -0.219172f, 0.0341202f, 0.0203343f, 0.0435131f, -0.0266338f, 0.140304f, -0.20669f, -0.130739f, 0.0213059f, 0.182793f, -0.0711616f, -0.165651f, -0.212373f, -0.0972764f, -0.284464f, -0.0834676f, -0.129573f, -0.133945f, 0.0684521f, -0.133913f, 0.165726f, -0.176839f, -0.0940447f, -0.145421f, -0.0471074f, 0.00950449f, 0.0308656f, -0.00761046f, -0.19397f, -0.161623f, 0.10975f, -0.0398157f, 0.00168868f, 0.0626417f, -0.118388f, -0.134741f, -0.243707f, 0.146451f, -0.165854f, 0.0585878f, 0.0269307f, 0.163195f, -0.197056f, 0.0438799f, -0.152668f, -0.178631f, -0.167278f, 0.0258257f, -0.22958f, -0.101918f, 0.0360034f, -0.165612f, -0.112482f, -0.419959f, -0.369384f, 0.0468117f, 0.202511f, 0.161559f, 0.0360435f, -0.211843f, 0.0480519f, -0.252478f, -0.0951382f, 0.100791f, -0.379245f, -0.129869f, -0.036501f, 0.0685223f, 0.0247177f, -0.0751386f, -0.12451f, 0.244585f, -0.0103249f, -0.346383f, -0.300614f, 0.230366f, -0.187795f, -0.0326416f, 0.0735751f, -0.0136039f, -0.0219528f, 0.0629145f, -0.0308739f, -0.101514f, -0.169444f, 0.058706f, -0.133274f, -0.200294f, -0.372511f, -0.214898f, -0.184366f, 0.253648f, -0.0362453f, 0.0618937f, 0.0838244f, -0.0386255f, 0.129191f, -0.147435f, -0.180809f, -0.0797491f, -0.286544f, -0.273005f, 0.116222f, -0.255255f, -0.0504643f, -0.0567216f, -0.0204081f, 0.206331f, -0.225266f, -0.211665f, -0.259216f, -0.0676753f, -0.176153f, 0.285802f, -0.00560349f, -0.0253936f, -0.182537f, -0.344487f, -0.341246f, -0.171879f, 0.24462f, 0.015354f, -0.0255803f, -0.0855239f, -0.151488f, -0.0329621f, 0.311794f, 0.0889872f, -0.142655f, -0.00124048f, 0.0175189f, 0.0459686f, 0.279491f, -0.237445f, 0.0570048f, -0.00665275f, -0.0558817f, 0.0731352f, 0.0291331f, 0.0918153f, 0.0276626f, -0.135103f, -0.303909f, 0.0283329f, -0.203482f, -0.0849922f, -0.284485f, -0.214908f, 0.0836636f, -0.219738f, 0.136157f, 0.0332432f, -0.143305f, 0.0283252f, -0.178703f, -0.0742534f, -0.153174f, 0.02235f, -0.0753622f, -0.210102f, -0.0915751f, -0.0189732f, -0.239039f, -0.135349f, -0.104589f, -0.0658414f, -0.183206f, -0.123006f, 0.0835748f, -0.0703047f, -0.207461f, -0.274129f, -0.225327f, -0.113485f, 0.13316f, 0.0295303f, -0.0958281f};
+  model->setOperandValue(op84, op84_init, sizeof(float) * 2816);
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op86, op2, op1, b87, b88, b89, b90}, {op0});
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op0, op29, op28, b91, b92, b93, b94, b95}, {op27});
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op27, op32, op31, b96, b97, b98, b99}, {op30});
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op30, op35, op34, b100, b101, b102, b103, b104}, {op33});
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op33, op38, op37, b105, b106, b107, b108}, {op36});
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op36, op41, op40, b109, b110, b111, b112, b113}, {op39});
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op39, op44, op43, b114, b115, b116, b117}, {op42});
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op42, op47, op46, b118, b119, b120, b121, b122}, {op45});
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op45, op50, op49, b123, b124, b125, b126}, {op48});
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op48, op53, op52, b127, b128, b129, b130, b131}, {op51});
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op51, op56, op55, b132, b133, b134, b135}, {op54});
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op54, op59, op58, b136, b137, b138, b139, b140}, {op57});
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op57, op62, op61, b141, b142, b143, b144}, {op60});
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op60, op65, op64, b145, b146, b147, b148, b149}, {op63});
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op63, op68, op67, b150, b151, b152, b153}, {op66});
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op66, op71, op70, b154, b155, b156, b157, b158}, {op69});
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op69, op74, op73, b159, b160, b161, b162}, {op72});
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op72, op77, op76, b163, b164, b165, b166, b167}, {op75});
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op75, op80, op79, b168, b169, b170, b171}, {op78});
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op78, op5, op4, b172, b173, b174, b175, b176}, {op3});
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op3, op8, op7, b177, b178, b179, b180}, {op6});
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op6, op11, op10, b181, b182, b183, b184, b185}, {op9});
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op9, op14, op13, b186, b187, b188, b189}, {op12});
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op12, op17, op16, b190, b191, b192, b193, b194}, {op15});
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op15, op20, op19, b195, b196, b197, b198}, {op18});
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op18, op23, op22, b199, b200, b201, b202, b203}, {op21});
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op21, op26, op25, b204, b205, b206, b207}, {op24});
+  model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {op24, b208, b209, b210, b211, b212, b213}, {op81});
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op81, op84, op83, b214, b215, b216, b217}, {op82});
+  model->addOperation(ANEURALNETWORKS_LOGISTIC, {op82}, {op85});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op86},
+    {op85});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/mul_relaxed.model.cpp b/nn/runtime/test/generated/models/mul_relaxed.model.cpp
new file mode 100644
index 0000000..cd3f32d
--- /dev/null
+++ b/nn/runtime/test/generated/models/mul_relaxed.model.cpp
@@ -0,0 +1,26 @@
+// Generated file (from: mul_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  auto act = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type0);
+  // Phase 2, operations
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_MUL, {op1, op2, act}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op2},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/mul_relu_relaxed.model.cpp b/nn/runtime/test/generated/models/mul_relu_relaxed.model.cpp
new file mode 100644
index 0000000..796fe65
--- /dev/null
+++ b/nn/runtime/test/generated/models/mul_relu_relaxed.model.cpp
@@ -0,0 +1,26 @@
+// Generated file (from: mul_relu_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  auto act = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type0);
+  // Phase 2, operations
+  static int32_t act_init[] = {1};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_MUL, {op1, op2, act}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op2},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/relu1_float_1_relaxed.model.cpp b/nn/runtime/test/generated/models/relu1_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..d92509d
--- /dev/null
+++ b/nn/runtime/test/generated/models/relu1_float_1_relaxed.model.cpp
@@ -0,0 +1,21 @@
+// Generated file (from: relu1_float_1_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_RELU1, {op1}, {op2});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op2});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/relu1_float_2_relaxed.model.cpp b/nn/runtime/test/generated/models/relu1_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..5860656
--- /dev/null
+++ b/nn/runtime/test/generated/models/relu1_float_2_relaxed.model.cpp
@@ -0,0 +1,21 @@
+// Generated file (from: relu1_float_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 30, 24, 2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto output = model->addOperand(&type0);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_RELU1, {input}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/relu6_float_1_relaxed.model.cpp b/nn/runtime/test/generated/models/relu6_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..b42b10c
--- /dev/null
+++ b/nn/runtime/test/generated/models/relu6_float_1_relaxed.model.cpp
@@ -0,0 +1,21 @@
+// Generated file (from: relu6_float_1_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_RELU6, {op1}, {op2});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op2});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/relu6_float_2_relaxed.model.cpp b/nn/runtime/test/generated/models/relu6_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..564b0bd
--- /dev/null
+++ b/nn/runtime/test/generated/models/relu6_float_2_relaxed.model.cpp
@@ -0,0 +1,21 @@
+// Generated file (from: relu6_float_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 26, 40, 2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto output = model->addOperand(&type0);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_RELU6, {input}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/relu_float_1_relaxed.model.cpp b/nn/runtime/test/generated/models/relu_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..a6fe9eb
--- /dev/null
+++ b/nn/runtime/test/generated/models/relu_float_1_relaxed.model.cpp
@@ -0,0 +1,21 @@
+// Generated file (from: relu_float_1_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_RELU, {op1}, {op2});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op2});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/reshape_relaxed.model.cpp b/nn/runtime/test/generated/models/reshape_relaxed.model.cpp
new file mode 100644
index 0000000..e6d7053
--- /dev/null
+++ b/nn/runtime/test/generated/models/reshape_relaxed.model.cpp
@@ -0,0 +1,26 @@
+// Generated file (from: reshape_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 1, 3, 3});
+  OperandType type2(Type::TENSOR_FLOAT32, {9});
+  OperandType type1(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t op2_init[] = {-1};
+  model->setOperandValue(op2, op2_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_RESHAPE, {op1, op2}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/reshape_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/models/reshape_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 0000000..1d9b2ca
--- /dev/null
+++ b/nn/runtime/test/generated/models/reshape_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,24 @@
+// Generated file (from: reshape_weights_as_inputs_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 1, 3, 3});
+  OperandType type2(Type::TENSOR_FLOAT32, {9});
+  OperandType type1(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_RESHAPE, {op1, op2}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op2},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/resize_bilinear_relaxed.model.cpp b/nn/runtime/test/generated/models/resize_bilinear_relaxed.model.cpp
new file mode 100644
index 0000000..3f88a87
--- /dev/null
+++ b/nn/runtime/test/generated/models/resize_bilinear_relaxed.model.cpp
@@ -0,0 +1,29 @@
+// Generated file (from: resize_bilinear_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
+  OperandType type1(Type::TENSOR_FLOAT32, {1, 3, 3, 1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto width = model->addOperand(&type2);
+  auto height = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t width_init[] = {3};
+  model->setOperandValue(width, width_init, sizeof(int32_t) * 1);
+  static int32_t height_init[] = {3};
+  model->setOperandValue(height, height_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_RESIZE_BILINEAR, {op1, width, height}, {op2});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op2});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/rnn_relaxed.model.cpp b/nn/runtime/test/generated/models/rnn_relaxed.model.cpp
new file mode 100644
index 0000000..72e2da9
--- /dev/null
+++ b/nn/runtime/test/generated/models/rnn_relaxed.model.cpp
@@ -0,0 +1,32 @@
+// Generated file (from: rnn_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::TENSOR_FLOAT32, {16, 16});
+  OperandType type1(Type::TENSOR_FLOAT32, {16, 8});
+  OperandType type3(Type::TENSOR_FLOAT32, {16});
+  OperandType type4(Type::TENSOR_FLOAT32, {2, 16});
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 8});
+  OperandType type5(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto weights = model->addOperand(&type1);
+  auto recurrent_weights = model->addOperand(&type2);
+  auto bias = model->addOperand(&type3);
+  auto hidden_state_in = model->addOperand(&type4);
+  auto activation_param = model->addOperand(&type5);
+  auto hidden_state_out = model->addOperand(&type4);
+  auto output = model->addOperand(&type4);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_RNN, {input, weights, recurrent_weights, bias, hidden_state_in, activation_param}, {hidden_state_out, output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input, weights, recurrent_weights, bias, hidden_state_in, activation_param},
+    {hidden_state_out, output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/rnn_state_relaxed.model.cpp b/nn/runtime/test/generated/models/rnn_state_relaxed.model.cpp
new file mode 100644
index 0000000..d696df7
--- /dev/null
+++ b/nn/runtime/test/generated/models/rnn_state_relaxed.model.cpp
@@ -0,0 +1,32 @@
+// Generated file (from: rnn_state_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::TENSOR_FLOAT32, {16, 16});
+  OperandType type1(Type::TENSOR_FLOAT32, {16, 8});
+  OperandType type3(Type::TENSOR_FLOAT32, {16});
+  OperandType type4(Type::TENSOR_FLOAT32, {2, 16});
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 8});
+  OperandType type5(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto weights = model->addOperand(&type1);
+  auto recurrent_weights = model->addOperand(&type2);
+  auto bias = model->addOperand(&type3);
+  auto hidden_state_in = model->addOperand(&type4);
+  auto activation_param = model->addOperand(&type5);
+  auto hidden_state_out = model->addOperand(&type4);
+  auto output = model->addOperand(&type4);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_RNN, {input, weights, recurrent_weights, bias, hidden_state_in, activation_param}, {hidden_state_out, output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input, weights, recurrent_weights, bias, hidden_state_in, activation_param},
+    {hidden_state_out, output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/softmax_float_1_relaxed.model.cpp b/nn/runtime/test/generated/models/softmax_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..93c7f7c
--- /dev/null
+++ b/nn/runtime/test/generated/models/softmax_float_1_relaxed.model.cpp
@@ -0,0 +1,25 @@
+// Generated file (from: softmax_float_1_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::FLOAT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 4});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto beta = model->addOperand(&type1);
+  auto output = model->addOperand(&type0);
+  // Phase 2, operations
+  static float beta_init[] = {1e-06f};
+  model->setOperandValue(beta, beta_init, sizeof(float) * 1);
+  model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/softmax_float_2_relaxed.model.cpp b/nn/runtime/test/generated/models/softmax_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..ac79a38
--- /dev/null
+++ b/nn/runtime/test/generated/models/softmax_float_2_relaxed.model.cpp
@@ -0,0 +1,25 @@
+// Generated file (from: softmax_float_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::FLOAT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 5});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto beta = model->addOperand(&type1);
+  auto output = model->addOperand(&type0);
+  // Phase 2, operations
+  static float beta_init[] = {1.0f};
+  model->setOperandValue(beta, beta_init, sizeof(float) * 1);
+  model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/space_to_depth_float_1_relaxed.model.cpp b/nn/runtime/test/generated/models/space_to_depth_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..70edbf5
--- /dev/null
+++ b/nn/runtime/test/generated/models/space_to_depth_float_1_relaxed.model.cpp
@@ -0,0 +1,26 @@
+// Generated file (from: space_to_depth_float_1_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 1, 1, 8});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto block_size = model->addOperand(&type1);
+  auto output = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t block_size_init[] = {2};
+  model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_SPACE_TO_DEPTH, {input, block_size}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/space_to_depth_float_2_relaxed.model.cpp b/nn/runtime/test/generated/models/space_to_depth_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..0d14c37
--- /dev/null
+++ b/nn/runtime/test/generated/models/space_to_depth_float_2_relaxed.model.cpp
@@ -0,0 +1,26 @@
+// Generated file (from: space_to_depth_float_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 2, 2, 4});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 4, 4, 1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto block_size = model->addOperand(&type1);
+  auto output = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t block_size_init[] = {2};
+  model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_SPACE_TO_DEPTH, {input, block_size}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/space_to_depth_float_3_relaxed.model.cpp b/nn/runtime/test/generated/models/space_to_depth_float_3_relaxed.model.cpp
new file mode 100644
index 0000000..0e37f1e
--- /dev/null
+++ b/nn/runtime/test/generated/models/space_to_depth_float_3_relaxed.model.cpp
@@ -0,0 +1,26 @@
+// Generated file (from: space_to_depth_float_3_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 2, 2, 8});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 4, 4, 2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto block_size = model->addOperand(&type1);
+  auto output = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t block_size_init[] = {2};
+  model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_SPACE_TO_DEPTH, {input, block_size}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/svdf2_relaxed.model.cpp b/nn/runtime/test/generated/models/svdf2_relaxed.model.cpp
new file mode 100644
index 0000000..2f68279
--- /dev/null
+++ b/nn/runtime/test/generated/models/svdf2_relaxed.model.cpp
@@ -0,0 +1,34 @@
+// Generated file (from: svdf2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 3});
+  OperandType type6(Type::TENSOR_FLOAT32, {2, 4});
+  OperandType type4(Type::TENSOR_FLOAT32, {2, 80});
+  OperandType type3(Type::TENSOR_FLOAT32, {4});
+  OperandType type2(Type::TENSOR_FLOAT32, {8, 10});
+  OperandType type1(Type::TENSOR_FLOAT32, {8, 3});
+  OperandType type5(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto weights_feature = model->addOperand(&type1);
+  auto weights_time = model->addOperand(&type2);
+  auto bias = model->addOperand(&type3);
+  auto state_in = model->addOperand(&type4);
+  auto rank_param = model->addOperand(&type5);
+  auto activation_param = model->addOperand(&type5);
+  auto state_out = model->addOperand(&type4);
+  auto output = model->addOperand(&type6);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_SVDF, {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param}, {state_out, output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param},
+    {state_out, output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/svdf_relaxed.model.cpp b/nn/runtime/test/generated/models/svdf_relaxed.model.cpp
new file mode 100644
index 0000000..719a088
--- /dev/null
+++ b/nn/runtime/test/generated/models/svdf_relaxed.model.cpp
@@ -0,0 +1,34 @@
+// Generated file (from: svdf_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 3});
+  OperandType type4(Type::TENSOR_FLOAT32, {2, 40});
+  OperandType type6(Type::TENSOR_FLOAT32, {2, 4});
+  OperandType type2(Type::TENSOR_FLOAT32, {4, 10});
+  OperandType type1(Type::TENSOR_FLOAT32, {4, 3});
+  OperandType type3(Type::TENSOR_FLOAT32, {4});
+  OperandType type5(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto weights_feature = model->addOperand(&type1);
+  auto weights_time = model->addOperand(&type2);
+  auto bias = model->addOperand(&type3);
+  auto state_in = model->addOperand(&type4);
+  auto rank_param = model->addOperand(&type5);
+  auto activation_param = model->addOperand(&type5);
+  auto state_out = model->addOperand(&type4);
+  auto output = model->addOperand(&type6);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_SVDF, {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param}, {state_out, output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param},
+    {state_out, output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/svdf_state_relaxed.model.cpp b/nn/runtime/test/generated/models/svdf_state_relaxed.model.cpp
new file mode 100644
index 0000000..403596e
--- /dev/null
+++ b/nn/runtime/test/generated/models/svdf_state_relaxed.model.cpp
@@ -0,0 +1,34 @@
+// Generated file (from: svdf_state_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 3});
+  OperandType type4(Type::TENSOR_FLOAT32, {2, 40});
+  OperandType type6(Type::TENSOR_FLOAT32, {2, 4});
+  OperandType type2(Type::TENSOR_FLOAT32, {4, 10});
+  OperandType type1(Type::TENSOR_FLOAT32, {4, 3});
+  OperandType type3(Type::TENSOR_FLOAT32, {4});
+  OperandType type5(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto weights_feature = model->addOperand(&type1);
+  auto weights_time = model->addOperand(&type2);
+  auto bias = model->addOperand(&type3);
+  auto state_in = model->addOperand(&type4);
+  auto rank_param = model->addOperand(&type5);
+  auto activation_param = model->addOperand(&type5);
+  auto state_out = model->addOperand(&type4);
+  auto output = model->addOperand(&type6);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_SVDF, {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param}, {state_out, output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param},
+    {state_out, output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/tanh_relaxed.model.cpp b/nn/runtime/test/generated/models/tanh_relaxed.model.cpp
new file mode 100644
index 0000000..0ea2fea
--- /dev/null
+++ b/nn/runtime/test/generated/models/tanh_relaxed.model.cpp
@@ -0,0 +1,21 @@
+// Generated file (from: tanh_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_TANH, {op1}, {op2});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op2});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/add.model.cpp b/nn/runtime/test/generated/vts_models/add.model.cpp
index a609c34..7ed2122 100644
--- a/nn/runtime/test/generated/vts_models/add.model.cpp
+++ b/nn/runtime/test/generated/vts_models/add.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/add_broadcast_quant8.model.cpp b/nn/runtime/test/generated/vts_models/add_broadcast_quant8.model.cpp
index 6307ae5..2b58aad 100644
--- a/nn/runtime/test/generated/vts_models/add_broadcast_quant8.model.cpp
+++ b/nn/runtime/test/generated/vts_models/add_broadcast_quant8.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/add_quant8.model.cpp b/nn/runtime/test/generated/vts_models/add_quant8.model.cpp
index 79ccec1..1e8d60d 100644
--- a/nn/runtime/test/generated/vts_models/add_quant8.model.cpp
+++ b/nn/runtime/test/generated/vts_models/add_quant8.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/add_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/add_relaxed.model.cpp
new file mode 100644
index 0000000..9aa8a1b
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/add_relaxed.model.cpp
@@ -0,0 +1,73 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::ADD,
+            .inputs = {0, 1, 2},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/avg_pool_float_1.model.cpp b/nn/runtime/test/generated/vts_models/avg_pool_float_1.model.cpp
index 3ff21f4..25f594b 100644
--- a/nn/runtime/test/generated/vts_models/avg_pool_float_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/avg_pool_float_1.model.cpp
@@ -74,6 +74,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/avg_pool_float_1_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/avg_pool_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..e84521b
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/avg_pool_float_1_relaxed.model.cpp
@@ -0,0 +1,82 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::AVERAGE_POOL_2D,
+            .inputs = {0, 2, 2, 2, 2, 1, 1, 1, 1, 3},
+            .outputs = {4},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {4};
+    std::vector<uint8_t> operandValues = {
+      1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/avg_pool_float_2.model.cpp b/nn/runtime/test/generated/vts_models/avg_pool_float_2.model.cpp
index 031d343..579e724 100644
--- a/nn/runtime/test/generated/vts_models/avg_pool_float_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/avg_pool_float_2.model.cpp
@@ -83,6 +83,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/avg_pool_float_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/avg_pool_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..737e2cf
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/avg_pool_float_2_relaxed.model.cpp
@@ -0,0 +1,91 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {5, 52, 60, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {5, 11, 13, 3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::AVERAGE_POOL_2D,
+            .inputs = {0, 3, 3, 3, 3, 1, 1, 2, 2, 4},
+            .outputs = {5},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {5};
+    std::vector<uint8_t> operandValues = {
+      5, 0, 0, 0, 100, 0, 0, 0, 50, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/avg_pool_float_3.model.cpp b/nn/runtime/test/generated/vts_models/avg_pool_float_3.model.cpp
index 60f74ae..b741315 100644
--- a/nn/runtime/test/generated/vts_models/avg_pool_float_3.model.cpp
+++ b/nn/runtime/test/generated/vts_models/avg_pool_float_3.model.cpp
@@ -83,6 +83,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/avg_pool_float_3_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/avg_pool_float_3_relaxed.model.cpp
new file mode 100644
index 0000000..7fe8f1e
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/avg_pool_float_3_relaxed.model.cpp
@@ -0,0 +1,91 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 200, 180, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 96, 86, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::AVERAGE_POOL_2D,
+            .inputs = {0, 3, 3, 3, 3, 1, 1, 2, 2, 4},
+            .outputs = {5},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {5};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0, 10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/avg_pool_float_4.model.cpp b/nn/runtime/test/generated/vts_models/avg_pool_float_4.model.cpp
index ffce9f2..b0905ef 100644
--- a/nn/runtime/test/generated/vts_models/avg_pool_float_4.model.cpp
+++ b/nn/runtime/test/generated/vts_models/avg_pool_float_4.model.cpp
@@ -83,6 +83,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/avg_pool_float_4_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/avg_pool_float_4_relaxed.model.cpp
new file mode 100644
index 0000000..099adfc
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/avg_pool_float_4_relaxed.model.cpp
@@ -0,0 +1,91 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {5, 52, 60, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {5, 11, 13, 3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::AVERAGE_POOL_2D,
+            .inputs = {0, 3, 3, 3, 3, 1, 1, 2, 2, 4},
+            .outputs = {5},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {5};
+    std::vector<uint8_t> operandValues = {
+      5, 0, 0, 0, 100, 0, 0, 0, 50, 0, 0, 0, 3, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/avg_pool_quant8_1.model.cpp b/nn/runtime/test/generated/vts_models/avg_pool_quant8_1.model.cpp
index 491532c..a4af210 100644
--- a/nn/runtime/test/generated/vts_models/avg_pool_quant8_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/avg_pool_quant8_1.model.cpp
@@ -74,6 +74,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/avg_pool_quant8_2.model.cpp b/nn/runtime/test/generated/vts_models/avg_pool_quant8_2.model.cpp
index 5f61cef..d6c8a4f 100644
--- a/nn/runtime/test/generated/vts_models/avg_pool_quant8_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/avg_pool_quant8_2.model.cpp
@@ -83,6 +83,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/avg_pool_quant8_3.model.cpp b/nn/runtime/test/generated/vts_models/avg_pool_quant8_3.model.cpp
index 5625884..4c221d0 100644
--- a/nn/runtime/test/generated/vts_models/avg_pool_quant8_3.model.cpp
+++ b/nn/runtime/test/generated/vts_models/avg_pool_quant8_3.model.cpp
@@ -83,6 +83,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/avg_pool_quant8_4.model.cpp b/nn/runtime/test/generated/vts_models/avg_pool_quant8_4.model.cpp
index d48694a..2653509 100644
--- a/nn/runtime/test/generated/vts_models/avg_pool_quant8_4.model.cpp
+++ b/nn/runtime/test/generated/vts_models/avg_pool_quant8_4.model.cpp
@@ -74,6 +74,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/batch_to_space.model.cpp b/nn/runtime/test/generated/vts_models/batch_to_space.model.cpp
index 5e012ba..fbcb2fd 100644
--- a/nn/runtime/test/generated/vts_models/batch_to_space.model.cpp
+++ b/nn/runtime/test/generated/vts_models/batch_to_space.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/batch_to_space_float_1.model.cpp b/nn/runtime/test/generated/vts_models/batch_to_space_float_1.model.cpp
index a57f246..aa30f68 100644
--- a/nn/runtime/test/generated/vts_models/batch_to_space_float_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/batch_to_space_float_1.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/batch_to_space_quant8_1.model.cpp b/nn/runtime/test/generated/vts_models/batch_to_space_quant8_1.model.cpp
index f56bab0..1655ce7 100644
--- a/nn/runtime/test/generated/vts_models/batch_to_space_quant8_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/batch_to_space_quant8_1.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/concat_float_1.model.cpp b/nn/runtime/test/generated/vts_models/concat_float_1.model.cpp
index 3c97d6f..4033f00 100644
--- a/nn/runtime/test/generated/vts_models/concat_float_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/concat_float_1.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/concat_float_1_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/concat_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..b657995
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/concat_float_1_relaxed.model.cpp
@@ -0,0 +1,73 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::CONCATENATION,
+            .inputs = {0, 1, 2},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/concat_float_2.model.cpp b/nn/runtime/test/generated/vts_models/concat_float_2.model.cpp
index 6fe4086..d056a95 100644
--- a/nn/runtime/test/generated/vts_models/concat_float_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/concat_float_2.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/concat_float_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/concat_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..41a1a4a
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/concat_float_2_relaxed.model.cpp
@@ -0,0 +1,73 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {52, 230},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {40, 230},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {92, 230},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::CONCATENATION,
+            .inputs = {0, 1, 2},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/concat_float_3.model.cpp b/nn/runtime/test/generated/vts_models/concat_float_3.model.cpp
index 4760d07..71eb2b1 100644
--- a/nn/runtime/test/generated/vts_models/concat_float_3.model.cpp
+++ b/nn/runtime/test/generated/vts_models/concat_float_3.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/concat_float_3_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/concat_float_3_relaxed.model.cpp
new file mode 100644
index 0000000..77af7c1
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/concat_float_3_relaxed.model.cpp
@@ -0,0 +1,73 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {212, 60},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {212, 30},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {212, 90},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::CONCATENATION,
+            .inputs = {0, 1, 2},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      1, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/concat_quant8_1.model.cpp b/nn/runtime/test/generated/vts_models/concat_quant8_1.model.cpp
index e0e66db..66b3e6c 100644
--- a/nn/runtime/test/generated/vts_models/concat_quant8_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/concat_quant8_1.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/concat_quant8_2.model.cpp b/nn/runtime/test/generated/vts_models/concat_quant8_2.model.cpp
index 945f495..0d81a96 100644
--- a/nn/runtime/test/generated/vts_models/concat_quant8_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/concat_quant8_2.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/concat_quant8_3.model.cpp b/nn/runtime/test/generated/vts_models/concat_quant8_3.model.cpp
index c6b0cc8..8ffd0a2 100644
--- a/nn/runtime/test/generated/vts_models/concat_quant8_3.model.cpp
+++ b/nn/runtime/test/generated/vts_models/concat_quant8_3.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/conv_1_h3_w2_SAME.model.cpp b/nn/runtime/test/generated/vts_models/conv_1_h3_w2_SAME.model.cpp
index 904e648..62700e6 100644
--- a/nn/runtime/test/generated/vts_models/conv_1_h3_w2_SAME.model.cpp
+++ b/nn/runtime/test/generated/vts_models/conv_1_h3_w2_SAME.model.cpp
@@ -101,6 +101,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/conv_1_h3_w2_SAME_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/conv_1_h3_w2_SAME_relaxed.model.cpp
new file mode 100644
index 0000000..91f5113
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/conv_1_h3_w2_SAME_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 8, 8, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 8, 8, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3, 2, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 72},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 88, .length = 4},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {4, 6, 7, 0, 1, 2, 3},
+            .outputs = {5},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {4};
+    const std::vector<uint32_t> outputIndexes = {5};
+    std::vector<uint8_t> operandValues = {
+      1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 188, 89, 119, 191, 193, 88, 239, 190, 143, 112, 82, 191, 42, 87, 20, 191, 124, 102, 228, 60, 105, 169, 76, 191, 153, 43, 47, 191, 94, 48, 16, 63, 112, 235, 190, 62, 185, 251, 60, 63, 177, 167, 197, 62, 77, 243, 106, 191, 177, 191, 60, 62, 228, 135, 138, 190, 47, 134, 82, 63, 8, 105, 199, 61, 144, 249, 112, 191, 207, 45, 20, 190, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/conv_1_h3_w2_VALID.model.cpp b/nn/runtime/test/generated/vts_models/conv_1_h3_w2_VALID.model.cpp
index b98701a..ae706b4 100644
--- a/nn/runtime/test/generated/vts_models/conv_1_h3_w2_VALID.model.cpp
+++ b/nn/runtime/test/generated/vts_models/conv_1_h3_w2_VALID.model.cpp
@@ -101,6 +101,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/conv_1_h3_w2_VALID_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/conv_1_h3_w2_VALID_relaxed.model.cpp
new file mode 100644
index 0000000..c69fe7e
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/conv_1_h3_w2_VALID_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 8, 8, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 6, 7, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3, 2, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 72},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 88, .length = 4},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {4, 6, 7, 0, 1, 2, 3},
+            .outputs = {5},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {4};
+    const std::vector<uint32_t> outputIndexes = {5};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 188, 89, 119, 191, 193, 88, 239, 190, 143, 112, 82, 191, 42, 87, 20, 191, 124, 102, 228, 60, 105, 169, 76, 191, 153, 43, 47, 191, 94, 48, 16, 63, 112, 235, 190, 62, 185, 251, 60, 63, 177, 167, 197, 62, 77, 243, 106, 191, 177, 191, 60, 62, 228, 135, 138, 190, 47, 134, 82, 63, 8, 105, 199, 61, 144, 249, 112, 191, 207, 45, 20, 190, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/conv_3_h3_w2_SAME.model.cpp b/nn/runtime/test/generated/vts_models/conv_3_h3_w2_SAME.model.cpp
index 1dd63f7..8da1e2c 100644
--- a/nn/runtime/test/generated/vts_models/conv_3_h3_w2_SAME.model.cpp
+++ b/nn/runtime/test/generated/vts_models/conv_3_h3_w2_SAME.model.cpp
@@ -101,6 +101,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/conv_3_h3_w2_SAME_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/conv_3_h3_w2_SAME_relaxed.model.cpp
new file mode 100644
index 0000000..8679c41
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/conv_3_h3_w2_SAME_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 8, 8, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 8, 8, 3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3, 3, 2, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 216},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 232, .length = 12},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {4, 6, 7, 0, 1, 2, 3},
+            .outputs = {5},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {4};
+    const std::vector<uint32_t> outputIndexes = {5};
+    std::vector<uint8_t> operandValues = {
+      1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 188, 89, 119, 191, 42, 87, 20, 191, 153, 43, 47, 191, 185, 251, 60, 63, 177, 191, 60, 62, 8, 105, 199, 61, 147, 27, 53, 190, 202, 26, 117, 190, 233, 189, 116, 185, 52, 132, 99, 61, 230, 61, 110, 190, 181, 255, 161, 190, 76, 107, 83, 188, 114, 51, 164, 62, 150, 63, 167, 190, 193, 111, 107, 191, 142, 58, 94, 63, 131, 25, 83, 191, 193, 88, 239, 190, 124, 102, 228, 60, 94, 48, 16, 63, 177, 167, 197, 62, 228, 135, 138, 190, 144, 249, 112, 191, 108, 123, 71, 191, 72, 226, 133, 190, 142, 89, 70, 191, 65, 241, 75, 191, 159, 31, 102, 62, 180, 32, 212, 190, 242, 150, 47, 63, 90, 212, 167, 190, 150, 33, 70, 63, 149, 238, 54, 191, 234, 236, 120, 191, 163, 143, 142, 61, 143, 112, 82, 191, 105, 169, 76, 191, 112, 235, 190, 62, 77, 243, 106, 191, 47, 134, 82, 63, 207, 45, 20, 190, 85, 51, 43, 190, 108, 63, 137, 62, 72, 224, 51, 63, 229, 14, 211, 190, 108, 121, 65, 63, 78, 183, 56, 63, 227, 107, 223, 190, 89, 192, 140, 190, 255, 207, 137, 190, 109, 226, 36, 62, 38, 226, 81, 63, 131, 191, 159, 190, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/conv_3_h3_w2_VALID.model.cpp b/nn/runtime/test/generated/vts_models/conv_3_h3_w2_VALID.model.cpp
index c09be8e..2500e50 100644
--- a/nn/runtime/test/generated/vts_models/conv_3_h3_w2_VALID.model.cpp
+++ b/nn/runtime/test/generated/vts_models/conv_3_h3_w2_VALID.model.cpp
@@ -101,6 +101,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/conv_3_h3_w2_VALID_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/conv_3_h3_w2_VALID_relaxed.model.cpp
new file mode 100644
index 0000000..be03714
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/conv_3_h3_w2_VALID_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 8, 8, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 6, 7, 3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3, 3, 2, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 216},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 232, .length = 12},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {4, 6, 7, 0, 1, 2, 3},
+            .outputs = {5},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {4};
+    const std::vector<uint32_t> outputIndexes = {5};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 188, 89, 119, 191, 42, 87, 20, 191, 153, 43, 47, 191, 185, 251, 60, 63, 177, 191, 60, 62, 8, 105, 199, 61, 147, 27, 53, 190, 202, 26, 117, 190, 233, 189, 116, 185, 52, 132, 99, 61, 230, 61, 110, 190, 181, 255, 161, 190, 76, 107, 83, 188, 114, 51, 164, 62, 150, 63, 167, 190, 193, 111, 107, 191, 142, 58, 94, 63, 131, 25, 83, 191, 193, 88, 239, 190, 124, 102, 228, 60, 94, 48, 16, 63, 177, 167, 197, 62, 228, 135, 138, 190, 144, 249, 112, 191, 108, 123, 71, 191, 72, 226, 133, 190, 142, 89, 70, 191, 65, 241, 75, 191, 159, 31, 102, 62, 180, 32, 212, 190, 242, 150, 47, 63, 90, 212, 167, 190, 150, 33, 70, 63, 149, 238, 54, 191, 234, 236, 120, 191, 163, 143, 142, 61, 143, 112, 82, 191, 105, 169, 76, 191, 112, 235, 190, 62, 77, 243, 106, 191, 47, 134, 82, 63, 207, 45, 20, 190, 85, 51, 43, 190, 108, 63, 137, 62, 72, 224, 51, 63, 229, 14, 211, 190, 108, 121, 65, 63, 78, 183, 56, 63, 227, 107, 223, 190, 89, 192, 140, 190, 255, 207, 137, 190, 109, 226, 36, 62, 38, 226, 81, 63, 131, 191, 159, 190, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/conv_float.model.cpp b/nn/runtime/test/generated/vts_models/conv_float.model.cpp
index 75e5166..96b7c64 100644
--- a/nn/runtime/test/generated/vts_models/conv_float.model.cpp
+++ b/nn/runtime/test/generated/vts_models/conv_float.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/conv_float_channels.model.cpp b/nn/runtime/test/generated/vts_models/conv_float_channels.model.cpp
index d6b2a0a..b369f31 100644
--- a/nn/runtime/test/generated/vts_models/conv_float_channels.model.cpp
+++ b/nn/runtime/test/generated/vts_models/conv_float_channels.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/conv_float_channels_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/conv_float_channels_relaxed.model.cpp
new file mode 100644
index 0000000..b799012
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/conv_float_channels_relaxed.model.cpp
@@ -0,0 +1,100 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3, 1, 1, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 36},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 36, .length = 12},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 48, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 52, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 56, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {0, 1, 2, 3, 3, 3, 3, 5, 5, 4},
+            .outputs = {6},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {6};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 128, 63, 0, 0, 0, 64, 0, 0, 0, 64, 0, 0, 0, 64, 0, 0, 64, 64, 0, 0, 64, 64, 0, 0, 64, 64, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/conv_float_channels_weights_as_inputs.model.cpp b/nn/runtime/test/generated/vts_models/conv_float_channels_weights_as_inputs.model.cpp
index 8983b1f..6a670ff 100644
--- a/nn/runtime/test/generated/vts_models/conv_float_channels_weights_as_inputs.model.cpp
+++ b/nn/runtime/test/generated/vts_models/conv_float_channels_weights_as_inputs.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/conv_float_channels_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/conv_float_channels_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 0000000..1b0bf01
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/conv_float_channels_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,100 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3, 1, 1, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {0, 1, 2, 3, 3, 3, 3, 5, 5, 4},
+            .outputs = {6},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2};
+    const std::vector<uint32_t> outputIndexes = {6};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/conv_float_large.model.cpp b/nn/runtime/test/generated/vts_models/conv_float_large.model.cpp
index e0890ed..af6e11d 100644
--- a/nn/runtime/test/generated/vts_models/conv_float_large.model.cpp
+++ b/nn/runtime/test/generated/vts_models/conv_float_large.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/conv_float_large_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/conv_float_large_relaxed.model.cpp
new file mode 100644
index 0000000..a610938
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/conv_float_large_relaxed.model.cpp
@@ -0,0 +1,100 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 3, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3, 1, 1, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 36},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 36, .length = 12},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 48, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 52, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 56, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 3, 3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {0, 1, 2, 3, 3, 3, 3, 5, 5, 4},
+            .outputs = {6},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {6};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 128, 63, 0, 0, 128, 64, 0, 0, 224, 64, 0, 0, 0, 64, 0, 0, 160, 64, 0, 0, 0, 65, 0, 0, 64, 64, 0, 0, 192, 64, 0, 0, 16, 65, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/conv_float_large_weights_as_inputs.model.cpp b/nn/runtime/test/generated/vts_models/conv_float_large_weights_as_inputs.model.cpp
index 15bea35..b386914 100644
--- a/nn/runtime/test/generated/vts_models/conv_float_large_weights_as_inputs.model.cpp
+++ b/nn/runtime/test/generated/vts_models/conv_float_large_weights_as_inputs.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/conv_float_large_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/conv_float_large_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 0000000..cd2ff86
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/conv_float_large_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,100 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 3, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3, 1, 1, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 3, 3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {0, 1, 2, 3, 3, 3, 3, 5, 5, 4},
+            .outputs = {6},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2};
+    const std::vector<uint32_t> outputIndexes = {6};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/conv_float_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/conv_float_relaxed.model.cpp
new file mode 100644
index 0000000..18820d7
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/conv_float_relaxed.model.cpp
@@ -0,0 +1,100 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3, 3, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 16},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 20, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 24, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 28, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {0, 1, 2, 3, 3, 3, 3, 5, 5, 4},
+            .outputs = {6},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {6};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 128, 62, 0, 0, 128, 62, 0, 0, 128, 62, 0, 0, 128, 62, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/conv_float_weights_as_inputs.model.cpp b/nn/runtime/test/generated/vts_models/conv_float_weights_as_inputs.model.cpp
index 7d273c5..1ff5af1 100644
--- a/nn/runtime/test/generated/vts_models/conv_float_weights_as_inputs.model.cpp
+++ b/nn/runtime/test/generated/vts_models/conv_float_weights_as_inputs.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/conv_float_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/conv_float_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 0000000..31768e0
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/conv_float_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,100 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3, 3, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {0, 1, 2, 3, 3, 3, 3, 5, 5, 4},
+            .outputs = {6},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2};
+    const std::vector<uint32_t> outputIndexes = {6};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/conv_quant8.model.cpp b/nn/runtime/test/generated/vts_models/conv_quant8.model.cpp
index f7b251f..b9e6856 100644
--- a/nn/runtime/test/generated/vts_models/conv_quant8.model.cpp
+++ b/nn/runtime/test/generated/vts_models/conv_quant8.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/conv_quant8_channels.model.cpp b/nn/runtime/test/generated/vts_models/conv_quant8_channels.model.cpp
index 24a4be7..af1c0c6 100644
--- a/nn/runtime/test/generated/vts_models/conv_quant8_channels.model.cpp
+++ b/nn/runtime/test/generated/vts_models/conv_quant8_channels.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/conv_quant8_channels_weights_as_inputs.model.cpp b/nn/runtime/test/generated/vts_models/conv_quant8_channels_weights_as_inputs.model.cpp
index 7e16a39..0a3706f 100644
--- a/nn/runtime/test/generated/vts_models/conv_quant8_channels_weights_as_inputs.model.cpp
+++ b/nn/runtime/test/generated/vts_models/conv_quant8_channels_weights_as_inputs.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/conv_quant8_large.model.cpp b/nn/runtime/test/generated/vts_models/conv_quant8_large.model.cpp
index 5a13361..ca81f11 100644
--- a/nn/runtime/test/generated/vts_models/conv_quant8_large.model.cpp
+++ b/nn/runtime/test/generated/vts_models/conv_quant8_large.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/conv_quant8_large_weights_as_inputs.model.cpp b/nn/runtime/test/generated/vts_models/conv_quant8_large_weights_as_inputs.model.cpp
index d683523..abc8e45 100644
--- a/nn/runtime/test/generated/vts_models/conv_quant8_large_weights_as_inputs.model.cpp
+++ b/nn/runtime/test/generated/vts_models/conv_quant8_large_weights_as_inputs.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/conv_quant8_overflow.model.cpp b/nn/runtime/test/generated/vts_models/conv_quant8_overflow.model.cpp
index 939065a..dc7f179 100644
--- a/nn/runtime/test/generated/vts_models/conv_quant8_overflow.model.cpp
+++ b/nn/runtime/test/generated/vts_models/conv_quant8_overflow.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/conv_quant8_overflow_weights_as_inputs.model.cpp b/nn/runtime/test/generated/vts_models/conv_quant8_overflow_weights_as_inputs.model.cpp
index d683523..abc8e45 100644
--- a/nn/runtime/test/generated/vts_models/conv_quant8_overflow_weights_as_inputs.model.cpp
+++ b/nn/runtime/test/generated/vts_models/conv_quant8_overflow_weights_as_inputs.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/conv_quant8_weights_as_inputs.model.cpp b/nn/runtime/test/generated/vts_models/conv_quant8_weights_as_inputs.model.cpp
index 90e8170..1962efa 100644
--- a/nn/runtime/test/generated/vts_models/conv_quant8_weights_as_inputs.model.cpp
+++ b/nn/runtime/test/generated/vts_models/conv_quant8_weights_as_inputs.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/depth_to_space_float_1.model.cpp b/nn/runtime/test/generated/vts_models/depth_to_space_float_1.model.cpp
index e4d79a0..405488f 100644
--- a/nn/runtime/test/generated/vts_models/depth_to_space_float_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/depth_to_space_float_1.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/depth_to_space_float_1_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/depth_to_space_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..9e02bc6
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/depth_to_space_float_1_relaxed.model.cpp
@@ -0,0 +1,64 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 8},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::DEPTH_TO_SPACE,
+            .inputs = {0, 1},
+            .outputs = {2},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {2};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/depth_to_space_float_2.model.cpp b/nn/runtime/test/generated/vts_models/depth_to_space_float_2.model.cpp
index eb7f25c..8f6d435 100644
--- a/nn/runtime/test/generated/vts_models/depth_to_space_float_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/depth_to_space_float_2.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/depth_to_space_float_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/depth_to_space_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..3319765
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/depth_to_space_float_2_relaxed.model.cpp
@@ -0,0 +1,64 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4, 4, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::DEPTH_TO_SPACE,
+            .inputs = {0, 1},
+            .outputs = {2},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {2};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/depth_to_space_float_3.model.cpp b/nn/runtime/test/generated/vts_models/depth_to_space_float_3.model.cpp
index 974982a..954d35e 100644
--- a/nn/runtime/test/generated/vts_models/depth_to_space_float_3.model.cpp
+++ b/nn/runtime/test/generated/vts_models/depth_to_space_float_3.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/depth_to_space_float_3_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/depth_to_space_float_3_relaxed.model.cpp
new file mode 100644
index 0000000..d5c8781
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/depth_to_space_float_3_relaxed.model.cpp
@@ -0,0 +1,64 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 8},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4, 4, 2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::DEPTH_TO_SPACE,
+            .inputs = {0, 1},
+            .outputs = {2},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {2};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/depth_to_space_quant8_1.model.cpp b/nn/runtime/test/generated/vts_models/depth_to_space_quant8_1.model.cpp
index feb5c19..c6e9c8c 100644
--- a/nn/runtime/test/generated/vts_models/depth_to_space_quant8_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/depth_to_space_quant8_1.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/depth_to_space_quant8_2.model.cpp b/nn/runtime/test/generated/vts_models/depth_to_space_quant8_2.model.cpp
index 404c79b..a3eb804 100644
--- a/nn/runtime/test/generated/vts_models/depth_to_space_quant8_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/depth_to_space_quant8_2.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv.model.cpp
index dbf3238..7c96357 100644
--- a/nn/runtime/test/generated/vts_models/depthwise_conv.model.cpp
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv.model.cpp
@@ -110,6 +110,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float.model.cpp
index 8e89fe1..7d1bd6b 100644
--- a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float.model.cpp
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float.model.cpp
@@ -101,6 +101,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large.model.cpp
index dd817e5..afcae23 100644
--- a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large.model.cpp
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large.model.cpp
@@ -101,6 +101,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2.model.cpp
index c949f8c..24a6e99 100644
--- a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2.model.cpp
@@ -101,6 +101,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2_weights_as_inputs.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2_weights_as_inputs.model.cpp
index 11e0b9d..70ca484 100644
--- a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2_weights_as_inputs.model.cpp
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2_weights_as_inputs.model.cpp
@@ -101,6 +101,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_relaxed.model.cpp
new file mode 100644
index 0000000..9f53c64
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 32},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 32, .length = 8},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 40, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 44, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 48, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 52, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {0, 1, 2, 3, 3, 3, 3, 5, 5, 6, 4},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 128, 62, 0, 0, 0, 0, 0, 0, 128, 62, 0, 0, 128, 63, 0, 0, 128, 62, 0, 0, 0, 0, 0, 0, 128, 62, 0, 0, 128, 63, 0, 0, 200, 66, 0, 0, 72, 67, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_weights_as_inputs.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_weights_as_inputs.model.cpp
index 4343e2b..f0483d6 100644
--- a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_weights_as_inputs.model.cpp
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_weights_as_inputs.model.cpp
@@ -101,6 +101,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 0000000..a768b7b
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {0, 1, 2, 3, 3, 3, 3, 5, 5, 6, 4},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_weights_as_inputs.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_weights_as_inputs.model.cpp
index 49d6e99..ddaff2b 100644
--- a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_weights_as_inputs.model.cpp
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_weights_as_inputs.model.cpp
@@ -101,6 +101,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv2d_quant8.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv2d_quant8.model.cpp
index f016869..611d2d8 100644
--- a/nn/runtime/test/generated/vts_models/depthwise_conv2d_quant8.model.cpp
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv2d_quant8.model.cpp
@@ -101,6 +101,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv2d_quant8_large.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv2d_quant8_large.model.cpp
index a623164..3ce6d84 100644
--- a/nn/runtime/test/generated/vts_models/depthwise_conv2d_quant8_large.model.cpp
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv2d_quant8_large.model.cpp
@@ -101,6 +101,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv2d_quant8_large_weights_as_inputs.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv2d_quant8_large_weights_as_inputs.model.cpp
index 236b398..fe5c40a 100644
--- a/nn/runtime/test/generated/vts_models/depthwise_conv2d_quant8_large_weights_as_inputs.model.cpp
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv2d_quant8_large_weights_as_inputs.model.cpp
@@ -101,6 +101,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv2d_quant8_weights_as_inputs.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv2d_quant8_weights_as_inputs.model.cpp
index 0e040cf..4ec9a1d 100644
--- a/nn/runtime/test/generated/vts_models/depthwise_conv2d_quant8_weights_as_inputs.model.cpp
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv2d_quant8_weights_as_inputs.model.cpp
@@ -101,6 +101,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv_relaxed.model.cpp
new file mode 100644
index 0000000..7c96357
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv_relaxed.model.cpp
@@ -0,0 +1,117 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 8, 8, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 8, 8, 3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 20, .length = 12},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 32, .length = 12},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {5, 7, 8, 0, 1, 2, 3, 4},
+            .outputs = {6},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {5};
+    const std::vector<uint32_t> outputIndexes = {6};
+    std::vector<uint8_t> operandValues = {
+      1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 188, 89, 119, 191, 193, 88, 239, 190, 143, 112, 82, 191, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/dequantize.model.cpp b/nn/runtime/test/generated/vts_models/dequantize.model.cpp
index d3c2e45..905e7a8 100644
--- a/nn/runtime/test/generated/vts_models/dequantize.model.cpp
+++ b/nn/runtime/test/generated/vts_models/dequantize.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/div.model.cpp b/nn/runtime/test/generated/vts_models/div.model.cpp
index 875f21f..86792e9 100644
--- a/nn/runtime/test/generated/vts_models/div.model.cpp
+++ b/nn/runtime/test/generated/vts_models/div.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/embedding_lookup.model.cpp b/nn/runtime/test/generated/vts_models/embedding_lookup.model.cpp
index ce2b4b3..3a61dba 100644
--- a/nn/runtime/test/generated/vts_models/embedding_lookup.model.cpp
+++ b/nn/runtime/test/generated/vts_models/embedding_lookup.model.cpp
@@ -54,6 +54,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/embedding_lookup_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/embedding_lookup_relaxed.model.cpp
new file mode 100644
index 0000000..70a4287
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/embedding_lookup_relaxed.model.cpp
@@ -0,0 +1,62 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3, 2, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3, 2, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::EMBEDDING_LOOKUP,
+            .inputs = {0, 1},
+            .outputs = {2},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1};
+    const std::vector<uint32_t> outputIndexes = {2};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/floor.model.cpp b/nn/runtime/test/generated/vts_models/floor.model.cpp
index aabd681..64580eb 100644
--- a/nn/runtime/test/generated/vts_models/floor.model.cpp
+++ b/nn/runtime/test/generated/vts_models/floor.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/floor_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/floor_relaxed.model.cpp
new file mode 100644
index 0000000..7f8962f
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/floor_relaxed.model.cpp
@@ -0,0 +1,53 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::FLOOR,
+            .inputs = {0},
+            .outputs = {1},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {1};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/fully_connected_float.model.cpp b/nn/runtime/test/generated/vts_models/fully_connected_float.model.cpp
index e0118b9..2179c27 100644
--- a/nn/runtime/test/generated/vts_models/fully_connected_float.model.cpp
+++ b/nn/runtime/test/generated/vts_models/fully_connected_float.model.cpp
@@ -74,6 +74,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/fully_connected_float_large.model.cpp b/nn/runtime/test/generated/vts_models/fully_connected_float_large.model.cpp
index 5db446d..1bf8618 100644
--- a/nn/runtime/test/generated/vts_models/fully_connected_float_large.model.cpp
+++ b/nn/runtime/test/generated/vts_models/fully_connected_float_large.model.cpp
@@ -74,6 +74,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/fully_connected_float_large_weights_as_inputs.model.cpp b/nn/runtime/test/generated/vts_models/fully_connected_float_large_weights_as_inputs.model.cpp
index d2f9495..566baf7 100644
--- a/nn/runtime/test/generated/vts_models/fully_connected_float_large_weights_as_inputs.model.cpp
+++ b/nn/runtime/test/generated/vts_models/fully_connected_float_large_weights_as_inputs.model.cpp
@@ -74,6 +74,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/fully_connected_float_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/fully_connected_float_relaxed.model.cpp
new file mode 100644
index 0000000..0c3ff95
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/fully_connected_float_relaxed.model.cpp
@@ -0,0 +1,82 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::FULLY_CONNECTED,
+            .inputs = {0, 1, 2, 4},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 64, 0, 0, 128, 64, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/fully_connected_float_weights_as_inputs.model.cpp b/nn/runtime/test/generated/vts_models/fully_connected_float_weights_as_inputs.model.cpp
index 78e2cc9..a46d954 100644
--- a/nn/runtime/test/generated/vts_models/fully_connected_float_weights_as_inputs.model.cpp
+++ b/nn/runtime/test/generated/vts_models/fully_connected_float_weights_as_inputs.model.cpp
@@ -74,6 +74,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/fully_connected_float_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/fully_connected_float_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 0000000..a001e1e
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/fully_connected_float_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,82 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::FULLY_CONNECTED,
+            .inputs = {0, 1, 2, 4},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/fully_connected_quant8.model.cpp b/nn/runtime/test/generated/vts_models/fully_connected_quant8.model.cpp
index f9d7422..d1d6c62 100644
--- a/nn/runtime/test/generated/vts_models/fully_connected_quant8.model.cpp
+++ b/nn/runtime/test/generated/vts_models/fully_connected_quant8.model.cpp
@@ -74,6 +74,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/fully_connected_quant8_large.model.cpp b/nn/runtime/test/generated/vts_models/fully_connected_quant8_large.model.cpp
index 9ec84fc..050a0f8 100644
--- a/nn/runtime/test/generated/vts_models/fully_connected_quant8_large.model.cpp
+++ b/nn/runtime/test/generated/vts_models/fully_connected_quant8_large.model.cpp
@@ -74,6 +74,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/fully_connected_quant8_large_weights_as_inputs.model.cpp b/nn/runtime/test/generated/vts_models/fully_connected_quant8_large_weights_as_inputs.model.cpp
index 274621a..560091c 100644
--- a/nn/runtime/test/generated/vts_models/fully_connected_quant8_large_weights_as_inputs.model.cpp
+++ b/nn/runtime/test/generated/vts_models/fully_connected_quant8_large_weights_as_inputs.model.cpp
@@ -74,6 +74,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/fully_connected_quant8_weights_as_inputs.model.cpp b/nn/runtime/test/generated/vts_models/fully_connected_quant8_weights_as_inputs.model.cpp
index 1fa69cd..71d88c4 100644
--- a/nn/runtime/test/generated/vts_models/fully_connected_quant8_weights_as_inputs.model.cpp
+++ b/nn/runtime/test/generated/vts_models/fully_connected_quant8_weights_as_inputs.model.cpp
@@ -74,6 +74,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/hashtable_lookup_float.model.cpp b/nn/runtime/test/generated/vts_models/hashtable_lookup_float.model.cpp
index a8b1a24..f0246f5 100644
--- a/nn/runtime/test/generated/vts_models/hashtable_lookup_float.model.cpp
+++ b/nn/runtime/test/generated/vts_models/hashtable_lookup_float.model.cpp
@@ -72,6 +72,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/hashtable_lookup_float_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/hashtable_lookup_float_relaxed.model.cpp
new file mode 100644
index 0000000..0908076
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/hashtable_lookup_float_relaxed.model.cpp
@@ -0,0 +1,80 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_QUANT8_ASYMM,
+            .dimensions = {4},
+            .numberOfConsumers = 0,
+            .scale = 1.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::HASHTABLE_LOOKUP,
+            .inputs = {0, 1, 2},
+            .outputs = {3, 4},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2};
+    const std::vector<uint32_t> outputIndexes = {3, 4};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/hashtable_lookup_quant8.model.cpp b/nn/runtime/test/generated/vts_models/hashtable_lookup_quant8.model.cpp
index 4acde61..72c9e5a 100644
--- a/nn/runtime/test/generated/vts_models/hashtable_lookup_quant8.model.cpp
+++ b/nn/runtime/test/generated/vts_models/hashtable_lookup_quant8.model.cpp
@@ -72,6 +72,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/l2_normalization.model.cpp b/nn/runtime/test/generated/vts_models/l2_normalization.model.cpp
index ee2b95e..b7fd00c 100644
--- a/nn/runtime/test/generated/vts_models/l2_normalization.model.cpp
+++ b/nn/runtime/test/generated/vts_models/l2_normalization.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/l2_normalization_large.model.cpp b/nn/runtime/test/generated/vts_models/l2_normalization_large.model.cpp
index be588d3..2ce631c 100644
--- a/nn/runtime/test/generated/vts_models/l2_normalization_large.model.cpp
+++ b/nn/runtime/test/generated/vts_models/l2_normalization_large.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/l2_normalization_large_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/l2_normalization_large_relaxed.model.cpp
new file mode 100644
index 0000000..a58e43e
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/l2_normalization_large_relaxed.model.cpp
@@ -0,0 +1,53 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::L2_NORMALIZATION,
+            .inputs = {0},
+            .outputs = {1},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {1};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/l2_normalization_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/l2_normalization_relaxed.model.cpp
new file mode 100644
index 0000000..3b31617
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/l2_normalization_relaxed.model.cpp
@@ -0,0 +1,53 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::L2_NORMALIZATION,
+            .inputs = {0},
+            .outputs = {1},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {1};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/l2_pool_float.model.cpp b/nn/runtime/test/generated/vts_models/l2_pool_float.model.cpp
index 585b22f..f63b83b 100644
--- a/nn/runtime/test/generated/vts_models/l2_pool_float.model.cpp
+++ b/nn/runtime/test/generated/vts_models/l2_pool_float.model.cpp
@@ -74,6 +74,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/l2_pool_float_large.model.cpp b/nn/runtime/test/generated/vts_models/l2_pool_float_large.model.cpp
index 4242b84..f718592 100644
--- a/nn/runtime/test/generated/vts_models/l2_pool_float_large.model.cpp
+++ b/nn/runtime/test/generated/vts_models/l2_pool_float_large.model.cpp
@@ -101,6 +101,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/l2_pool_float_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/l2_pool_float_relaxed.model.cpp
new file mode 100644
index 0000000..99c2ecd
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/l2_pool_float_relaxed.model.cpp
@@ -0,0 +1,82 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::L2_POOL_2D,
+            .inputs = {0, 2, 2, 2, 2, 1, 1, 1, 1, 3},
+            .outputs = {4},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {4};
+    std::vector<uint8_t> operandValues = {
+      1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/local_response_norm_float_1.model.cpp b/nn/runtime/test/generated/vts_models/local_response_norm_float_1.model.cpp
index bbaa66e..cfb6de8 100644
--- a/nn/runtime/test/generated/vts_models/local_response_norm_float_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/local_response_norm_float_1.model.cpp
@@ -83,6 +83,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/local_response_norm_float_1_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/local_response_norm_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..7ae54fa
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/local_response_norm_float_1_relaxed.model.cpp
@@ -0,0 +1,91 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 6},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::FLOAT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::FLOAT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::FLOAT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 6},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::LOCAL_RESPONSE_NORMALIZATION,
+            .inputs = {0, 1, 2, 3, 4},
+            .outputs = {5},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {5};
+    std::vector<uint8_t> operandValues = {
+      20, 0, 0, 0, 0, 0, 16, 65, 0, 0, 128, 64, 0, 0, 0, 63
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/local_response_norm_float_2.model.cpp b/nn/runtime/test/generated/vts_models/local_response_norm_float_2.model.cpp
index f7322f3..39e117c 100644
--- a/nn/runtime/test/generated/vts_models/local_response_norm_float_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/local_response_norm_float_2.model.cpp
@@ -83,6 +83,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/local_response_norm_float_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/local_response_norm_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..c74d513
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/local_response_norm_float_2_relaxed.model.cpp
@@ -0,0 +1,91 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 6},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::FLOAT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::FLOAT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::FLOAT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 6},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::LOCAL_RESPONSE_NORMALIZATION,
+            .inputs = {0, 1, 2, 3, 4},
+            .outputs = {5},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {5};
+    std::vector<uint8_t> operandValues = {
+      20, 0, 0, 0, 0, 0, 0, 0, 0, 0, 128, 63, 0, 0, 0, 63
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/local_response_norm_float_3.model.cpp b/nn/runtime/test/generated/vts_models/local_response_norm_float_3.model.cpp
index 1cd1f8f..17dfd7a 100644
--- a/nn/runtime/test/generated/vts_models/local_response_norm_float_3.model.cpp
+++ b/nn/runtime/test/generated/vts_models/local_response_norm_float_3.model.cpp
@@ -83,6 +83,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/local_response_norm_float_3_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/local_response_norm_float_3_relaxed.model.cpp
new file mode 100644
index 0000000..9c797c7
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/local_response_norm_float_3_relaxed.model.cpp
@@ -0,0 +1,91 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 6},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::FLOAT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::FLOAT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::FLOAT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 6},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::LOCAL_RESPONSE_NORMALIZATION,
+            .inputs = {0, 1, 2, 3, 4},
+            .outputs = {5},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {5};
+    std::vector<uint8_t> operandValues = {
+      20, 0, 0, 0, 0, 0, 0, 0, 0, 0, 128, 64, 0, 0, 0, 63
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/local_response_norm_float_4.model.cpp b/nn/runtime/test/generated/vts_models/local_response_norm_float_4.model.cpp
index 0a54bd8..2dcf3e4 100644
--- a/nn/runtime/test/generated/vts_models/local_response_norm_float_4.model.cpp
+++ b/nn/runtime/test/generated/vts_models/local_response_norm_float_4.model.cpp
@@ -83,6 +83,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/local_response_norm_float_4_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/local_response_norm_float_4_relaxed.model.cpp
new file mode 100644
index 0000000..6d37008
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/local_response_norm_float_4_relaxed.model.cpp
@@ -0,0 +1,91 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 6},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::FLOAT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::FLOAT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::FLOAT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 6},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::LOCAL_RESPONSE_NORMALIZATION,
+            .inputs = {0, 1, 2, 3, 4},
+            .outputs = {5},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {5};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0, 0, 0, 16, 65, 0, 0, 128, 64, 0, 0, 0, 63
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/logistic_float_1.model.cpp b/nn/runtime/test/generated/vts_models/logistic_float_1.model.cpp
index 541d258..fd1207f 100644
--- a/nn/runtime/test/generated/vts_models/logistic_float_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/logistic_float_1.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/logistic_float_1_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/logistic_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..5304eb0
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/logistic_float_1_relaxed.model.cpp
@@ -0,0 +1,53 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::LOGISTIC,
+            .inputs = {0},
+            .outputs = {1},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {1};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/logistic_float_2.model.cpp b/nn/runtime/test/generated/vts_models/logistic_float_2.model.cpp
index 9fffa7d..6f0f24a 100644
--- a/nn/runtime/test/generated/vts_models/logistic_float_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/logistic_float_2.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/logistic_float_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/logistic_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..a594f4b
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/logistic_float_2_relaxed.model.cpp
@@ -0,0 +1,53 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 32, 40, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 32, 40, 2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::LOGISTIC,
+            .inputs = {0},
+            .outputs = {1},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {1};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/logistic_quant8_1.model.cpp b/nn/runtime/test/generated/vts_models/logistic_quant8_1.model.cpp
index 2623a97..abd1b18 100644
--- a/nn/runtime/test/generated/vts_models/logistic_quant8_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/logistic_quant8_1.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/logistic_quant8_2.model.cpp b/nn/runtime/test/generated/vts_models/logistic_quant8_2.model.cpp
index 1cd2204..cb5d980 100644
--- a/nn/runtime/test/generated/vts_models/logistic_quant8_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/logistic_quant8_2.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/lsh_projection.model.cpp b/nn/runtime/test/generated/vts_models/lsh_projection.model.cpp
index f2fcfb4..cc784f0 100644
--- a/nn/runtime/test/generated/vts_models/lsh_projection.model.cpp
+++ b/nn/runtime/test/generated/vts_models/lsh_projection.model.cpp
@@ -74,6 +74,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/lsh_projection_2.model.cpp b/nn/runtime/test/generated/vts_models/lsh_projection_2.model.cpp
index 1aa040a..3dcc1a6 100644
--- a/nn/runtime/test/generated/vts_models/lsh_projection_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/lsh_projection_2.model.cpp
@@ -74,6 +74,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/lsh_projection_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/lsh_projection_2_relaxed.model.cpp
new file mode 100644
index 0000000..45088db
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/lsh_projection_2_relaxed.model.cpp
@@ -0,0 +1,82 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 32},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {3, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 32, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::LSH_PROJECTION,
+            .inputs = {0, 1, 2, 3},
+            .outputs = {4},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {1, 2};
+    const std::vector<uint32_t> outputIndexes = {4};
+    std::vector<uint8_t> operandValues = {
+      109, 231, 251, 61, 213, 120, 233, 62, 29, 90, 164, 190, 139, 108, 39, 191, 182, 243, 157, 63, 45, 178, 181, 64, 162, 69, 138, 192, 113, 61, 12, 193, 1, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/lsh_projection_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/lsh_projection_relaxed.model.cpp
new file mode 100644
index 0000000..b7e4389
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/lsh_projection_relaxed.model.cpp
@@ -0,0 +1,82 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 32},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {3, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 32, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {8},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::LSH_PROJECTION,
+            .inputs = {0, 1, 2, 3},
+            .outputs = {4},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {1, 2};
+    const std::vector<uint32_t> outputIndexes = {4};
+    std::vector<uint8_t> operandValues = {
+      109, 231, 251, 61, 213, 120, 233, 62, 29, 90, 164, 190, 139, 108, 39, 191, 182, 243, 157, 63, 45, 178, 181, 64, 162, 69, 138, 192, 113, 61, 12, 193, 2, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/lsh_projection_weights_as_inputs.model.cpp b/nn/runtime/test/generated/vts_models/lsh_projection_weights_as_inputs.model.cpp
index b088432..15e76ba 100644
--- a/nn/runtime/test/generated/vts_models/lsh_projection_weights_as_inputs.model.cpp
+++ b/nn/runtime/test/generated/vts_models/lsh_projection_weights_as_inputs.model.cpp
@@ -72,6 +72,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/lsh_projection_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/lsh_projection_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 0000000..d4110fa
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/lsh_projection_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,80 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {3, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {8},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::LSH_PROJECTION,
+            .inputs = {0, 1, 2, 3},
+            .outputs = {4},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2, 3};
+    const std::vector<uint32_t> outputIndexes = {4};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/lstm.model.cpp b/nn/runtime/test/generated/vts_models/lstm.model.cpp
index 65a5fd4..207f298 100644
--- a/nn/runtime/test/generated/vts_models/lstm.model.cpp
+++ b/nn/runtime/test/generated/vts_models/lstm.model.cpp
@@ -270,6 +270,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {0};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/lstm2.model.cpp b/nn/runtime/test/generated/vts_models/lstm2.model.cpp
index 3769d91..9ea0aae 100644
--- a/nn/runtime/test/generated/vts_models/lstm2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/lstm2.model.cpp
@@ -270,6 +270,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {0};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/lstm2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/lstm2_relaxed.model.cpp
new file mode 100644
index 0000000..04fdc00
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/lstm2_relaxed.model.cpp
@@ -0,0 +1,278 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0,0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 12},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::LSTM,
+            .inputs = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22},
+            .outputs = {23, 24, 25, 26},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22};
+    const std::vector<uint32_t> outputIndexes = {23, 24, 25, 26};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/lstm2_state.model.cpp b/nn/runtime/test/generated/vts_models/lstm2_state.model.cpp
index 3769d91..9ea0aae 100644
--- a/nn/runtime/test/generated/vts_models/lstm2_state.model.cpp
+++ b/nn/runtime/test/generated/vts_models/lstm2_state.model.cpp
@@ -270,6 +270,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {0};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/lstm2_state2.model.cpp b/nn/runtime/test/generated/vts_models/lstm2_state2.model.cpp
index 95fc7ca..80f4b04 100644
--- a/nn/runtime/test/generated/vts_models/lstm2_state2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/lstm2_state2.model.cpp
@@ -270,6 +270,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {1, 2, 0};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/lstm2_state2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/lstm2_state2_relaxed.model.cpp
new file mode 100644
index 0000000..5428fc8
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/lstm2_state2_relaxed.model.cpp
@@ -0,0 +1,278 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0,0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 12},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::LSTM,
+            .inputs = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22},
+            .outputs = {23, 24, 25, 26},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22};
+    const std::vector<uint32_t> outputIndexes = {23, 24, 25, 26};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {1, 2, 0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/lstm2_state_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/lstm2_state_relaxed.model.cpp
new file mode 100644
index 0000000..04fdc00
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/lstm2_state_relaxed.model.cpp
@@ -0,0 +1,278 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0,0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 12},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::LSTM,
+            .inputs = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22},
+            .outputs = {23, 24, 25, 26},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22};
+    const std::vector<uint32_t> outputIndexes = {23, 24, 25, 26};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/lstm3.model.cpp b/nn/runtime/test/generated/vts_models/lstm3.model.cpp
index e1c0d7b..6438e10 100644
--- a/nn/runtime/test/generated/vts_models/lstm3.model.cpp
+++ b/nn/runtime/test/generated/vts_models/lstm3.model.cpp
@@ -270,6 +270,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {0};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/lstm3_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/lstm3_relaxed.model.cpp
new file mode 100644
index 0000000..25e626b
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/lstm3_relaxed.model.cpp
@@ -0,0 +1,278 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {16,20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 80},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 16},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 20},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 16},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::LSTM,
+            .inputs = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22},
+            .outputs = {23, 24, 25, 26},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22};
+    const std::vector<uint32_t> outputIndexes = {23, 24, 25, 26};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/lstm3_state.model.cpp b/nn/runtime/test/generated/vts_models/lstm3_state.model.cpp
index e1c0d7b..6438e10 100644
--- a/nn/runtime/test/generated/vts_models/lstm3_state.model.cpp
+++ b/nn/runtime/test/generated/vts_models/lstm3_state.model.cpp
@@ -270,6 +270,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {0};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/lstm3_state2.model.cpp b/nn/runtime/test/generated/vts_models/lstm3_state2.model.cpp
index e1c0d7b..6438e10 100644
--- a/nn/runtime/test/generated/vts_models/lstm3_state2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/lstm3_state2.model.cpp
@@ -270,6 +270,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {0};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/lstm3_state2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/lstm3_state2_relaxed.model.cpp
new file mode 100644
index 0000000..25e626b
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/lstm3_state2_relaxed.model.cpp
@@ -0,0 +1,278 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {16,20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 80},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 16},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 20},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 16},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::LSTM,
+            .inputs = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22},
+            .outputs = {23, 24, 25, 26},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22};
+    const std::vector<uint32_t> outputIndexes = {23, 24, 25, 26};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/lstm3_state3.model.cpp b/nn/runtime/test/generated/vts_models/lstm3_state3.model.cpp
index 565772f..646d48b 100644
--- a/nn/runtime/test/generated/vts_models/lstm3_state3.model.cpp
+++ b/nn/runtime/test/generated/vts_models/lstm3_state3.model.cpp
@@ -270,6 +270,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {1, 2, 0};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/lstm3_state3_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/lstm3_state3_relaxed.model.cpp
new file mode 100644
index 0000000..eee4e36
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/lstm3_state3_relaxed.model.cpp
@@ -0,0 +1,278 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {16,20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 80},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 16},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 20},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 16},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::LSTM,
+            .inputs = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22},
+            .outputs = {23, 24, 25, 26},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22};
+    const std::vector<uint32_t> outputIndexes = {23, 24, 25, 26};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {1, 2, 0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/lstm3_state_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/lstm3_state_relaxed.model.cpp
new file mode 100644
index 0000000..25e626b
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/lstm3_state_relaxed.model.cpp
@@ -0,0 +1,278 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {16,20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 20},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 80},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 16},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 20},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 16},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::LSTM,
+            .inputs = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22},
+            .outputs = {23, 24, 25, 26},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22};
+    const std::vector<uint32_t> outputIndexes = {23, 24, 25, 26};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/lstm_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/lstm_relaxed.model.cpp
new file mode 100644
index 0000000..e56e1c2
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/lstm_relaxed.model.cpp
@@ -0,0 +1,278 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0,0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 16},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::LSTM,
+            .inputs = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22},
+            .outputs = {23, 24, 25, 26},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22};
+    const std::vector<uint32_t> outputIndexes = {23, 24, 25, 26};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/lstm_state.model.cpp b/nn/runtime/test/generated/vts_models/lstm_state.model.cpp
index 65a5fd4..207f298 100644
--- a/nn/runtime/test/generated/vts_models/lstm_state.model.cpp
+++ b/nn/runtime/test/generated/vts_models/lstm_state.model.cpp
@@ -270,6 +270,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {0};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/lstm_state2.model.cpp b/nn/runtime/test/generated/vts_models/lstm_state2.model.cpp
index 33d890b..aab981c 100644
--- a/nn/runtime/test/generated/vts_models/lstm_state2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/lstm_state2.model.cpp
@@ -270,6 +270,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {1, 2, 0};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/lstm_state2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/lstm_state2_relaxed.model.cpp
new file mode 100644
index 0000000..ca650ac
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/lstm_state2_relaxed.model.cpp
@@ -0,0 +1,278 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0,0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 16},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::LSTM,
+            .inputs = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22},
+            .outputs = {23, 24, 25, 26},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22};
+    const std::vector<uint32_t> outputIndexes = {23, 24, 25, 26};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {1, 2, 0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/lstm_state_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/lstm_state_relaxed.model.cpp
new file mode 100644
index 0000000..e56e1c2
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/lstm_state_relaxed.model.cpp
@@ -0,0 +1,278 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0,0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {0},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 16},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::LSTM,
+            .inputs = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22},
+            .outputs = {23, 24, 25, 26},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22};
+    const std::vector<uint32_t> outputIndexes = {23, 24, 25, 26};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/max_pool_float_1.model.cpp b/nn/runtime/test/generated/vts_models/max_pool_float_1.model.cpp
index 0b1121f..072557e 100644
--- a/nn/runtime/test/generated/vts_models/max_pool_float_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/max_pool_float_1.model.cpp
@@ -74,6 +74,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/max_pool_float_1_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/max_pool_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..58d690e
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/max_pool_float_1_relaxed.model.cpp
@@ -0,0 +1,82 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::MAX_POOL_2D,
+            .inputs = {0, 2, 2, 2, 2, 1, 1, 1, 1, 3},
+            .outputs = {4},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {4};
+    std::vector<uint8_t> operandValues = {
+      1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/max_pool_float_2.model.cpp b/nn/runtime/test/generated/vts_models/max_pool_float_2.model.cpp
index 3cbd6fd..e3e13c6 100644
--- a/nn/runtime/test/generated/vts_models/max_pool_float_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/max_pool_float_2.model.cpp
@@ -83,6 +83,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/max_pool_float_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/max_pool_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..a1bd6ce
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/max_pool_float_2_relaxed.model.cpp
@@ -0,0 +1,91 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {5, 50, 70, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {5, 2, 3, 3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::MAX_POOL_2D,
+            .inputs = {0, 3, 3, 3, 3, 1, 1, 2, 2, 4},
+            .outputs = {5},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {5};
+    std::vector<uint8_t> operandValues = {
+      20, 0, 0, 0, 20, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/max_pool_float_3.model.cpp b/nn/runtime/test/generated/vts_models/max_pool_float_3.model.cpp
index f8abbe8..2704c73 100644
--- a/nn/runtime/test/generated/vts_models/max_pool_float_3.model.cpp
+++ b/nn/runtime/test/generated/vts_models/max_pool_float_3.model.cpp
@@ -83,6 +83,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/max_pool_float_3_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/max_pool_float_3_relaxed.model.cpp
new file mode 100644
index 0000000..f3cb776
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/max_pool_float_3_relaxed.model.cpp
@@ -0,0 +1,91 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {5, 50, 70, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {5, 2, 3, 3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::MAX_POOL_2D,
+            .inputs = {0, 3, 3, 3, 3, 1, 1, 2, 2, 4},
+            .outputs = {5},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {5};
+    std::vector<uint8_t> operandValues = {
+      20, 0, 0, 0, 20, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/max_pool_quant8_1.model.cpp b/nn/runtime/test/generated/vts_models/max_pool_quant8_1.model.cpp
index 56c2388..0255d6f 100644
--- a/nn/runtime/test/generated/vts_models/max_pool_quant8_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/max_pool_quant8_1.model.cpp
@@ -74,6 +74,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/max_pool_quant8_2.model.cpp b/nn/runtime/test/generated/vts_models/max_pool_quant8_2.model.cpp
index f277b34..ffdac41 100644
--- a/nn/runtime/test/generated/vts_models/max_pool_quant8_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/max_pool_quant8_2.model.cpp
@@ -83,6 +83,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/max_pool_quant8_3.model.cpp b/nn/runtime/test/generated/vts_models/max_pool_quant8_3.model.cpp
index e72b672..aad7e84 100644
--- a/nn/runtime/test/generated/vts_models/max_pool_quant8_3.model.cpp
+++ b/nn/runtime/test/generated/vts_models/max_pool_quant8_3.model.cpp
@@ -83,6 +83,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/mean.model.cpp b/nn/runtime/test/generated/vts_models/mean.model.cpp
index 89ea434..9743a70 100644
--- a/nn/runtime/test/generated/vts_models/mean.model.cpp
+++ b/nn/runtime/test/generated/vts_models/mean.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/mean_float_1.model.cpp b/nn/runtime/test/generated/vts_models/mean_float_1.model.cpp
index db44286..dfacd8d 100644
--- a/nn/runtime/test/generated/vts_models/mean_float_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/mean_float_1.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/mean_float_2.model.cpp b/nn/runtime/test/generated/vts_models/mean_float_2.model.cpp
index 50f35a3..8e92984 100644
--- a/nn/runtime/test/generated/vts_models/mean_float_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/mean_float_2.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/mobilenet_224_gender_basic_fixed.model.cpp b/nn/runtime/test/generated/vts_models/mobilenet_224_gender_basic_fixed.model.cpp
index 9d70320..83cb058 100644
--- a/nn/runtime/test/generated/vts_models/mobilenet_224_gender_basic_fixed.model.cpp
+++ b/nn/runtime/test/generated/vts_models/mobilenet_224_gender_basic_fixed.model.cpp
@@ -2136,6 +2136,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/mobilenet_224_gender_basic_fixed_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/mobilenet_224_gender_basic_fixed_relaxed.model.cpp
new file mode 100644
index 0000000..1008d2a
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/mobilenet_224_gender_basic_fixed_relaxed.model.cpp
@@ -0,0 +1,2144 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 20, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 24, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 28, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 32, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 36, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 40, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 44, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 48, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 52, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 56, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 60, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 64, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 68, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 72, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 76, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 80, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 84, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 88, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 92, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 96, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 100, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 104, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 108, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 112, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 116, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 120, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 124, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 128, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 132, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 136, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 140, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 144, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 148, .length = 4},
+        },
+        {
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+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {64},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 566604, .length = 256},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {64, 1, 1, 32},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 566860, .length = 8192},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 28, 28, 64},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {64},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 575052, .length = 256},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3, 3, 64},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 575308, .length = 2304},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 28, 28, 64},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {64},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 577612, .length = 256},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {64, 1, 1, 64},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 577868, .length = 16384},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 14, 14, 64},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {64},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 594252, .length = 256},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3, 3, 64},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 594508, .length = 2304},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 14, 14, 128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 596812, .length = 512},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {128, 1, 1, 64},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 597324, .length = 32768},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 14, 14, 128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 630092, .length = 512},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3, 3, 128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 630604, .length = 4608},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 14, 14, 128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 635212, .length = 512},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {128, 1, 1, 128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 635724, .length = 65536},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 14, 14, 128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 701260, .length = 512},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3, 3, 128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 701772, .length = 4608},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 14, 14, 128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 706380, .length = 512},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {128, 1, 1, 128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 706892, .length = 65536},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 14, 14, 128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 772428, .length = 512},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3, 3, 128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 772940, .length = 4608},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 14, 14, 128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 777548, .length = 512},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {128, 1, 1, 128},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 778060, .length = 65536},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 256},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 11},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {11},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 843596, .length = 44},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {11, 1, 1, 256},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 843640, .length = 11264},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {131, 135, 134, 0, 1, 2, 3},
+            .outputs = {133},
+        },
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {133, 162, 161, 4, 5, 6, 7, 8},
+            .outputs = {160},
+        },
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {160, 165, 164, 9, 10, 11, 12},
+            .outputs = {163},
+        },
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {163, 168, 167, 13, 14, 15, 16, 17},
+            .outputs = {166},
+        },
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {166, 171, 170, 18, 19, 20, 21},
+            .outputs = {169},
+        },
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {169, 174, 173, 22, 23, 24, 25, 26},
+            .outputs = {172},
+        },
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {172, 177, 176, 27, 28, 29, 30},
+            .outputs = {175},
+        },
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {175, 180, 179, 31, 32, 33, 34, 35},
+            .outputs = {178},
+        },
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {178, 183, 182, 36, 37, 38, 39},
+            .outputs = {181},
+        },
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {181, 186, 185, 40, 41, 42, 43, 44},
+            .outputs = {184},
+        },
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {184, 189, 188, 45, 46, 47, 48},
+            .outputs = {187},
+        },
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {187, 192, 191, 49, 50, 51, 52, 53},
+            .outputs = {190},
+        },
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {190, 195, 194, 54, 55, 56, 57},
+            .outputs = {193},
+        },
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {193, 198, 197, 58, 59, 60, 61, 62},
+            .outputs = {196},
+        },
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {196, 201, 200, 63, 64, 65, 66},
+            .outputs = {199},
+        },
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {199, 204, 203, 67, 68, 69, 70, 71},
+            .outputs = {202},
+        },
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {202, 207, 206, 72, 73, 74, 75},
+            .outputs = {205},
+        },
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {205, 210, 209, 76, 77, 78, 79, 80},
+            .outputs = {208},
+        },
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {208, 213, 212, 81, 82, 83, 84},
+            .outputs = {211},
+        },
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {211, 138, 137, 85, 86, 87, 88, 89},
+            .outputs = {136},
+        },
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {136, 141, 140, 90, 91, 92, 93},
+            .outputs = {139},
+        },
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {139, 144, 143, 94, 95, 96, 97, 98},
+            .outputs = {142},
+        },
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {142, 147, 146, 99, 100, 101, 102},
+            .outputs = {145},
+        },
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {145, 150, 149, 103, 104, 105, 106, 107},
+            .outputs = {148},
+        },
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {148, 153, 152, 108, 109, 110, 111},
+            .outputs = {151},
+        },
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {151, 156, 155, 112, 113, 114, 115, 116},
+            .outputs = {154},
+        },
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {154, 159, 158, 117, 118, 119, 120},
+            .outputs = {157},
+        },
+        {
+            .type = OperationType::AVERAGE_POOL_2D,
+            .inputs = {157, 121, 122, 123, 124, 125, 126},
+            .outputs = {214},
+        },
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {214, 217, 216, 127, 128, 129, 130},
+            .outputs = {215},
+        },
+        {
+            .type = OperationType::LOGISTIC,
+            .inputs = {215},
+            .outputs = {132},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {131};
+    const std::vector<uint32_t> outputIndexes = {132};
+    std::vector<uint8_t> operandValues = {
+      1, 0, 0, 0, 2, 0, 0, 0, 2, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 2, 0, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 2, 0, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 2, 0, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 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142, 203, 176, 62, 31, 16, 40, 62, 163, 224, 45, 187, 123, 255, 149, 189, 105, 55, 178, 62, 98, 102, 127, 190, 72, 153, 62, 61, 104, 12, 142, 61, 213, 173, 163, 61, 2, 51, 1, 57, 234, 3, 57, 62, 117, 247, 186, 61, 118, 169, 153, 190, 214, 172, 147, 190, 253, 188, 25, 62, 253, 74, 231, 61, 51, 168, 214, 61, 35, 176, 99, 189, 94, 252, 6, 187, 47, 190, 205, 188, 188, 111, 161, 189, 4, 114, 137, 188, 3, 233, 226, 189, 18, 21, 170, 189, 241, 214, 89, 190, 47, 191, 147, 62, 95, 240, 233, 189, 61, 40, 232, 189, 88, 229, 226, 61, 38, 252, 242, 61, 80, 171, 8, 62, 228, 146, 244, 188, 191, 42, 119, 190, 251, 7, 33, 62, 62, 114, 176, 61, 77, 56, 186, 189, 78, 180, 204, 58, 31, 49, 218, 61, 92, 31, 86, 190, 47, 21, 219, 189, 137, 135, 166, 60, 230, 116, 57, 190, 76, 138, 159, 190, 180, 171, 115, 187, 205, 162, 145, 61, 171, 174, 83, 190, 142, 120, 146, 62, 237, 16, 15, 62, 254, 214, 238, 61, 211, 45, 59, 62, 97, 156, 201, 60, 133, 8, 56, 190, 41, 177, 43, 61, 190, 103, 148, 61, 62, 94, 136, 62, 25, 150, 202, 61, 26, 65, 148, 61, 77, 199, 210, 60, 195, 212, 214, 61, 82, 163, 139, 61, 210, 86, 144, 189, 5, 7, 11, 59, 213, 34, 186, 190, 113, 171, 224, 60, 49, 177, 217, 189, 159, 89, 186, 190, 168, 25, 2, 62, 22, 169, 107, 189, 92, 198, 77, 190, 125, 111, 136, 189, 234, 207, 14, 190, 245, 177, 140, 188, 74, 241, 129, 62, 123, 103, 132, 190, 58, 89, 42, 190, 20, 119, 220, 189, 156, 223, 136, 62, 27, 15, 214, 61, 132, 98, 171, 188, 14, 215, 159, 189, 134, 0, 0, 62, 18, 239, 165, 60, 251, 38, 184, 189, 175, 152, 1, 190, 115, 128, 152, 190, 112, 233, 248, 61, 112, 141, 137, 189, 198, 46, 54, 189, 134, 55, 171, 62, 54, 200, 180, 61, 182, 30, 180, 189, 199, 246, 53, 187, 145, 183, 124, 189, 111, 28, 103, 61, 200, 239, 237, 189, 52, 215, 105, 190, 231, 83, 231, 61, 215, 78, 52, 62, 227, 141, 204, 61, 18, 69, 208, 187, 132, 243, 233, 189, 24, 236, 118, 62, 218, 254, 197, 61, 124, 211, 196, 189, 212, 129, 12, 62, 15, 119, 170, 189, 101, 1, 11, 191, 160, 26, 111, 190, 235, 114, 10, 189, 86, 159, 235, 189, 242, 150, 187, 190, 57, 208, 115, 190, 47, 230, 194, 189, 212, 181, 134, 62, 31, 101, 4, 62, 179, 41, 23, 190, 87, 113, 143, 61, 168, 7, 160, 60, 88, 140, 146, 190, 73, 247, 139, 190, 156, 141, 112, 61, 109, 169, 131, 190, 153, 132, 11, 190, 134, 143, 8, 190, 66, 10, 126, 190, 48, 70, 140, 62, 170, 241, 154, 190, 104, 205, 175, 189, 32, 254, 171, 189, 91, 152, 5, 190, 140, 133, 129, 62, 135, 11, 42, 189, 2, 88, 142, 189, 61, 130, 187, 189, 4, 86, 134, 190, 188, 65, 132, 189, 114, 23, 65, 62, 130, 29, 79, 190, 141, 213, 230, 189, 76, 236, 206, 59, 110, 197, 89, 60, 17, 25, 86, 188, 25, 197, 154, 190, 34, 30, 100, 61, 50, 132, 173, 188, 56, 141, 99, 189, 156, 122, 238, 60, 215, 221, 44, 62, 9, 26, 19, 62, 90, 223, 184, 187, 146, 152, 123, 189, 117, 113, 192, 189, 48, 138, 196, 61, 215, 219, 86, 190, 194, 195, 212, 189, 140, 244, 82, 190, 12, 181, 33, 189, 218, 144, 95, 61, 89, 218, 14, 189, 171, 62, 7, 190, 133, 171, 72, 189, 19, 211, 53, 190, 139, 138, 40, 190, 117, 216, 142, 188, 127, 190, 141, 190, 27, 99, 7, 190, 220, 242, 113, 190, 51, 153, 123, 189, 77, 129, 108, 190, 141, 152, 209, 190, 246, 122, 183, 189, 218, 145, 58, 62, 181, 192, 174, 190, 239, 54, 132, 189, 42, 63, 132, 188, 186, 164, 42, 190, 43, 161, 160, 189, 64, 107, 198, 190, 186, 75, 114, 62, 216, 43, 236, 189, 48, 187, 231, 189, 188, 231, 224, 189, 34, 107, 194, 189, 239, 230, 129, 190, 62, 65, 130, 190, 171, 134, 179, 189, 237, 243, 120, 190, 160, 110, 96, 190, 159, 193, 11, 61, 30, 148, 166, 60, 203, 58, 50, 61, 32, 47, 218, 188, 218, 171, 15, 62, 139, 166, 83, 190, 114, 224, 5, 190, 182, 137, 174, 60, 23, 46, 59, 62, 44, 189, 145, 189, 106, 160, 41, 190, 79, 120, 89, 190, 217, 56, 199, 189, 68, 165, 145, 190, 16, 241, 170, 189, 201, 174, 4, 190, 225, 40, 9, 190, 157, 48, 140, 61, 125, 32, 9, 190, 20, 180, 41, 62, 72, 21, 53, 190, 130, 154, 192, 189, 62, 233, 20, 190, 176, 243, 64, 189, 184, 184, 27, 60, 219, 217, 252, 60, 42, 97, 249, 187, 18, 160, 70, 190, 128, 128, 37, 190, 156, 196, 224, 61, 202, 21, 35, 189, 179, 86, 221, 58, 75, 74, 128, 61, 104, 117, 242, 189, 139, 249, 9, 190, 84, 142, 121, 190, 64, 247, 21, 62, 162, 213, 41, 190, 195, 249, 111, 61, 197, 157, 220, 60, 151, 28, 39, 62, 12, 201, 73, 190, 105, 187, 51, 61, 0, 85, 28, 190, 11, 235, 54, 190, 237, 74, 43, 190, 107, 144, 211, 60, 5, 23, 107, 190, 98, 186, 208, 189, 77, 120, 19, 61, 49, 150, 41, 190, 246, 92, 230, 189, 222, 4, 215, 190, 230, 31, 189, 190, 160, 189, 63, 61, 11, 95, 79, 62, 185, 111, 37, 62, 89, 162, 19, 61, 95, 237, 88, 190, 18, 210, 68, 61, 204, 68, 129, 190, 209, 215, 194, 189, 131, 107, 206, 61, 103, 44, 194, 190, 97, 252, 4, 190, 19, 130, 21, 189, 107, 85, 140, 61, 198, 124, 202, 60, 68, 226, 153, 189, 25, 255, 254, 189, 126, 116, 122, 62, 197, 41, 41, 188, 29, 89, 177, 190, 20, 234, 153, 190, 17, 229, 107, 62, 85, 77, 64, 190, 51, 179, 5, 189, 139, 174, 150, 61, 228, 226, 94, 188, 92, 214, 179, 188, 81, 217, 128, 61, 67, 235, 252, 188, 146, 230, 207, 189, 186, 130, 45, 190, 180, 117, 112, 61, 251, 120, 8, 190, 223, 25, 77, 190, 195, 185, 190, 190, 57, 14, 92, 190, 113, 202, 60, 190, 39, 222, 129, 62, 244, 117, 20, 189, 64, 132, 125, 61, 33, 172, 171, 61, 198, 53, 30, 189, 165, 74, 4, 62, 51, 249, 22, 190, 255, 37, 57, 190, 127, 83, 163, 189, 229, 181, 146, 190, 80, 199, 139, 190, 205, 5, 238, 61, 201, 176, 130, 190, 167, 179, 78, 189, 233, 84, 104, 189, 227, 46, 167, 188, 111, 72, 83, 62, 33, 172, 102, 190, 182, 190, 88, 190, 246, 183, 132, 190, 89, 153, 138, 189, 116, 97, 52, 190, 164, 84, 146, 62, 123, 157, 183, 187, 61, 6, 208, 188, 251, 234, 58, 190, 154, 96, 176, 190, 204, 183, 174, 190, 12, 1, 48, 190, 170, 125, 122, 62, 88, 143, 123, 60, 199, 141, 209, 188, 40, 39, 175, 189, 172, 31, 27, 190, 68, 3, 7, 189, 119, 163, 159, 62, 236, 62, 182, 61, 39, 20, 18, 190, 154, 151, 162, 186, 204, 131, 143, 60, 146, 73, 60, 61, 114, 25, 143, 62, 200, 36, 115, 190, 221, 125, 105, 61, 80, 255, 217, 187, 54, 228, 100, 189, 232, 199, 149, 61, 138, 168, 238, 60, 169, 9, 188, 61, 173, 156, 226, 60, 113, 88, 10, 190, 246, 153, 155, 190, 102, 26, 232, 60, 150, 93, 80, 190, 100, 16, 174, 189, 5, 168, 145, 190, 216, 16, 92, 190, 210, 87, 171, 61, 0, 3, 97, 190, 190, 108, 11, 62, 6, 42, 8, 61, 140, 190, 18, 190, 64, 10, 232, 60, 235, 253, 54, 190, 43, 18, 152, 189, 165, 217, 28, 190, 89, 23, 183, 60, 127, 87, 154, 189, 251, 36, 87, 190, 186, 139, 187, 189, 175, 109, 155, 188, 164, 198, 116, 190, 238, 152, 10, 190, 194, 50, 214, 189, 219, 215, 134, 189, 91, 154, 59, 190, 146, 234, 251, 189, 68, 41, 171, 61, 233, 251, 143, 189, 168, 112, 84, 190, 163, 90, 140, 190, 31, 188, 102, 190, 211, 106, 232, 189, 24, 91, 8, 62, 135, 233, 241, 60, 134, 65, 196, 189
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/mobilenet_quantized.model.cpp b/nn/runtime/test/generated/vts_models/mobilenet_quantized.model.cpp
index 1dbcbc7..220da49 100644
--- a/nn/runtime/test/generated/vts_models/mobilenet_quantized.model.cpp
+++ b/nn/runtime/test/generated/vts_models/mobilenet_quantized.model.cpp
@@ -2192,6 +2192,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/mul.model.cpp b/nn/runtime/test/generated/vts_models/mul.model.cpp
index 3dcc99a..1665ea1 100644
--- a/nn/runtime/test/generated/vts_models/mul.model.cpp
+++ b/nn/runtime/test/generated/vts_models/mul.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/mul_broadcast_quant8.model.cpp b/nn/runtime/test/generated/vts_models/mul_broadcast_quant8.model.cpp
index 2cb91a1..c851905 100644
--- a/nn/runtime/test/generated/vts_models/mul_broadcast_quant8.model.cpp
+++ b/nn/runtime/test/generated/vts_models/mul_broadcast_quant8.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/mul_quant8.model.cpp b/nn/runtime/test/generated/vts_models/mul_quant8.model.cpp
index d975cf7..0e09d79 100644
--- a/nn/runtime/test/generated/vts_models/mul_quant8.model.cpp
+++ b/nn/runtime/test/generated/vts_models/mul_quant8.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/mul_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/mul_relaxed.model.cpp
new file mode 100644
index 0000000..fef4bdf
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/mul_relaxed.model.cpp
@@ -0,0 +1,73 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::MUL,
+            .inputs = {0, 1, 2},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/mul_relu.model.cpp b/nn/runtime/test/generated/vts_models/mul_relu.model.cpp
index e4ccda8..7dc0324 100644
--- a/nn/runtime/test/generated/vts_models/mul_relu.model.cpp
+++ b/nn/runtime/test/generated/vts_models/mul_relu.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/mul_relu_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/mul_relu_relaxed.model.cpp
new file mode 100644
index 0000000..a0166e6
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/mul_relu_relaxed.model.cpp
@@ -0,0 +1,73 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::MUL,
+            .inputs = {0, 1, 2},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      1, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/pad.model.cpp b/nn/runtime/test/generated/vts_models/pad.model.cpp
index dd85157..d82d406 100644
--- a/nn/runtime/test/generated/vts_models/pad.model.cpp
+++ b/nn/runtime/test/generated/vts_models/pad.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/pad_float_1.model.cpp b/nn/runtime/test/generated/vts_models/pad_float_1.model.cpp
index 0434f11..9cc5341 100644
--- a/nn/runtime/test/generated/vts_models/pad_float_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/pad_float_1.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/relu1_float_1.model.cpp b/nn/runtime/test/generated/vts_models/relu1_float_1.model.cpp
index 7137c73..9ae04c4 100644
--- a/nn/runtime/test/generated/vts_models/relu1_float_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/relu1_float_1.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/relu1_float_1_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/relu1_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..4397f70
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/relu1_float_1_relaxed.model.cpp
@@ -0,0 +1,53 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::RELU1,
+            .inputs = {0},
+            .outputs = {1},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {1};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/relu1_float_2.model.cpp b/nn/runtime/test/generated/vts_models/relu1_float_2.model.cpp
index ba63c96..9fe9f4b 100644
--- a/nn/runtime/test/generated/vts_models/relu1_float_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/relu1_float_2.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/relu1_float_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/relu1_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..5f94f4b
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/relu1_float_2_relaxed.model.cpp
@@ -0,0 +1,53 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 30, 24, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 30, 24, 2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::RELU1,
+            .inputs = {0},
+            .outputs = {1},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {1};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/relu1_quant8_1.model.cpp b/nn/runtime/test/generated/vts_models/relu1_quant8_1.model.cpp
index 73da28d..5679c16 100644
--- a/nn/runtime/test/generated/vts_models/relu1_quant8_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/relu1_quant8_1.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/relu1_quant8_2.model.cpp b/nn/runtime/test/generated/vts_models/relu1_quant8_2.model.cpp
index f0dcde2..df83727 100644
--- a/nn/runtime/test/generated/vts_models/relu1_quant8_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/relu1_quant8_2.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/relu6_float_1.model.cpp b/nn/runtime/test/generated/vts_models/relu6_float_1.model.cpp
index aecdd91..9866f06 100644
--- a/nn/runtime/test/generated/vts_models/relu6_float_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/relu6_float_1.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/relu6_float_1_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/relu6_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..68c8e50
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/relu6_float_1_relaxed.model.cpp
@@ -0,0 +1,53 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::RELU6,
+            .inputs = {0},
+            .outputs = {1},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {1};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/relu6_float_2.model.cpp b/nn/runtime/test/generated/vts_models/relu6_float_2.model.cpp
index 400f417..e512fc5 100644
--- a/nn/runtime/test/generated/vts_models/relu6_float_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/relu6_float_2.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/relu6_float_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/relu6_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..2c41464
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/relu6_float_2_relaxed.model.cpp
@@ -0,0 +1,53 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 26, 40, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 26, 40, 2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::RELU6,
+            .inputs = {0},
+            .outputs = {1},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {1};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/relu6_quant8_1.model.cpp b/nn/runtime/test/generated/vts_models/relu6_quant8_1.model.cpp
index 577a701..46e32e5 100644
--- a/nn/runtime/test/generated/vts_models/relu6_quant8_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/relu6_quant8_1.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/relu6_quant8_2.model.cpp b/nn/runtime/test/generated/vts_models/relu6_quant8_2.model.cpp
index 8c6f4d3..c87422f 100644
--- a/nn/runtime/test/generated/vts_models/relu6_quant8_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/relu6_quant8_2.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/relu_float_1.model.cpp b/nn/runtime/test/generated/vts_models/relu_float_1.model.cpp
index 8a6086c..a232e74 100644
--- a/nn/runtime/test/generated/vts_models/relu_float_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/relu_float_1.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/relu_float_1_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/relu_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..dcef5d7
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/relu_float_1_relaxed.model.cpp
@@ -0,0 +1,53 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::RELU,
+            .inputs = {0},
+            .outputs = {1},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {1};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/relu_float_2.model.cpp b/nn/runtime/test/generated/vts_models/relu_float_2.model.cpp
index 84afe00..e4f981b 100644
--- a/nn/runtime/test/generated/vts_models/relu_float_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/relu_float_2.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/relu_quant8_1.model.cpp b/nn/runtime/test/generated/vts_models/relu_quant8_1.model.cpp
index eecd936..4e0f7cf 100644
--- a/nn/runtime/test/generated/vts_models/relu_quant8_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/relu_quant8_1.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/relu_quant8_2.model.cpp b/nn/runtime/test/generated/vts_models/relu_quant8_2.model.cpp
index dda52da..6553c50 100644
--- a/nn/runtime/test/generated/vts_models/relu_quant8_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/relu_quant8_2.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/reshape.model.cpp b/nn/runtime/test/generated/vts_models/reshape.model.cpp
index 0a5e578..2e7209e 100644
--- a/nn/runtime/test/generated/vts_models/reshape.model.cpp
+++ b/nn/runtime/test/generated/vts_models/reshape.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/reshape_quant8.model.cpp b/nn/runtime/test/generated/vts_models/reshape_quant8.model.cpp
index 9ee7363..dc756ed 100644
--- a/nn/runtime/test/generated/vts_models/reshape_quant8.model.cpp
+++ b/nn/runtime/test/generated/vts_models/reshape_quant8.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/reshape_quant8_weights_as_inputs.model.cpp b/nn/runtime/test/generated/vts_models/reshape_quant8_weights_as_inputs.model.cpp
index 8a44723..4063235 100644
--- a/nn/runtime/test/generated/vts_models/reshape_quant8_weights_as_inputs.model.cpp
+++ b/nn/runtime/test/generated/vts_models/reshape_quant8_weights_as_inputs.model.cpp
@@ -54,6 +54,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/reshape_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/reshape_relaxed.model.cpp
new file mode 100644
index 0000000..9011e48
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/reshape_relaxed.model.cpp
@@ -0,0 +1,64 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 3, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {9},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::RESHAPE,
+            .inputs = {0, 1},
+            .outputs = {2},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {2};
+    std::vector<uint8_t> operandValues = {
+      255, 255, 255, 255
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/reshape_weights_as_inputs.model.cpp b/nn/runtime/test/generated/vts_models/reshape_weights_as_inputs.model.cpp
index 7a3296e..66950b0 100644
--- a/nn/runtime/test/generated/vts_models/reshape_weights_as_inputs.model.cpp
+++ b/nn/runtime/test/generated/vts_models/reshape_weights_as_inputs.model.cpp
@@ -54,6 +54,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/reshape_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/reshape_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 0000000..b01f68e
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/reshape_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,62 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 3, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {9},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::RESHAPE,
+            .inputs = {0, 1},
+            .outputs = {2},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1};
+    const std::vector<uint32_t> outputIndexes = {2};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/resize_bilinear.model.cpp b/nn/runtime/test/generated/vts_models/resize_bilinear.model.cpp
index 31f5b03..82b0bfe 100644
--- a/nn/runtime/test/generated/vts_models/resize_bilinear.model.cpp
+++ b/nn/runtime/test/generated/vts_models/resize_bilinear.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/resize_bilinear_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/resize_bilinear_relaxed.model.cpp
new file mode 100644
index 0000000..be88c27
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/resize_bilinear_relaxed.model.cpp
@@ -0,0 +1,73 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3, 3, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::RESIZE_BILINEAR,
+            .inputs = {0, 2, 3},
+            .outputs = {1},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {1};
+    std::vector<uint8_t> operandValues = {
+      3, 0, 0, 0, 3, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/rnn.model.cpp b/nn/runtime/test/generated/vts_models/rnn.model.cpp
index b5f1c9b..a8d8689 100644
--- a/nn/runtime/test/generated/vts_models/rnn.model.cpp
+++ b/nn/runtime/test/generated/vts_models/rnn.model.cpp
@@ -99,6 +99,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {0};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/rnn_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/rnn_relaxed.model.cpp
new file mode 100644
index 0000000..f179b19
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/rnn_relaxed.model.cpp
@@ -0,0 +1,107 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 8},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {16, 8},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {16, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 16},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 16},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::RNN,
+            .inputs = {0, 1, 2, 3, 4, 5},
+            .outputs = {6, 7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2, 3, 4, 5};
+    const std::vector<uint32_t> outputIndexes = {6, 7};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/rnn_state.model.cpp b/nn/runtime/test/generated/vts_models/rnn_state.model.cpp
index b5f1c9b..a8d8689 100644
--- a/nn/runtime/test/generated/vts_models/rnn_state.model.cpp
+++ b/nn/runtime/test/generated/vts_models/rnn_state.model.cpp
@@ -99,6 +99,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {0};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/rnn_state_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/rnn_state_relaxed.model.cpp
new file mode 100644
index 0000000..f179b19
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/rnn_state_relaxed.model.cpp
@@ -0,0 +1,107 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 8},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {16, 8},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {16, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 16},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 16},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::RNN,
+            .inputs = {0, 1, 2, 3, 4, 5},
+            .outputs = {6, 7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2, 3, 4, 5};
+    const std::vector<uint32_t> outputIndexes = {6, 7};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/softmax_float_1.model.cpp b/nn/runtime/test/generated/vts_models/softmax_float_1.model.cpp
index ed2fbb0..80cad58 100644
--- a/nn/runtime/test/generated/vts_models/softmax_float_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/softmax_float_1.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/softmax_float_1_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/softmax_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..38cebbb
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/softmax_float_1_relaxed.model.cpp
@@ -0,0 +1,64 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::FLOAT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::SOFTMAX,
+            .inputs = {0, 1},
+            .outputs = {2},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {2};
+    std::vector<uint8_t> operandValues = {
+      189, 55, 134, 53
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/softmax_float_2.model.cpp b/nn/runtime/test/generated/vts_models/softmax_float_2.model.cpp
index 8a20985..2cb4e60 100644
--- a/nn/runtime/test/generated/vts_models/softmax_float_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/softmax_float_2.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/softmax_float_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/softmax_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..cd7848b
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/softmax_float_2_relaxed.model.cpp
@@ -0,0 +1,64 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::FLOAT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 5},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::SOFTMAX,
+            .inputs = {0, 1},
+            .outputs = {2},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {2};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 128, 63
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/softmax_quant8_1.model.cpp b/nn/runtime/test/generated/vts_models/softmax_quant8_1.model.cpp
index ebe1eb9..bd48e04 100644
--- a/nn/runtime/test/generated/vts_models/softmax_quant8_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/softmax_quant8_1.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/softmax_quant8_2.model.cpp b/nn/runtime/test/generated/vts_models/softmax_quant8_2.model.cpp
index 7a6d1e0..ef7b407 100644
--- a/nn/runtime/test/generated/vts_models/softmax_quant8_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/softmax_quant8_2.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/space_to_batch.model.cpp b/nn/runtime/test/generated/vts_models/space_to_batch.model.cpp
index cb4bf5a..c526b3f 100644
--- a/nn/runtime/test/generated/vts_models/space_to_batch.model.cpp
+++ b/nn/runtime/test/generated/vts_models/space_to_batch.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/space_to_batch_float_1.model.cpp b/nn/runtime/test/generated/vts_models/space_to_batch_float_1.model.cpp
index 350e113..9563ccf 100644
--- a/nn/runtime/test/generated/vts_models/space_to_batch_float_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/space_to_batch_float_1.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/space_to_batch_float_2.model.cpp b/nn/runtime/test/generated/vts_models/space_to_batch_float_2.model.cpp
index 4fbaab5..6871169 100644
--- a/nn/runtime/test/generated/vts_models/space_to_batch_float_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/space_to_batch_float_2.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/space_to_batch_float_3.model.cpp b/nn/runtime/test/generated/vts_models/space_to_batch_float_3.model.cpp
index 1b823a2..9ba87ea 100644
--- a/nn/runtime/test/generated/vts_models/space_to_batch_float_3.model.cpp
+++ b/nn/runtime/test/generated/vts_models/space_to_batch_float_3.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/space_to_batch_quant8_1.model.cpp b/nn/runtime/test/generated/vts_models/space_to_batch_quant8_1.model.cpp
index 9da8789..1700e1f 100644
--- a/nn/runtime/test/generated/vts_models/space_to_batch_quant8_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/space_to_batch_quant8_1.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/space_to_batch_quant8_2.model.cpp b/nn/runtime/test/generated/vts_models/space_to_batch_quant8_2.model.cpp
index 7dd74ae..ffc2d78 100644
--- a/nn/runtime/test/generated/vts_models/space_to_batch_quant8_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/space_to_batch_quant8_2.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/space_to_batch_quant8_3.model.cpp b/nn/runtime/test/generated/vts_models/space_to_batch_quant8_3.model.cpp
index 93aff19..ffb926e 100644
--- a/nn/runtime/test/generated/vts_models/space_to_batch_quant8_3.model.cpp
+++ b/nn/runtime/test/generated/vts_models/space_to_batch_quant8_3.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/space_to_depth_float_1.model.cpp b/nn/runtime/test/generated/vts_models/space_to_depth_float_1.model.cpp
index e1dc1e8..1bc5687 100644
--- a/nn/runtime/test/generated/vts_models/space_to_depth_float_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/space_to_depth_float_1.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/space_to_depth_float_1_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/space_to_depth_float_1_relaxed.model.cpp
new file mode 100644
index 0000000..c205f96
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/space_to_depth_float_1_relaxed.model.cpp
@@ -0,0 +1,64 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 8},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::SPACE_TO_DEPTH,
+            .inputs = {0, 1},
+            .outputs = {2},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {2};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/space_to_depth_float_2.model.cpp b/nn/runtime/test/generated/vts_models/space_to_depth_float_2.model.cpp
index 75ade17..7a6d6bf 100644
--- a/nn/runtime/test/generated/vts_models/space_to_depth_float_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/space_to_depth_float_2.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/space_to_depth_float_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/space_to_depth_float_2_relaxed.model.cpp
new file mode 100644
index 0000000..560dcde
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/space_to_depth_float_2_relaxed.model.cpp
@@ -0,0 +1,64 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4, 4, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::SPACE_TO_DEPTH,
+            .inputs = {0, 1},
+            .outputs = {2},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {2};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/space_to_depth_float_3.model.cpp b/nn/runtime/test/generated/vts_models/space_to_depth_float_3.model.cpp
index 9f3a83e..4deeccf 100644
--- a/nn/runtime/test/generated/vts_models/space_to_depth_float_3.model.cpp
+++ b/nn/runtime/test/generated/vts_models/space_to_depth_float_3.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/space_to_depth_float_3_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/space_to_depth_float_3_relaxed.model.cpp
new file mode 100644
index 0000000..d2ff0c0
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/space_to_depth_float_3_relaxed.model.cpp
@@ -0,0 +1,64 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4, 4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 8},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::SPACE_TO_DEPTH,
+            .inputs = {0, 1},
+            .outputs = {2},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {2};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/space_to_depth_quant8_1.model.cpp b/nn/runtime/test/generated/vts_models/space_to_depth_quant8_1.model.cpp
index f1c1f9a..fa141a0 100644
--- a/nn/runtime/test/generated/vts_models/space_to_depth_quant8_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/space_to_depth_quant8_1.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/space_to_depth_quant8_2.model.cpp b/nn/runtime/test/generated/vts_models/space_to_depth_quant8_2.model.cpp
index 1d7dc58..aebda00 100644
--- a/nn/runtime/test/generated/vts_models/space_to_depth_quant8_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/space_to_depth_quant8_2.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/squeeze.model.cpp b/nn/runtime/test/generated/vts_models/squeeze.model.cpp
index 41528a1..bb14c56 100644
--- a/nn/runtime/test/generated/vts_models/squeeze.model.cpp
+++ b/nn/runtime/test/generated/vts_models/squeeze.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/squeeze_float_1.model.cpp b/nn/runtime/test/generated/vts_models/squeeze_float_1.model.cpp
index da86602..28cd790 100644
--- a/nn/runtime/test/generated/vts_models/squeeze_float_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/squeeze_float_1.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/squeeze_quant8_1.model.cpp b/nn/runtime/test/generated/vts_models/squeeze_quant8_1.model.cpp
index 279fdbc..75aa1ee 100644
--- a/nn/runtime/test/generated/vts_models/squeeze_quant8_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/squeeze_quant8_1.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice.model.cpp
index 26a1f65..04e1c5b 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_1.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_1.model.cpp
index a98cdc8..c20ebb4 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_float_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_1.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_10.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_10.model.cpp
index 17ca04d..80f0706 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_float_10.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_10.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_2.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_2.model.cpp
index 2163cb8..1de6ef4 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_float_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_2.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_3.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_3.model.cpp
index c15156a..0ef0bc8 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_float_3.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_3.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_4.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_4.model.cpp
index ed2a1b4..18dc789 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_float_4.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_4.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_5.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_5.model.cpp
index 9873059..11c20e3 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_float_5.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_5.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_6.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_6.model.cpp
index f689320..da5f356 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_float_6.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_6.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_7.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_7.model.cpp
index facc785..b46d569 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_float_7.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_7.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_8.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_8.model.cpp
index 859f832..4d4a9d9 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_float_8.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_8.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_9.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_9.model.cpp
index 8ae37a8..412c9c4 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_float_9.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_9.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_qaunt8_10.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_qaunt8_10.model.cpp
index 307135d..397a61f 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_qaunt8_10.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_qaunt8_10.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_quant8_1.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_quant8_1.model.cpp
index 19dcaac..4a9cb38 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_quant8_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_quant8_1.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_quant8_2.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_quant8_2.model.cpp
index d4801fe..88661a2 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_quant8_2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_quant8_2.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_quant8_3.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_quant8_3.model.cpp
index 0e115eb..ce82b6e 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_quant8_3.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_quant8_3.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_quant8_4.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_quant8_4.model.cpp
index 472bfef..8473f53 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_quant8_4.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_quant8_4.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_quant8_5.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_quant8_5.model.cpp
index 721f1e3..381e616 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_quant8_5.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_quant8_5.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_quant8_6.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_quant8_6.model.cpp
index 4f8459b..4d9e84e 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_quant8_6.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_quant8_6.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_quant8_7.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_quant8_7.model.cpp
index f2f1a46..f756c01 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_quant8_7.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_quant8_7.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_quant8_8.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_quant8_8.model.cpp
index f951909..8814580 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_quant8_8.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_quant8_8.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_quant8_9.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_quant8_9.model.cpp
index c50d405..bd5be93 100644
--- a/nn/runtime/test/generated/vts_models/strided_slice_quant8_9.model.cpp
+++ b/nn/runtime/test/generated/vts_models/strided_slice_quant8_9.model.cpp
@@ -92,6 +92,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/sub.model.cpp b/nn/runtime/test/generated/vts_models/sub.model.cpp
index 90c0914..0487381 100644
--- a/nn/runtime/test/generated/vts_models/sub.model.cpp
+++ b/nn/runtime/test/generated/vts_models/sub.model.cpp
@@ -65,6 +65,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/svdf.model.cpp b/nn/runtime/test/generated/vts_models/svdf.model.cpp
index 87f5251..ef1caf2 100644
--- a/nn/runtime/test/generated/vts_models/svdf.model.cpp
+++ b/nn/runtime/test/generated/vts_models/svdf.model.cpp
@@ -108,6 +108,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {0};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/svdf2.model.cpp b/nn/runtime/test/generated/vts_models/svdf2.model.cpp
index 75ffe28..d91a357 100644
--- a/nn/runtime/test/generated/vts_models/svdf2.model.cpp
+++ b/nn/runtime/test/generated/vts_models/svdf2.model.cpp
@@ -108,6 +108,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {0};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/svdf2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/svdf2_relaxed.model.cpp
new file mode 100644
index 0000000..dea5876
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/svdf2_relaxed.model.cpp
@@ -0,0 +1,116 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {8, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {8, 10},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 80},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 80},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::SVDF,
+            .inputs = {0, 1, 2, 3, 4, 5, 6},
+            .outputs = {7, 8},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2, 3, 4, 5, 6};
+    const std::vector<uint32_t> outputIndexes = {7, 8};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/svdf_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/svdf_relaxed.model.cpp
new file mode 100644
index 0000000..5c15ae5
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/svdf_relaxed.model.cpp
@@ -0,0 +1,116 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 10},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 40},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 40},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::SVDF,
+            .inputs = {0, 1, 2, 3, 4, 5, 6},
+            .outputs = {7, 8},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2, 3, 4, 5, 6};
+    const std::vector<uint32_t> outputIndexes = {7, 8};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/svdf_state.model.cpp b/nn/runtime/test/generated/vts_models/svdf_state.model.cpp
index 164da36..4418917 100644
--- a/nn/runtime/test/generated/vts_models/svdf_state.model.cpp
+++ b/nn/runtime/test/generated/vts_models/svdf_state.model.cpp
@@ -108,6 +108,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/svdf_state_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/svdf_state_relaxed.model.cpp
new file mode 100644
index 0000000..f3ab4bf
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/svdf_state_relaxed.model.cpp
@@ -0,0 +1,116 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 10},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 40},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 40},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::SVDF,
+            .inputs = {0, 1, 2, 3, 4, 5, 6},
+            .outputs = {7, 8},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2, 3, 4, 5, 6};
+    const std::vector<uint32_t> outputIndexes = {7, 8};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/tanh.model.cpp b/nn/runtime/test/generated/vts_models/tanh.model.cpp
index 4b5a71c..eeef20d 100644
--- a/nn/runtime/test/generated/vts_models/tanh.model.cpp
+++ b/nn/runtime/test/generated/vts_models/tanh.model.cpp
@@ -45,6 +45,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/tanh_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/tanh_relaxed.model.cpp
new file mode 100644
index 0000000..3d1585e
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/tanh_relaxed.model.cpp
@@ -0,0 +1,53 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::TANH,
+            .inputs = {0},
+            .outputs = {1},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {1};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/transpose.model.cpp b/nn/runtime/test/generated/vts_models/transpose.model.cpp
index 04eb39c..0862d84 100644
--- a/nn/runtime/test/generated/vts_models/transpose.model.cpp
+++ b/nn/runtime/test/generated/vts_models/transpose.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/transpose_float_1.model.cpp b/nn/runtime/test/generated/vts_models/transpose_float_1.model.cpp
index eb98545..6f05e90 100644
--- a/nn/runtime/test/generated/vts_models/transpose_float_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/transpose_float_1.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/generated/vts_models/transpose_quant8_1.model.cpp b/nn/runtime/test/generated/vts_models/transpose_quant8_1.model.cpp
index a45ca88..1b03d94 100644
--- a/nn/runtime/test/generated/vts_models/transpose_quant8_1.model.cpp
+++ b/nn/runtime/test/generated/vts_models/transpose_quant8_1.model.cpp
@@ -56,6 +56,7 @@
     };
 }
 
+
 bool is_ignored(int i) {
   static std::set<int> ignore = {};
   return ignore.find(i) != ignore.end();
diff --git a/nn/runtime/test/specs/V1_0/mobilenet_224_gender_basic_fixed.mod.py b/nn/runtime/test/specs/V1_0/mobilenet_224_gender_basic_fixed.mod.py
index a1c6352..808445b 100644
--- a/nn/runtime/test/specs/V1_0/mobilenet_224_gender_basic_fixed.mod.py
+++ b/nn/runtime/test/specs/V1_0/mobilenet_224_gender_basic_fixed.mod.py
@@ -251,7 +251,7 @@
 # Example 1
 input0 = { i86: [0.791841, 0.131271, 0.840444, 0.524133, 0.301398, 0.711596, 8.78908e-05, 0.358888, 0.156309, 0.273055, 0.143706, 0.663516, 0.817875, 0.0178006, 0.0663899, 0.38532, 0.108224, 0.120309, 0.252355, 0.468634, 0.535587, 0.372087, 0.0191815, 0.0750463, 0.896686, 0.564102, 0.781927, 0.138955, 0.876559, 0.672544, 0.47254, 0.685613, 0.864712, 0.678431, 0.681087, 0.954624, 0.707985, 0.0945955, 0.663676, 0.0174337, 0.514265, 0.0993437, 0.837646, 0.16886, 0.0206787, 0.460454, 0.298217, 0.0939906, 0.792089, 0.145739, 0.124991, 0.152928, 0.18507, 0.0910606, 0.886938, 0.703805, 0.738545, 0.0914867, 0.785625, 0.255978, 0.25971, 0.564347, 0.496365, 0.40138, 0.181351, 0.229051, 0.528806, 0.815946, 0.723594, 0.0782805, 0.417488, 0.357831, 0.699987, 0.110877, 0.706929, 0.361355, 0.44735, 0.51417, 0.234213, 0.49157, 0.754239, 0.35671, 0.90015, 0.368686, 0.162982, 0.467298, 0.712059, 0.73199, 0.394652, 0.216439, 0.0325005, 0.675254, 0.0965207, 0.919576, 0.46926, 0.923022, 0.0721544, 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-output0 = {i85: [0.605074, 0.0733608, 0.0200205, 0.114568, 0.178815, 0.0580576, 0.123144, 0.232838, 0.0916902, 0.111395, 0.138349]}
+output0 = {i85: [0.605085, 0.0733608, 0.0200205, 0.114568, 0.178815, 0.0580576, 0.123144, 0.232838, 0.0916902, 0.111395, 0.138349]}
 
 Example((input0, output0))