arm_compute v18.08
diff --git a/src/graph/GraphBuilder.cpp b/src/graph/GraphBuilder.cpp
index 4c5d30a..81a18c4 100644
--- a/src/graph/GraphBuilder.cpp
+++ b/src/graph/GraphBuilder.cpp
@@ -25,9 +25,11 @@
#include "arm_compute/graph/Graph.h"
#include "arm_compute/graph/Utils.h"
-#include "arm_compute/graph/algorithms/BFS.h"
+#include "arm_compute/graph/algorithms/TopologicalSort.h"
#include "arm_compute/graph/nodes/Nodes.h"
+#include "support/ToolchainSupport.h"
+
#define CHECK_NODEIDX_PAIR(pair, g) \
ARM_COMPUTE_ERROR_ON(((pair).node_id >= (g).nodes().size()) || ((g).node((pair).node_id) == nullptr) || ((pair).index >= (g).node((pair).node_id)->num_outputs()));
@@ -79,43 +81,6 @@
return nid;
}
-
-NodeID create_grouped_convolution(Graph &g, NodeParams ¶ms, NodeIdxPair input, NodeID weights, NodeID bias,
- PadStrideInfo conv_info, ConvolutionMethod method, FastMathHint fast_math_hint, unsigned int num_groups)
-{
- bool has_bias = (bias != EmptyNodeID);
-
- // Split input
- NodeID input_split = GraphBuilder::add_split_node(g, params, input, num_groups, 2);
-
- // Split weights
- NodeID weights_split = GraphBuilder::add_split_node(g, params, { weights, 0 }, num_groups, 3);
-
- // Split bias
- NodeID bias_split = EmptyNodeID;
- if(has_bias)
- {
- // Split bias
- bias_split = GraphBuilder::add_split_node(g, params, { bias, 0 }, num_groups, 0);
- }
-
- std::vector<NodeIdxPair> convolution_outputs;
- for(unsigned int i = 0; i < num_groups; ++i)
- {
- NodeID conv_nid = g.add_node<ConvolutionLayerNode>(conv_info, method, fast_math_hint);
- g.add_connection(input_split, i, conv_nid, 0);
- g.add_connection(weights_split, i, conv_nid, 1);
- if(has_bias)
- {
- g.add_connection(bias_split, i, conv_nid, 2);
- }
- set_node_params(g, conv_nid, params);
- convolution_outputs.push_back({ conv_nid, 0 });
- }
-
- // Depth concatenate output
- return GraphBuilder::add_depth_concatenate_node(g, params, convolution_outputs);
-}
} // namespace
NodeID GraphBuilder::add_const_node(Graph &g, NodeParams params, TensorDescriptor desc, ITensorAccessorUPtr accessor)
@@ -203,6 +168,11 @@
return batch_norm_nid;
}
+NodeID GraphBuilder::add_channel_shuffle_node(Graph &g, NodeParams params, NodeIdxPair input, unsigned int num_groups)
+{
+ return create_simple_single_input_output_node<ChannelShuffleLayerNode>(g, params, input, num_groups);
+}
+
NodeID GraphBuilder::add_convolution_node(Graph &g, NodeParams params, NodeIdxPair input,
Size2D kernel_spatial_extend, unsigned int depth, PadStrideInfo conv_info,
unsigned int num_groups, ConvolutionMethod method, FastMathHint fast_math_hint,
@@ -239,34 +209,81 @@
{
TensorDescriptor b_desc = input_tensor_desc;
b_desc.shape = TensorShape(depth);
- b_nid = add_const_node_with_name(g, params, "Bias", b_desc, std::move(bias_accessor));
- }
-
- if(num_groups == 1)
- {
- // Create convolution node and connect
- NodeID conv_nid = g.add_node<ConvolutionLayerNode>(conv_info, method, fast_math_hint, out_quant_info);
- g.add_connection(input.node_id, input.index, conv_nid, 0);
- g.add_connection(w_nid, 0, conv_nid, 1);
- if(has_bias)
+ if(is_data_type_quantized_asymmetric(input_tensor_desc.data_type))
{
- g.add_connection(b_nid, 0, conv_nid, 2);
+ b_desc.data_type = DataType::S32;
}
- set_node_params(g, conv_nid, params);
+ b_nid = add_const_node_with_name(g, params, "Bias", b_desc, std::move(bias_accessor));
+ }
- return conv_nid;
- }
- else
+ // Create convolution node and connect
+ NodeID conv_nid = g.add_node<ConvolutionLayerNode>(conv_info, num_groups, method, fast_math_hint, out_quant_info);
+ g.add_connection(input.node_id, input.index, conv_nid, 0);
+ g.add_connection(w_nid, 0, conv_nid, 1);
+ if(has_bias)
{
- return create_grouped_convolution(g, params, input, w_nid, b_nid, conv_info, method, fast_math_hint, num_groups);
+ g.add_connection(b_nid, 0, conv_nid, 2);
}
+ set_node_params(g, conv_nid, params);
+
+ return conv_nid;
}
-NodeID GraphBuilder::add_depth_concatenate_node(Graph &g, NodeParams params, std::vector<NodeIdxPair> inputs)
+NodeID GraphBuilder::add_deconvolution_node(Graph &g, NodeParams params, NodeIdxPair input,
+ Size2D kernel_spatial_extend, unsigned int depth, PadStrideInfo deconv_info,
+ Size2D inner_border, ITensorAccessorUPtr weights_accessor,
+ ITensorAccessorUPtr bias_accessor)
+{
+ CHECK_NODEIDX_PAIR(input, g);
+ ARM_COMPUTE_ERROR_ON(depth == 0);
+ ARM_COMPUTE_ERROR_ON((kernel_spatial_extend.width == 0) || (kernel_spatial_extend.height == 0));
+
+ bool has_bias = (bias_accessor != nullptr);
+
+ // Get input tensor descriptor
+ const TensorDescriptor input_tensor_desc = get_tensor_descriptor(g, g.node(input.node_id)->outputs()[0]);
+
+ // Create weights node
+ TensorDescriptor w_desc = input_tensor_desc;
+ w_desc.shape.set(get_dimension_idx(input_tensor_desc, DataLayoutDimension::WIDTH), kernel_spatial_extend.width);
+ w_desc.shape.set(get_dimension_idx(input_tensor_desc, DataLayoutDimension::HEIGHT), kernel_spatial_extend.height);
+ w_desc.shape.set(get_dimension_idx(input_tensor_desc, DataLayoutDimension::CHANNEL),
+ get_dimension_size(input_tensor_desc, DataLayoutDimension::CHANNEL));
+ w_desc.shape.set(get_dimension_idx(input_tensor_desc, DataLayoutDimension::BATCHES), depth);
+
+ NodeID w_nid = add_const_node_with_name(g, params, "Weights", w_desc, std::move(weights_accessor));
+
+ // Create bias nodes
+ NodeID b_nid = EmptyNodeID;
+ if(has_bias)
+ {
+ TensorDescriptor b_desc = input_tensor_desc;
+ b_desc.shape = TensorShape(depth);
+ if(is_data_type_quantized_asymmetric(input_tensor_desc.data_type))
+ {
+ b_desc.data_type = DataType::S32;
+ }
+ b_nid = add_const_node_with_name(g, params, "Bias", b_desc, std::move(bias_accessor));
+ }
+
+ // Create convolution node and connect
+ NodeID deconv_nid = g.add_node<DeconvolutionLayerNode>(deconv_info, inner_border);
+ g.add_connection(input.node_id, input.index, deconv_nid, 0);
+ g.add_connection(w_nid, 0, deconv_nid, 1);
+ if(has_bias)
+ {
+ g.add_connection(b_nid, 0, deconv_nid, 2);
+ }
+ set_node_params(g, deconv_nid, params);
+
+ return deconv_nid;
+}
+
+NodeID GraphBuilder::add_concatenate_node(Graph &g, NodeParams params, std::vector<NodeIdxPair> inputs, DataLayoutDimension axis)
{
ARM_COMPUTE_ERROR_ON(inputs.size() == 0);
- NodeID nid = g.add_node<DepthConcatenateLayerNode>(inputs.size());
+ NodeID nid = g.add_node<ConcatenateLayerNode>(inputs.size(), axis);
unsigned int i = 0;
for(const auto &input : inputs)
@@ -309,7 +326,7 @@
if(has_bias)
{
TensorDescriptor b_desc = input_tensor_desc;
- b_desc.shape = TensorShape(b_desc.shape.z());
+ b_desc.shape = TensorShape(get_dimension_size(input_tensor_desc, DataLayoutDimension::CHANNEL));
b_nid = add_const_node_with_name(g, params, "Bias", b_desc, std::move(bias_accessor));
}
@@ -326,6 +343,11 @@
return conv_nid;
}
+NodeID GraphBuilder::add_dummy_node(Graph &g, NodeParams params, NodeIdxPair input, TensorShape shape)
+{
+ return create_simple_single_input_output_node<DummyNode>(g, params, input, shape);
+}
+
NodeID GraphBuilder::add_elementwise_node(Graph &g, NodeParams params, NodeIdxPair input0, NodeIdxPair input1, EltwiseOperation operation)
{
CHECK_NODEIDX_PAIR(input0, g);
@@ -347,7 +369,9 @@
}
NodeID GraphBuilder::add_fully_connected_layer(Graph &g, NodeParams params, NodeIdxPair input, unsigned int num_outputs,
- ITensorAccessorUPtr weights_accessor, ITensorAccessorUPtr bias_accessor)
+ ITensorAccessorUPtr weights_accessor, ITensorAccessorUPtr bias_accessor,
+ const FullyConnectedLayerInfo fc_info,
+ const QuantizationInfo weights_quant_info, const QuantizationInfo out_quant_info)
{
CHECK_NODEIDX_PAIR(input, g);
ARM_COMPUTE_ERROR_ON(num_outputs == 0);
@@ -358,7 +382,7 @@
const TensorDescriptor input_tensor_desc = get_tensor_descriptor(g, g.node(input.node_id)->outputs()[0]);
// Create weights node
- TensorDescriptor w_desc = FullyConnectedLayerNode::compute_weights_descriptor(input_tensor_desc, num_outputs);
+ TensorDescriptor w_desc = FullyConnectedLayerNode::compute_weights_descriptor(input_tensor_desc, num_outputs, fc_info, weights_quant_info);
NodeID w_nid = add_const_node_with_name(g, params, "Weights", w_desc, std::move(weights_accessor));
// Create bias nodes
@@ -367,11 +391,15 @@
{
TensorDescriptor b_desc = input_tensor_desc;
b_desc.shape = TensorShape(num_outputs);
- b_nid = add_const_node_with_name(g, params, "Bias", b_desc, std::move(bias_accessor));
+ if(is_data_type_quantized_asymmetric(input_tensor_desc.data_type))
+ {
+ b_desc.data_type = DataType::S32;
+ }
+ b_nid = add_const_node_with_name(g, params, "Bias", b_desc, std::move(bias_accessor));
}
- // Create convolution node and connect
- NodeID fc_nid = g.add_node<FullyConnectedLayerNode>(num_outputs);
+ // Create fully connected node and connect
+ NodeID fc_nid = g.add_node<FullyConnectedLayerNode>(num_outputs, out_quant_info, fc_info);
g.add_connection(input.node_id, input.index, fc_nid, 0);
g.add_connection(w_nid, 0, fc_nid, 1);
if(has_bias)
@@ -389,6 +417,11 @@
return create_simple_single_input_output_node<NormalizationLayerNode>(g, params, input, norm_info);
}
+NodeID GraphBuilder::add_permute_node(Graph &g, NodeParams params, NodeIdxPair input, PermutationVector perm, DataLayout layout)
+{
+ return create_simple_single_input_output_node<PermuteLayerNode>(g, params, input, perm, layout);
+}
+
NodeID GraphBuilder::add_pooling_node(Graph &g, NodeParams params, NodeIdxPair input, PoolingLayerInfo pool_info)
{
return create_simple_single_input_output_node<PoolingLayerNode>(g, params, input, pool_info);
@@ -399,6 +432,12 @@
return create_simple_single_input_output_node<ReshapeLayerNode>(g, params, input, shape);
}
+NodeID GraphBuilder::add_resize_node(Graph &g, NodeParams params, NodeIdxPair input, InterpolationPolicy policy,
+ float width_scale, float height_scale)
+{
+ return create_simple_single_input_output_node<ResizeLayerNode>(g, params, input, policy, width_scale, height_scale);
+}
+
NodeID GraphBuilder::add_scale_layer(Graph &g, const NodeParams ¶ms, NodeIdxPair input, ITensorAccessorUPtr mul_accessor, ITensorAccessorUPtr add_accessor)
{
CHECK_NODEIDX_PAIR(input, g);
@@ -421,9 +460,9 @@
NodeIdxPair add_const_nidxp = { add_const_nid, 0 };
// Create node and connect
- NodeID mul_node = GraphBuilder::add_elementwise_node(g, params, input, mul_const_nidxp, EltwiseOperation::MUL);
+ NodeID mul_node = GraphBuilder::add_elementwise_node(g, params, input, mul_const_nidxp, EltwiseOperation::Mul);
NodeIdxPair mulnode_nidxp = { mul_node, 0 };
- NodeID add_node = GraphBuilder::add_elementwise_node(g, params, mulnode_nidxp, add_const_nidxp, EltwiseOperation::ADD);
+ NodeID add_node = GraphBuilder::add_elementwise_node(g, params, mulnode_nidxp, add_const_nidxp, EltwiseOperation::Add);
return add_node;
}
@@ -438,4 +477,4 @@
return create_simple_single_input_output_node<SplitLayerNode>(g, params, input, num_splits, axis);
}
} // namespace graph
-} // namespace arm_compute
\ No newline at end of file
+} // namespace arm_compute