arm_compute v19.02
Change-Id: I853a3ecf38f206da13c1b03640c8adf73c20477c
diff --git a/examples/graph_vgg_vdsr.cpp b/examples/graph_vgg_vdsr.cpp
new file mode 100644
index 0000000..ca7d10f
--- /dev/null
+++ b/examples/graph_vgg_vdsr.cpp
@@ -0,0 +1,178 @@
+/*
+ * Copyright (c) 2018 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "arm_compute/graph.h"
+#include "support/ToolchainSupport.h"
+#include "utils/CommonGraphOptions.h"
+#include "utils/GraphUtils.h"
+#include "utils/Utils.h"
+
+using namespace arm_compute;
+using namespace arm_compute::utils;
+using namespace arm_compute::graph::frontend;
+using namespace arm_compute::graph_utils;
+
+/** Example demonstrating how to implement VGG based VDSR network using the Compute Library's graph API */
+class GraphVDSRExample : public Example
+{
+public:
+ GraphVDSRExample()
+ : cmd_parser(), common_opts(cmd_parser), common_params(), graph(0, "VDSR")
+ {
+ model_input_width = cmd_parser.add_option<SimpleOption<unsigned int>>("image-width", 192);
+ model_input_height = cmd_parser.add_option<SimpleOption<unsigned int>>("image-height", 192);
+
+ // Add model id option
+ model_input_width->set_help("Input image width.");
+ model_input_height->set_help("Input image height.");
+ }
+ GraphVDSRExample(const GraphVDSRExample &) = delete;
+ GraphVDSRExample &operator=(const GraphVDSRExample &) = delete;
+ GraphVDSRExample(GraphVDSRExample &&) = default; // NOLINT
+ GraphVDSRExample &operator=(GraphVDSRExample &&) = default; // NOLINT
+ ~GraphVDSRExample() override = default;
+ bool do_setup(int argc, char **argv) override
+ {
+ // Parse arguments
+ cmd_parser.parse(argc, argv);
+
+ // Consume common parameters
+ common_params = consume_common_graph_parameters(common_opts);
+
+ // Return when help menu is requested
+ if(common_params.help)
+ {
+ cmd_parser.print_help(argv[0]);
+ return false;
+ }
+
+ // Get input image width and height
+ const unsigned int image_width = model_input_width->value();
+ const unsigned int image_height = model_input_height->value();
+
+ // Print parameter values
+ std::cout << common_params << std::endl;
+ std::cout << "Image width: " << image_width << std::endl;
+ std::cout << "Image height: " << image_height << std::endl;
+
+ // Get trainable parameters data path
+ const std::string data_path = common_params.data_path;
+ const std::string model_path = "/cnn_data/vdsr_model/";
+
+ // Create a preprocessor object
+ std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>();
+
+ // Create input descriptor
+ const TensorShape tensor_shape = permute_shape(TensorShape(image_width, image_height, 1U, 1U), DataLayout::NCHW, common_params.data_layout);
+ TensorDescriptor input_descriptor = TensorDescriptor(tensor_shape, common_params.data_type).set_layout(common_params.data_layout);
+
+ // Set weights trained layout
+ const DataLayout weights_layout = DataLayout::NCHW;
+
+ // Note: Quantization info are random and used only for benchmarking purposes
+ graph << common_params.target
+ << common_params.fast_math_hint
+ << InputLayer(input_descriptor.set_quantization_info(QuantizationInfo(0.0078125f, 128)),
+ get_input_accessor(common_params, std::move(preprocessor), false));
+
+ SubStream left(graph);
+ SubStream right(graph);
+
+ // Layer 1
+ right << ConvolutionLayer(
+ 3U, 3U, 64U,
+ get_weights_accessor(data_path, "conv0_w.npy", weights_layout),
+ get_weights_accessor(data_path, "conv0_b.npy"),
+ PadStrideInfo(1, 1, 1, 1), 1, QuantizationInfo(0.031778190285f, 156), QuantizationInfo(0.0784313753247f, 128))
+ .set_name("conv0")
+ << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("conv0/Relu");
+
+ // Rest 17 layers
+ for(unsigned int i = 1; i < 19; ++i)
+ {
+ const std::string conv_w_path = "conv" + arm_compute::support::cpp11::to_string(i) + "_w.npy";
+ const std::string conv_b_path = "conv" + arm_compute::support::cpp11::to_string(i) + "_b.npy";
+ const std::string conv_name = "conv" + arm_compute::support::cpp11::to_string(i);
+ right << ConvolutionLayer(
+ 3U, 3U, 64U,
+ get_weights_accessor(data_path, conv_w_path, weights_layout),
+ get_weights_accessor(data_path, conv_b_path),
+ PadStrideInfo(1, 1, 1, 1), 1, QuantizationInfo(0.015851572156f, 93))
+ .set_name(conv_name)
+ << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name(conv_name + "/Relu");
+ }
+
+ // Final layer
+ right << ConvolutionLayer(
+ 3U, 3U, 1U,
+ get_weights_accessor(data_path, "conv20_w.npy", weights_layout),
+ get_weights_accessor(data_path, "conv20_b.npy"),
+ PadStrideInfo(1, 1, 1, 1), 1, QuantizationInfo(0.015851572156f, 93))
+ .set_name("conv20")
+ << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("conv20/Relu");
+
+ // Add residual to input
+ graph << EltwiseLayer(std::move(left), std::move(right), EltwiseOperation::Add).set_name("add")
+ << OutputLayer(arm_compute::support::cpp14::make_unique<DummyAccessor>(0));
+
+ // Finalize graph
+ GraphConfig config;
+ config.num_threads = common_params.threads;
+ config.use_tuner = common_params.enable_tuner;
+ config.tuner_file = common_params.tuner_file;
+
+ graph.finalize(common_params.target, config);
+
+ return true;
+ }
+ void do_run() override
+ {
+ // Run graph
+ graph.run();
+ }
+
+private:
+ CommandLineParser cmd_parser;
+ CommonGraphOptions common_opts;
+ SimpleOption<unsigned int> *model_input_width{ nullptr };
+ SimpleOption<unsigned int> *model_input_height{ nullptr };
+ CommonGraphParams common_params;
+ Stream graph;
+};
+
+/** Main program for VGG-based VDSR
+ *
+ * Model is based on:
+ * https://arxiv.org/pdf/1511.04587.pdf
+ * "Accurate Image Super-Resolution Using Very Deep Convolutional Networks"
+ * Jiwon Kim, Jung Kwon Lee and Kyoung Mu Lee
+ *
+ * @note To list all the possible arguments execute the binary appended with the --help option
+ *
+ * @param[in] argc Number of arguments
+ * @param[in] argv Arguments
+ */
+int main(int argc, char **argv)
+{
+ return arm_compute::utils::run_example<GraphVDSRExample>(argc, argv);
+}