COMPMID-1805: Implement SRCNN 9-5-5

Change-Id: I2463c44e79e8df3dc081c645b2aa37468d5b9f0b
Reviewed-on: https://review.mlplatform.org/346
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <Anthony.barbier@arm.com>

1 files changed, 159 insertions, 0 deletions

diff --git a/examples/graph_srcnn955.cpp b/examples/graph_srcnn955.cpp
new file mode 100644
index 0000000000..f03e8fe287
--- /dev/null
+++ b/examples/graph_srcnn955.cpp
@@ -0,0 +1,159 @@
+/*
+ * 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::utils;
+using namespace arm_compute::graph::frontend;
+using namespace arm_compute::graph_utils;
+
+/** Example demonstrating how to implement SRCNN 9-5-5 network using the Compute Library's graph API */
+class GraphSRCNN955Example : public Example
+{
+public:
+    GraphSRCNN955Example()
+        : cmd_parser(), common_opts(cmd_parser), model_input_width(nullptr), model_input_height(nullptr), common_params(), graph(0, "SRCNN955")
+    {
+        model_input_width  = cmd_parser.add_option<SimpleOption<unsigned int>>("image-width", 300);
+        model_input_height = cmd_parser.add_option<SimpleOption<unsigned int>>("image-height", 300);
+
+        // Add model id option
+        model_input_width->set_help("Input image width.");
+        model_input_height->set_help("Input image height.");
+    }
+    GraphSRCNN955Example(const GraphSRCNN955Example &) = delete;
+    GraphSRCNN955Example &operator=(const GraphSRCNN955Example &) = delete;
+    GraphSRCNN955Example(GraphSRCNN955Example &&)                 = default; // NOLINT
+    GraphSRCNN955Example &operator=(GraphSRCNN955Example &&) = default;      // NOLINT
+    ~GraphSRCNN955Example() 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;
+
+        // Checks
+        ARM_COMPUTE_EXIT_ON_MSG(arm_compute::is_data_type_quantized_asymmetric(common_params.data_type), "QASYMM8 not supported for this graph");
+
+        // Get trainable parameters data path
+        const std::string data_path  = common_params.data_path;
+        const std::string model_path = "/cnn_data/srcnn955_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, 3U, 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;
+
+        graph << common_params.target
+              << common_params.fast_math_hint
+              << InputLayer(input_descriptor, get_input_accessor(common_params, std::move(preprocessor), false /* Do not convert to BGR */))
+              << ConvolutionLayer(
+                  9U, 9U, 64U,
+                  get_weights_accessor(data_path, "conv1_weights.npy", weights_layout),
+                  get_weights_accessor(data_path, "conv1_biases.npy"),
+                  PadStrideInfo(1, 1, 4, 4))
+              .set_name("conv1/convolution")
+              << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("conv1/Relu")
+              << ConvolutionLayer(
+                  5U, 5U, 32U,
+                  get_weights_accessor(data_path, "conv2_weights.npy", weights_layout),
+                  get_weights_accessor(data_path, "conv2_biases.npy"),
+                  PadStrideInfo(1, 1, 2, 2))
+              .set_name("conv2/convolution")
+              << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("conv2/Relu")
+              << ConvolutionLayer(
+                  5U, 5U, 3U,
+                  get_weights_accessor(data_path, "conv3_weights.npy", weights_layout),
+                  get_weights_accessor(data_path, "conv3_biases.npy"),
+                  PadStrideInfo(1, 1, 2, 2))
+              .set_name("conv3/convolution")
+              << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("conv3/Relu")
+              << 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;
+        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 SRCNN 9-5-5
+ *
+ * Model is based on:
+ *      http://mmlab.ie.cuhk.edu.hk/projects/SRCNN.html
+ *      "Image Super-Resolution Using Deep Convolutional Networks"
+ *      Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang
+ *
+ * @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<GraphSRCNN955Example>(argc, argv);
+}