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Diffstat (limited to 'examples/graph_mnist.cpp')
| -rw-r--r-- | examples/graph_mnist.cpp | 170 |
1 files changed, 170 insertions, 0 deletions
diff --git a/examples/graph_mnist.cpp b/examples/graph_mnist.cpp new file mode 100644 index 0000000000..eb66138df4 --- /dev/null +++ b/examples/graph_mnist.cpp @@ -0,0 +1,170 @@ +/* + * Copyright (c) 2019 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 Mnist's network using the Compute Library's graph API */ +class GraphMnistExample : public Example +{ +public: + GraphMnistExample() + : cmd_parser(), common_opts(cmd_parser), common_params(), graph(0, "LeNet") + { + } + bool do_setup(int argc, char **argv) override + { + // Parse arguments + cmd_parser.parse(argc, argv); + cmd_parser.validate(); + + // 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; + } + + // Print parameter values + std::cout << common_params << std::endl; + + // Get trainable parameters data path + std::string data_path = common_params.data_path; + + // Add model path to data path + if(!data_path.empty() && arm_compute::is_data_type_quantized_asymmetric(common_params.data_type)) + { + data_path += "/cnn_data/mnist_qasymm8_model/"; + } + + // Create input descriptor + const TensorShape tensor_shape = permute_shape(TensorShape(28U, 28U, 1U), DataLayout::NCHW, common_params.data_layout); + TensorDescriptor input_descriptor = TensorDescriptor(tensor_shape, common_params.data_type).set_layout(common_params.data_layout); + + const QuantizationInfo in_quant_info = QuantizationInfo(0.003921568859368563f, 0); + + const std::vector<std::pair<QuantizationInfo, QuantizationInfo>> conv_quant_info = + { + { QuantizationInfo(0.004083447158336639f, 138), QuantizationInfo(0.0046257381327450275f, 0) }, // conv0 + { QuantizationInfo(0.0048590428195893764f, 149), QuantizationInfo(0.03558270260691643f, 0) }, // conv1 + { QuantizationInfo(0.004008443560451269f, 146), QuantizationInfo(0.09117382764816284f, 0) }, // conv2 + { QuantizationInfo(0.004344311077147722f, 160), QuantizationInfo(0.5494495034217834f, 167) }, // fc + }; + + // Set weights trained layout + const DataLayout weights_layout = DataLayout::NHWC; + FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo(); + fc_info.set_weights_trained_layout(weights_layout); + + graph << common_params.target + << common_params.fast_math_hint + << InputLayer(input_descriptor.set_quantization_info(in_quant_info), + get_input_accessor(common_params)) + << ConvolutionLayer( + 3U, 3U, 32U, + get_weights_accessor(data_path, "conv2d_weights_quant_FakeQuantWithMinMaxVars.npy", weights_layout), + get_weights_accessor(data_path, "conv2d_Conv2D_bias.npy"), + PadStrideInfo(1U, 1U, 1U, 1U), 1, conv_quant_info.at(0).first, conv_quant_info.at(0).second) + .set_name("Conv0") + + << ConvolutionLayer( + 3U, 3U, 32U, + get_weights_accessor(data_path, "conv2d_1_weights_quant_FakeQuantWithMinMaxVars.npy", weights_layout), + get_weights_accessor(data_path, "conv2d_1_Conv2D_bias.npy"), + PadStrideInfo(1U, 1U, 1U, 1U), 1, conv_quant_info.at(1).first, conv_quant_info.at(1).second) + .set_name("conv1") + + << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0))).set_name("maxpool1") + + << ConvolutionLayer( + 3U, 3U, 32U, + get_weights_accessor(data_path, "conv2d_2_weights_quant_FakeQuantWithMinMaxVars.npy", weights_layout), + get_weights_accessor(data_path, "conv2d_2_Conv2D_bias.npy"), + PadStrideInfo(1U, 1U, 1U, 1U), 1, conv_quant_info.at(2).first, conv_quant_info.at(2).second) + .set_name("conv2") + + << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0))).set_name("maxpool2") + + << FullyConnectedLayer( + 10U, + get_weights_accessor(data_path, "dense_weights_quant_FakeQuantWithMinMaxVars_transpose.npy", weights_layout), + get_weights_accessor(data_path, "dense_MatMul_bias.npy"), + fc_info, conv_quant_info.at(3).first, conv_quant_info.at(3).second) + .set_name("fc") + + << SoftmaxLayer().set_name("prob"); + + if(arm_compute::is_data_type_quantized_asymmetric(common_params.data_type)) + { + graph << DequantizationLayer().set_name("dequantize"); + } + + graph << OutputLayer(get_output_accessor(common_params, 5)); + + // Finalize graph + GraphConfig config; + config.num_threads = common_params.threads; + config.use_tuner = common_params.enable_tuner; + config.tuner_mode = common_params.tuner_mode; + 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; + CommonGraphParams common_params; + Stream graph; +}; + +/** Main program for Mnist Example + * + * @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<GraphMnistExample>(argc, argv); +} |