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author | Michele Di Giorgio <michele.digiorgio@arm.com> | 2018-02-14 14:18:01 +0000 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:47:18 +0000 |
commit | e3fba0afa892c66379da1e3d3843f2155a1fb29a (patch) | |
tree | 2a420a3d988d269cc157d73e8d3c8accf1d21af8 /examples/graph_cl_mobilenet_qasymm8.cpp | |
parent | f07d28d9ee8ae73a93fe433f72855b6dcf58ad90 (diff) | |
download | ComputeLibrary-e3fba0afa892c66379da1e3d3843f2155a1fb29a.tar.gz |
COMPMID-925: Enabling OpenCL tuner in the graph examples
Change-Id: I4fe501281f527e20e8fdd0253d59ea2c4629056b
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/120354
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Diffstat (limited to 'examples/graph_cl_mobilenet_qasymm8.cpp')
-rw-r--r-- | examples/graph_cl_mobilenet_qasymm8.cpp | 223 |
1 files changed, 0 insertions, 223 deletions
diff --git a/examples/graph_cl_mobilenet_qasymm8.cpp b/examples/graph_cl_mobilenet_qasymm8.cpp deleted file mode 100644 index 046c7779b1..0000000000 --- a/examples/graph_cl_mobilenet_qasymm8.cpp +++ /dev/null @@ -1,223 +0,0 @@ -/* - * Copyright (c) 2017-2018 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/Graph.h" -#include "arm_compute/graph/Nodes.h" -#include "support/ToolchainSupport.h" -#include "utils/GraphUtils.h" -#include "utils/Utils.h" - -using namespace arm_compute; -using namespace arm_compute::graph; -using namespace arm_compute::graph_utils; - -/** Example demonstrating how to implement QASYMM8 MobileNet's network using the Compute Library's graph API - * - * @param[in] argc Number of arguments - * @param[in] argv Arguments ( [optional] Path to the weights folder, [optional] npy_input, [optional] labels ) - */ -class GraphMobileNetQASYMM8Example : public utils::Example -{ -public: - void do_setup(int argc, char **argv) override - { - std::string data_path; /* Path to the trainable data */ - std::string input; /* Image data */ - std::string label; /* Label data */ - - // Quantization info taken from the AndroidNN QASYMM8 MobileNet example - const QuantizationInfo in_quant_info = QuantizationInfo(0.0078125f, 128); - const QuantizationInfo mid_quant_info = QuantizationInfo(0.0784313753247f, 128); - - const std::vector<QuantizationInfo> conv_weights_quant_info = - { - QuantizationInfo(0.031778190285f, 156), // conv0 - QuantizationInfo(0.00604454148561f, 66) // conv14 - }; - - const std::vector<QuantizationInfo> depth_weights_quant_info = - { - QuantizationInfo(0.254282623529f, 129), // dwsc1 - QuantizationInfo(0.12828284502f, 172), // dwsc2 - QuantizationInfo(0.265911251307f, 83), // dwsc3 - QuantizationInfo(0.0985597148538f, 30), // dwsc4 - QuantizationInfo(0.0631204470992f, 54), // dwsc5 - QuantizationInfo(0.0137207424268f, 141), // dwsc6 - QuantizationInfo(0.0817828401923f, 125), // dwsc7 - QuantizationInfo(0.0393880493939f, 164), // dwsc8 - QuantizationInfo(0.211694166064f, 129), // dwsc9 - QuantizationInfo(0.158015936613f, 103), // dwsc10 - QuantizationInfo(0.0182712618262f, 137), // dwsc11 - QuantizationInfo(0.0127998134121f, 134), // dwsc12 - QuantizationInfo(0.299285322428f, 161) // dwsc13 - }; - - const std::vector<QuantizationInfo> point_weights_quant_info = - { - QuantizationInfo(0.0425766184926f, 129), // dwsc1 - QuantizationInfo(0.0250773020089f, 94), // dwsc2 - QuantizationInfo(0.015851572156f, 93), // dwsc3 - QuantizationInfo(0.0167811904103f, 98), // dwsc4 - QuantizationInfo(0.00951790809631f, 135), // dwsc5 - QuantizationInfo(0.00999817531556f, 128), // dwsc6 - QuantizationInfo(0.00590536883101f, 126), // dwsc7 - QuantizationInfo(0.00576109671965f, 133), // dwsc8 - QuantizationInfo(0.00830461271107f, 142), // dwsc9 - QuantizationInfo(0.0152327232063f, 72), // dwsc10 - QuantizationInfo(0.00741417845711f, 125), // dwsc11 - QuantizationInfo(0.0135628981516f, 142), // dwsc12 - QuantizationInfo(0.0338749065995f, 140) // dwsc13 - }; - - // Parse arguments - if(argc < 2) - { - // Print help - std::cout << "Usage: " << argv[0] << " [path_to_data] [npy_input] [labels]\n\n"; - std::cout << "No data folder provided: using random values\n\n"; - } - else if(argc == 2) - { - data_path = argv[1]; - std::cout << "Usage: " << argv[0] << " " << argv[1] << " [npy_input] [labels]\n\n"; - std::cout << "No input provided: using random values\n\n"; - } - else if(argc == 3) - { - data_path = argv[1]; - input = argv[2]; - std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " [labels]\n\n"; - std::cout << "No text file with labels provided: skipping output accessor\n\n"; - } - else - { - data_path = argv[1]; - input = argv[2]; - label = argv[3]; - } - - graph << TargetHint::OPENCL - << arm_compute::graph::Tensor(TensorInfo(TensorShape(224U, 224U, 3U, 1U), 1, DataType::QASYMM8, in_quant_info), - get_weights_accessor(data_path, "/cnn_data/mobilenet_qasymm8_model/" + input)) - << ConvolutionLayer( - 3U, 3U, 32U, - get_weights_accessor(data_path, "/cnn_data/mobilenet_qasymm8_model/Conv2d_0_weights.npy"), - get_weights_accessor(data_path, "/cnn_data/mobilenet_qasymm8_model/Conv2d_0_bias.npy"), - PadStrideInfo(2U, 2U, 0U, 1U, 0U, 1U, DimensionRoundingType::FLOOR), - 1, WeightsInfo(), - conv_weights_quant_info.at(0), - mid_quant_info) - << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f)) - << get_dwsc_node(data_path, "Conv2d_1", 64U, PadStrideInfo(1U, 1U, 1U, 1U), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(0), point_weights_quant_info.at(0)) - << get_dwsc_node(data_path, "Conv2d_2", 128U, PadStrideInfo(2U, 2U, 0U, 1U, 0U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(1), - point_weights_quant_info.at(1)) - << get_dwsc_node(data_path, "Conv2d_3", 128U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(2), - point_weights_quant_info.at(2)) - << get_dwsc_node(data_path, "Conv2d_4", 256U, PadStrideInfo(2U, 2U, 0U, 1U, 0U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(3), - point_weights_quant_info.at(3)) - << get_dwsc_node(data_path, "Conv2d_5", 256U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(4), - point_weights_quant_info.at(4)) - << get_dwsc_node(data_path, "Conv2d_6", 512U, PadStrideInfo(2U, 2U, 0U, 1U, 0U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(5), - point_weights_quant_info.at(5)) - << get_dwsc_node(data_path, "Conv2d_7", 512U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(6), - point_weights_quant_info.at(6)) - << get_dwsc_node(data_path, "Conv2d_8", 512U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(7), - point_weights_quant_info.at(7)) - << get_dwsc_node(data_path, "Conv2d_9", 512U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(8), - point_weights_quant_info.at(8)) - << get_dwsc_node(data_path, "Conv2d_10", 512U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(9), - point_weights_quant_info.at(9)) - << get_dwsc_node(data_path, "Conv2d_11", 512U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(10), - point_weights_quant_info.at(10)) - << get_dwsc_node(data_path, "Conv2d_12", 1024U, PadStrideInfo(2U, 2U, 0U, 1U, 0U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(11), - point_weights_quant_info.at(11)) - << get_dwsc_node(data_path, "Conv2d_13", 1024U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(12), - point_weights_quant_info.at(12)) - << PoolingLayer(PoolingLayerInfo(PoolingType::AVG)) - << ConvolutionLayer( - 1U, 1U, 1001U, - get_weights_accessor(data_path, "/cnn_data/mobilenet_qasymm8_model/Logits_Conv2d_1c_1x1_weights.npy"), - get_weights_accessor(data_path, "/cnn_data/mobilenet_qasymm8_model/Logits_Conv2d_1c_1x1_bias.npy"), - PadStrideInfo(1U, 1U, 0U, 0U), 1, WeightsInfo(), conv_weights_quant_info.at(1)) - << ReshapeLayer(TensorShape(1001U)) - << SoftmaxLayer() - << arm_compute::graph::Tensor(get_output_accessor(label, 5)); - } - void do_run() override - { - // Run graph - graph.run(); - } - -private: - Graph graph{}; - - /** This function produces a depthwise separable convolution node (i.e. depthwise + pointwise layers) with ReLU6 activation after each layer. - * - * @param[in] data_path Path to trainable data folder - * @param[in] param_path Prefix of specific set of weights/biases data - * @param[in] conv_filt Filters depths for pointwise convolution - * @param[in] dwc_pad_stride_info PadStrideInfo for depthwise convolution - * @param[in] conv_pad_stride_info PadStrideInfo for pointwise convolution - * @param[in] depth_weights_quant_info QuantizationInfo for depthwise convolution's weights - * @param[in] point_weights_quant_info QuantizationInfo for pointwise convolution's weights - * - * @return The complete dwsc node - */ - BranchLayer get_dwsc_node(const std::string &data_path, std::string &¶m_path, - const unsigned int conv_filt, - PadStrideInfo dwc_pad_stride_info, PadStrideInfo conv_pad_stride_info, - QuantizationInfo depth_weights_quant_info, QuantizationInfo point_weights_quant_info) - { - std::string total_path = "/cnn_data/mobilenet_qasymm8_model/" + param_path + "_"; - SubGraph sg; - - sg << DepthwiseConvolutionLayer( - 3U, 3U, - get_weights_accessor(data_path, total_path + "depthwise_weights.npy"), - get_weights_accessor(data_path, total_path + "depthwise_bias.npy"), - dwc_pad_stride_info, - true, - depth_weights_quant_info) - << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f)) - << ConvolutionLayer( - 1U, 1U, conv_filt, - get_weights_accessor(data_path, total_path + "pointwise_weights.npy"), - get_weights_accessor(data_path, total_path + "pointwise_bias.npy"), - conv_pad_stride_info, - 1, WeightsInfo(), - point_weights_quant_info) - << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f)); - - return BranchLayer(std::move(sg)); - } -}; -/** Main program for MobileNetQASYMM8 - * - * @param[in] argc Number of arguments - * @param[in] argv Arguments ( [optional] Path to the weights folder, [optional] npy_input, [optional] labels ) - */ -int main(int argc, char **argv) -{ - return utils::run_example<GraphMobileNetQASYMM8Example>(argc, argv); -} |