| /* |
| * 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 "tests/NEON/Accessor.h" |
| #include "tests/validation/Validation.h" |
| #include "tests/validation/reference/ConvolutionLayer.h" |
| #include "tests/validation/reference/Permute.h" |
| |
| #include "utils/CommonGraphOptions.h" |
| #include "utils/GraphUtils.h" |
| #include "utils/Utils.h" |
| |
| #include "ValidateExample.h" |
| #include "graph_validate_utils.h" |
| |
| #include <utility> |
| |
| using namespace arm_compute::utils; |
| using namespace arm_compute::graph::frontend; |
| using namespace arm_compute::graph_utils; |
| using namespace arm_compute::graph; |
| using namespace arm_compute; |
| using namespace arm_compute::test; |
| using namespace arm_compute::test::validation; |
| |
| namespace |
| { |
| /** Convolution command line options used to configure the graph examples |
| * |
| * (Similar to common options) |
| * The options in this object get populated when "parse()" is called on the parser used to construct it. |
| * The expected workflow is: |
| * |
| * CommandLineParser parser; |
| * CommonOptions options( parser ); |
| * parser.parse(argc, argv); |
| */ |
| class ConvolutionOptions final : public CommonGraphValidateOptions |
| { |
| public: |
| explicit ConvolutionOptions(CommandLineParser &parser) noexcept |
| : CommonGraphValidateOptions(parser), |
| width(parser.add_option<SimpleOption<int>>("width", 9)), |
| height(parser.add_option<SimpleOption<int>>("height", 9)), |
| channels(parser.add_option<SimpleOption<int>>("channels", 1)), |
| batch(parser.add_option<SimpleOption<int>>("batch", 1)), |
| weights_width(parser.add_option<SimpleOption<int>>("weights_width", 3)), |
| weights_height(parser.add_option<SimpleOption<int>>("weights_height", 3)), |
| OFM(parser.add_option<SimpleOption<int>>("OFM", 1)), |
| padding_top(parser.add_option<SimpleOption<int>>("padding_top", 0)), |
| padding_left(parser.add_option<SimpleOption<int>>("padding_left", 0)), |
| padding_bottom(parser.add_option<SimpleOption<int>>("padding_bottom", 0)), |
| padding_right(parser.add_option<SimpleOption<int>>("padding_right", 0)), |
| stride_x(parser.add_option<SimpleOption<int>>("stride_x", 1)), |
| stride_y(parser.add_option<SimpleOption<int>>("stride_y", 1)), |
| padding_mode(), |
| conv_mode(), |
| data_layout(), |
| scale(parser.add_option<SimpleOption<float>>("scale", 1.0f)), |
| offset(parser.add_option<SimpleOption<int>>("offset", 0)), |
| weights_scale(parser.add_option<SimpleOption<float>>("weights_scale", 1.0f)), |
| weights_offset(parser.add_option<SimpleOption<int>>("weights_offset", 0)), |
| output_scale(parser.add_option<SimpleOption<float>>("output_scale", 1.0f)), |
| output_offset(parser.add_option<SimpleOption<int>>("output_offset", 0)), |
| input_range_low(parser.add_option<SimpleOption<uint64_t>>("input_range_low")), |
| input_range_high(parser.add_option<SimpleOption<uint64_t>>("input_range_high")), |
| weights_range_low(parser.add_option<SimpleOption<uint64_t>>("weights_range_low")), |
| weights_range_high(parser.add_option<SimpleOption<uint64_t>>("weights_range_high")), |
| input_npy(parser.add_option<SimpleOption<std::string>>("input_image")), |
| output_npy(parser.add_option<SimpleOption<std::string>>("reference_image")), |
| weights_npy(parser.add_option<SimpleOption<std::string>>("weights_npy")), |
| bias_npy(parser.add_option<SimpleOption<std::string>>("bias_image")) |
| { |
| const std::set<ConvolutionPaddingMode> available_padding_modes |
| { |
| ConvolutionPaddingMode::Valid, |
| ConvolutionPaddingMode::Same |
| }; |
| |
| const std::set<arm_compute::graph::ConvolutionMethod> supported_convolution_methods |
| { |
| arm_compute::graph::ConvolutionMethod::Default, |
| arm_compute::graph::ConvolutionMethod::GEMM, |
| arm_compute::graph::ConvolutionMethod::Winograd, |
| arm_compute::graph::ConvolutionMethod::Direct |
| }; |
| |
| const std::set<DataLayout> supported_data_layouts |
| { |
| DataLayout::NHWC, |
| DataLayout::NCHW, |
| }; |
| |
| padding_mode = parser.add_option<EnumOption<ConvolutionPaddingMode>>("padding_mode", available_padding_modes, ConvolutionPaddingMode::Valid); |
| conv_mode = parser.add_option<EnumOption<arm_compute::graph::ConvolutionMethod>>("convolution_method", supported_convolution_methods, arm_compute::graph::ConvolutionMethod::Default); |
| data_layout = parser.add_option<EnumOption<DataLayout>>("layout", supported_data_layouts, DataLayout::NHWC); |
| |
| padding_mode->set_help("Set padding mode"); |
| help->set_help("Show this help message"); |
| width->set_help("Set Input dimension width"); |
| height->set_help("Set Input dimension height"); |
| channels->set_help("Set Input dimension channels"); |
| batch->set_help("Set Input dimension batch"); |
| weights_width->set_help("Set weights_dimensions width"); |
| weights_height->set_help("Set weights_dimensions height"); |
| OFM->set_help("Set OFM"); |
| padding_top->set_help("Set padding top"); |
| padding_bottom->set_help("Set padding bottom"); |
| padding_left->set_help("Set padding left"); |
| padding_right->set_help("Set padding right"); |
| stride_x->set_help("Set padding stride x"); |
| stride_y->set_help("Set padding stride y"); |
| conv_mode->set_help("Set convolution method"); |
| scale->set_help("Quantization scale from QASYMM8"); |
| offset->set_help("Quantization offset from QASYMM8"); |
| weights_scale->set_help("Quantization scale from QASYMM8"); |
| weights_offset->set_help("Quantization offset from QASYMM8"); |
| output_scale->set_help("Quantization scale from QASYMM8"); |
| output_offset->set_help("Quantization offset from QASYMM8"); |
| input_npy->set_help("Use input .npy instead"); |
| output_npy->set_help("Use .npy as a reference"); |
| input_range_low->set_help("Lower bound for input randomization range"); |
| input_range_high->set_help("Lower bound for input randomization range"); |
| weights_range_low->set_help("Lower bound for input randomization range"); |
| weights_range_high->set_help("Lower bound for input randomization range"); |
| } |
| |
| /** Fill out the supplied parameters with user supplied parameters |
| * |
| * @param[out] os Output stream. |
| * @param[in] common_params Example parameters to output |
| * |
| * @return None. |
| */ |
| void consume_parameters(ExampleParams &common_params) |
| { |
| common_params.input.width = width->value(); |
| common_params.input.height = height->value(); |
| common_params.input.fm = channels->value(); |
| common_params.input.batch = batch->value(); |
| common_params.input.quant_info = QuantizationInfo(scale->value(), offset->value()); |
| common_params.input.npy = input_npy->value(); |
| common_params.input.range_low = input_range_low->value(); |
| common_params.input.range_high = input_range_high->value(); |
| |
| common_params.weights.width = weights_width->value(); |
| common_params.weights.height = weights_height->value(); |
| common_params.weights.fm = OFM->value(); |
| common_params.weights.npy = weights_npy->value(); |
| common_params.weights.quant_info = QuantizationInfo(weights_scale->value(), weights_offset->value()); |
| common_params.weights.range_low = weights_range_low->value(); |
| common_params.weights.range_high = weights_range_high->value(); |
| |
| common_params.bias.npy = bias_npy->value(); |
| |
| common_params.output.quant_info = QuantizationInfo(output_scale->value(), output_offset->value()); |
| common_params.output.npy = output_npy->value(); |
| |
| common_params.convolution.padding_mode = padding_mode->value(); |
| common_params.convolution.padding_top = padding_top->value(); |
| common_params.convolution.padding_bottom = padding_bottom->value(); |
| common_params.convolution.padding_left = padding_left->value(); |
| common_params.convolution.padding_right = padding_right->value(); |
| common_params.convolution.padding_stride_x = stride_x->value(); |
| common_params.convolution.padding_stride_y = stride_y->value(); |
| |
| common_params.data_type = data_type->value(); |
| common_params.data_layout = data_layout->value(); |
| common_params.convolution_method = conv_mode->value(); |
| } |
| |
| void print_parameters(::std::ostream &os, const ExampleParams &common_params) override |
| { |
| os << "Threads : " << common_params.common_params.threads << std::endl; |
| os << "Target : " << common_params.common_params.target << std::endl; |
| os << "Data type : " << common_params.data_type << std::endl; |
| os << "Input dimensions(X,Y, Channels, Batch) : (" << common_params.input.width << "," << common_params.input.height << "," << common_params.input.fm << "," << common_params.input.batch << ")" |
| << std::endl; |
| os << "Weight dimensions(X,Y, Channels(same as input), OFM) : (" << common_params.weights.width << "," << common_params.weights.height << "," << common_params.input.fm << "," << |
| common_params.weights.fm << ")" << std::endl; |
| os << "Padding(top, bottom, left, right) (stride x, stride y) : (" << common_params.convolution.padding_top << "," << common_params.convolution.padding_bottom << "," << |
| common_params.convolution.padding_left << "," << common_params.convolution.padding_right << ") (" << common_params.convolution.padding_stride_x << "," << common_params.convolution.padding_stride_y << |
| ")" << std::endl; |
| os << "Padding Mode: " << common_params.convolution.padding_mode << std::endl; |
| os << "Convolution Method: " << common_params.convolution_method << std::endl; |
| } |
| |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| ConvolutionOptions(const ConvolutionOptions &) = delete; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| ConvolutionOptions &operator=(const ConvolutionOptions &) = delete; |
| /** Allow instances of this class to be moved */ |
| ConvolutionOptions(ConvolutionOptions &&) noexcept(true) = default; |
| /** Allow instances of this class to be moved */ |
| ConvolutionOptions &operator=(ConvolutionOptions &&) noexcept(true) = default; |
| /** Default destructor */ |
| ~ConvolutionOptions() override = default; |
| |
| private: |
| SimpleOption<int> *width; /**< Input width */ |
| SimpleOption<int> *height; /**< Input height */ |
| SimpleOption<int> *channels; /**< Input channels */ |
| SimpleOption<int> *batch; /**< Input batch */ |
| SimpleOption<int> *weights_width; /**< weights width */ |
| SimpleOption<int> *weights_height; /**< weights height */ |
| SimpleOption<int> *OFM; /**< Output Feature Map */ |
| SimpleOption<int> *padding_top; /**< Padding top */ |
| SimpleOption<int> *padding_left; /**< Padding left */ |
| SimpleOption<int> *padding_bottom; /**< Padding bottom */ |
| SimpleOption<int> *padding_right; /**< Padding right */ |
| SimpleOption<int> *stride_x; /**< Padding stride x */ |
| SimpleOption<int> *stride_y; /**< Padding stride y */ |
| EnumOption<ConvolutionPaddingMode> *padding_mode; /**< Padding mode */ |
| EnumOption<arm_compute::graph::ConvolutionMethod> *conv_mode; /**< Convolution method */ |
| EnumOption<arm_compute::DataLayout> *data_layout; /**< Graph data layout */ |
| SimpleOption<float> *scale; /**< Input Quantization scale from QASYMM8 */ |
| SimpleOption<int> *offset; /**< Input Quantization offset from QASYMM8 */ |
| SimpleOption<float> *weights_scale; /**< Weights Quantization scale from QASYMM8 */ |
| SimpleOption<int> *weights_offset; /**< Weights Quantization offset from QASYMM8 */ |
| SimpleOption<float> *output_scale; /**< Output Quantization scale from QASYMM8 */ |
| SimpleOption<int> *output_offset; /**< Output Quantization offset from QASYMM8 */ |
| SimpleOption<uint64_t> *input_range_low; /**< Lower bound for input randomization range */ |
| SimpleOption<uint64_t> *input_range_high; /**< Upper bound for input randomization range */ |
| SimpleOption<uint64_t> *weights_range_low; /**< Lower bound for weights randomization range */ |
| SimpleOption<uint64_t> *weights_range_high; /**< Upper bound for weights randomization range */ |
| |
| SimpleOption<std::string> *input_npy; /**< Use input .npy image */ |
| SimpleOption<std::string> *output_npy; /**< Use output .npy image to verify*/ |
| SimpleOption<std::string> *weights_npy; /**< Use weights .npy image */ |
| SimpleOption<std::string> *bias_npy; /**< Use bias .npy image */ |
| }; |
| |
| /** ConvolutionLayer Graph example validation accessor class */ |
| template <typename D> |
| class ConvolutionVerifyAccessor final : public VerifyAccessor<D> |
| { |
| using BaseClassType = VerifyAccessor<D>; |
| using BaseClassType::BaseClassType; |
| using BaseClassType::_params; |
| using TBias = typename std::conditional<std::is_same<typename std::decay<D>::type, uint8_t>::value, int32_t, D>::type; |
| |
| SimpleTensor<D> reference(SimpleTensor<D> &src, SimpleTensor<D> &weights, SimpleTensor<TBias> &bias, const TensorShape &output_shape) override |
| { |
| // Calculate padding information |
| const PadStrideInfo padding_info = calculate_convolution_padding(_params); |
| |
| //Calculate reference |
| return reference::convolution_layer<D>(src, weights, bias, output_shape, padding_info, Size2D(1, 1), |
| 1, _params.output.quant_info); |
| } |
| |
| float relative_tolerance() override |
| { |
| const std::map<arm_compute::graph::Target, const std::map<DataType, float>> relative_tolerance |
| { |
| { |
| arm_compute::graph::Target::CL, |
| { { DataType::F16, 0.2f }, |
| { DataType::F32, 0.5f }, |
| { DataType::QASYMM8, 1.0f } |
| } |
| }, |
| { |
| arm_compute::graph::Target::NEON, |
| { { DataType::F16, 0.2f }, |
| { DataType::F32, 0.01f }, |
| { DataType::QASYMM8, 0.0f } |
| } |
| } |
| }; |
| |
| if(_params.convolution_method == arm_compute::graph::ConvolutionMethod::Winograd |
| && _params.data_type == DataType::F32 |
| && _params.common_params.target == arm_compute::graph::Target::NEON) |
| { |
| return 0.05f; |
| } |
| else |
| { |
| return relative_tolerance.at(_params.common_params.target).at(_params.data_type); |
| } |
| } |
| |
| float absolute_tolerance() override |
| { |
| const std::map<Target, const std::map<DataType, float>> absolute_tolerance |
| { |
| { |
| Target::CL, |
| { { DataType::F16, 0.0f }, |
| { DataType::F32, 0.0001f }, |
| { DataType::QASYMM8, 0.0f } |
| } |
| }, |
| { |
| Target::NEON, |
| { { DataType::F16, 0.2f }, |
| { DataType::F32, 0.002f }, |
| { DataType::QASYMM8, 0.0f } |
| } |
| } |
| }; |
| |
| return absolute_tolerance.at(_params.common_params.target).at(_params.data_type); |
| } |
| |
| float tolerance_number() override |
| { |
| const std::map<Target, const std::map<DataType, float>> absolute_tolerance |
| { |
| { |
| Target::CL, |
| { { DataType::F16, 0.07f }, |
| { DataType::F32, 0.07f }, |
| { DataType::QASYMM8, 0.0f } |
| } |
| }, |
| { |
| Target::NEON, |
| { { DataType::F16, 0.07f }, |
| { DataType::F32, 0.0f }, |
| { DataType::QASYMM8, 0.0f } |
| } |
| } |
| }; |
| |
| return absolute_tolerance.at(_params.common_params.target).at(_params.data_type); |
| } |
| }; |
| |
| } // namespace |
| |
| class GraphConvolutionValidateExample final : public GraphValidateExample<ConvolutionLayer, ConvolutionOptions, ConvolutionVerifyAccessor> |
| { |
| using GraphValidateExample::graph; |
| |
| public: |
| GraphConvolutionValidateExample() |
| : GraphValidateExample("Convolution Graph example") |
| { |
| } |
| |
| ConvolutionLayer GraphFunctionLayer(ExampleParams ¶ms) override |
| { |
| const PixelValue lower = PixelValue(params.input.range_low, params.data_type, params.input.quant_info); |
| const PixelValue upper = PixelValue(params.input.range_high, params.data_type, params.input.quant_info); |
| |
| const PixelValue weights_lower = PixelValue(params.weights.range_low, params.data_type, params.weights.quant_info); |
| const PixelValue weights_upper = PixelValue(params.weights.range_high, params.data_type, params.weights.quant_info); |
| |
| // Calculate padding information |
| const PadStrideInfo padding_info = calculate_convolution_padding(params); |
| |
| return ConvolutionLayer(params.weights.width, params.weights.height, params.weights.fm, |
| get_accessor(params.weights, weights_lower, weights_upper, 1), |
| get_accessor(params.bias, lower, upper, 2), |
| padding_info, 1, params.weights.quant_info, params.output.quant_info); |
| } |
| }; |
| |
| /** Main program for Graph Convolution test |
| * |
| * @param[in] argc Number of arguments |
| * @param[in] argv Arguments ( Input dimensions [width, height, channels, batch] |
| * Weights dimensions [width, height, OFM] |
| * Padding [top,bottom,left,right, Stride x, Stride y, mode [Valid / Same / Manual] ) |
| * Convolution Method[ Auto/GEMM/Winograd/Direct] |
| * Verification[tolerance_number,absolute_tolerance,relative_tolerance] ) |
| * |
| */ |
| int main(int argc, char **argv) |
| { |
| return arm_compute::utils::run_example<GraphConvolutionValidateExample>(argc, argv); |
| } |