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Diffstat (limited to 'tests/validate_examples/graph_convolution.cpp')
| -rw-r--r-- | tests/validate_examples/graph_convolution.cpp | 398 |
1 files changed, 0 insertions, 398 deletions
diff --git a/tests/validate_examples/graph_convolution.cpp b/tests/validate_examples/graph_convolution.cpp deleted file mode 100644 index 1ab6691e57..0000000000 --- a/tests/validate_examples/graph_convolution.cpp +++ /dev/null @@ -1,398 +0,0 @@ -/* - * 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); -} |