diff options
| -rw-r--r-- | arm_compute/graph/TypeLoader.h | 25 | ||||
| -rw-r--r-- | src/graph/TypeLoader.cpp | 29 | ||||
| -rw-r--r-- | tests/NEON/Accessor.h | 8 | ||||
| -rw-r--r-- | tests/validate_examples/graph_convolution.cpp | 842 | ||||
| -rw-r--r-- | tests/validation/reference/ConvolutionLayer.cpp | 17 | ||||
| -rw-r--r-- | tests/validation/reference/ConvolutionLayer.h | 4 | ||||
| -rw-r--r-- | utils/GraphUtils.cpp | 5 |
7 files changed, 913 insertions, 17 deletions
diff --git a/arm_compute/graph/TypeLoader.h b/arm_compute/graph/TypeLoader.h index 77f096133d..dcdc1736a7 100644 --- a/arm_compute/graph/TypeLoader.h +++ b/arm_compute/graph/TypeLoader.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -100,6 +100,29 @@ inline ::std::istream &operator>>(::std::istream &stream, Target &target) target = target_from_name(value); return stream; } + +/** Converts a string to a strong types enumeration @ref ConvolutionMethod + * + * @param[in] name String to convert + * + * @return Converted Target enumeration + */ +ConvolutionMethod Convolution_method_from_name(const std::string &name); + +/** Input Stream operator for @ref ConvolutionMethod + * + * @param[in] stream Stream to parse + * @param[out] target Output target + * + * @return Updated stream + */ +inline ::std::istream &operator>>(::std::istream &stream, ConvolutionMethod &target) +{ + std::string value; + stream >> value; + target = Convolution_method_from_name(value); + return stream; +} } // namespace graph } // namespace arm_compute #endif /* __ARM_COMPUTE_GRAPH_TYPE_LOADER_H__ */ diff --git a/src/graph/TypeLoader.cpp b/src/graph/TypeLoader.cpp index e0ba7e2d50..0c1ce25b92 100644 --- a/src/graph/TypeLoader.cpp +++ b/src/graph/TypeLoader.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -17,7 +17,7 @@ * 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 OTHERWNISE, ARISING FROM, + * 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. */ @@ -100,5 +100,30 @@ Target target_from_name(const std::string &name) } #endif /* ARM_COMPUTE_EXCEPTIONS_DISABLED */ } + +ConvolutionMethod Convolution_method_from_name(const std::string &name) +{ + static const std::map<std::string, ConvolutionMethod> methods = + { + { "default", ConvolutionMethod::Default }, + { "direct", ConvolutionMethod::Direct }, + { "gemm", ConvolutionMethod::GEMM }, + { "winograd", ConvolutionMethod::Winograd }, + }; + +#ifndef ARM_COMPUTE_EXCEPTIONS_DISABLED + try + { +#endif /* ARM_COMPUTE_EXCEPTIONS_DISABLED */ + return methods.at(arm_compute::utility::tolower(name)); + +#ifndef ARM_COMPUTE_EXCEPTIONS_DISABLED + } + catch(const std::out_of_range &) + { + throw std::invalid_argument(name); + } +#endif /* ARM_COMPUTE_EXCEPTIONS_DISABLED */ +} } // namespace graph } // namespace arm_compute diff --git a/tests/NEON/Accessor.h b/tests/NEON/Accessor.h index ceb4c473ac..e3a926cffe 100644 --- a/tests/NEON/Accessor.h +++ b/tests/NEON/Accessor.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2018 ARM Limited. + * Copyright (c) 2017-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -39,7 +39,7 @@ public: * * @param[in, out] tensor To be accessed tensor. */ - Accessor(Tensor &tensor); + Accessor(ITensor &tensor); /** Prevent instances of this class from being copy constructed */ Accessor(const Accessor &) = delete; @@ -75,10 +75,10 @@ public: void *operator()(const Coordinates &coord) override; private: - Tensor &_tensor; + ITensor &_tensor; }; -inline Accessor::Accessor(Tensor &tensor) +inline Accessor::Accessor(ITensor &tensor) : _tensor{ tensor } { } diff --git a/tests/validate_examples/graph_convolution.cpp b/tests/validate_examples/graph_convolution.cpp new file mode 100644 index 0000000000..4f5ab0dc08 --- /dev/null +++ b/tests/validate_examples/graph_convolution.cpp @@ -0,0 +1,842 @@ +/* + * 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 <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 +{ +/*Available Padding modes */ +enum class PaddingMode +{ + Valid, + Same, + Manual +}; + +/** Stream Input operator for the PaddingMode type + * + * @param[in] stream Input stream. + * @param[out] Mode Convolution parameters to output + * + * @return input stream. + */ +inline ::std::istream &operator>>(::std::istream &stream, PaddingMode &Mode) +{ + static const std::map<std::string, PaddingMode> modes = + { + { "valid", PaddingMode::Valid }, + { "same", PaddingMode::Same }, + { "manual", PaddingMode::Manual } + }; + std::string value; + stream >> value; + try + { + Mode = modes.at(arm_compute::utility::tolower(value)); + } + catch(const std::out_of_range &) + { + throw std::invalid_argument(value); + } + + return stream; +} + +/** Formatted output of the PaddingMode type + * + * @param[out] os Output stream. + * @param[in] Mode PaddingMode to output + * + * @return Modified output stream. + */ +inline ::std::ostream &operator<<(::std::ostream &os, PaddingMode Mode) +{ + switch(Mode) + { + case PaddingMode::Valid: + os << "Valid"; + break; + case PaddingMode::Same: + os << "Same"; + break; + case PaddingMode::Manual: + os << "Manual"; + break; + default: + throw std::invalid_argument("Unsupported padding mode format"); + } + + return os; +} +/** Structure holding all the input tensor graph parameters */ +struct TensorParams +{ + int width{ 0 }; + int height{ 0 }; + int fm{ 0 }; + int batch{ 0 }; + QuantizationInfo quant_info{ 1.0f, 0 }; + std::string npy{}; + uint64_t range_low{ 0 }; + uint64_t range_high{ 16 }; +}; +/** Structure holding all the verification graph parameters */ +struct VerificationParams +{ + float absolute_tolerance{ -1.f }; + float relative_tolerance{ -1.f }; + float tolerance_number{ -1.f }; +}; + +/** Structure holding all the common graph parameters */ +struct FrameworkParams +{ + bool help{ false }; + int threads{ 0 }; + arm_compute::graph::Target target{ arm_compute::graph::Target::NEON }; +}; + +/** Structure holding all the Convolution layer graph parameters */ +struct ConvolutionParams +{ + arm_compute::DataType data_type{ DataType::F32 }; + arm_compute::DataLayout data_layout{ DataLayout::NCHW }; + arm_compute::graph::ConvolutionMethod convolution_method{ arm_compute::graph::ConvolutionMethod::Default }; + + /** Padding graph parameters */ + int padding_top{ 0 }; + int padding_bottom{ 0 }; + int padding_left{ 0 }; + int padding_right{ 0 }; + int padding_stride_x{ 0 }; + int padding_stride_y{ 0 }; + PaddingMode padding_mode{ PaddingMode::Valid }; + struct + { + struct + { + int X{ 0 }; + int Y{ 0 }; + } stride{}; + PaddingMode mode{ PaddingMode::Valid }; + } padding{}; +}; + +/** Structure holding all the graph Example parameters */ +struct ExampleParams +{ + FrameworkParams common_params{}; + TensorParams input{}; + TensorParams weights{}; + TensorParams bias{}; + TensorParams output{}; + VerificationParams verification{}; + ConvolutionParams convolution{}; +}; + +/** Formatted output of the ConvolutionParams type + * + * @param[out] os Output stream. + * @param[in] common_params Convolution parameters to output + * + * @return Modified output stream. + */ +::std::ostream &operator<<(::std::ostream &os, const ExampleParams &common_params) +{ + os << "Threads : " << common_params.common_params.threads << std::endl; + os << "Target : " << common_params.common_params.target << std::endl; + os << "Data type : " << common_params.convolution.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.convolution_method << std::endl; + return os; +} + +/** 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: + explicit ConvolutionOptions(CommandLineParser &parser) noexcept + : 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)), + help(parser.add_option<ToggleOption>("help")), + threads(parser.add_option<SimpleOption<int>>("threads")), + target(), + data_type(), + padding_mode(), + conv_mode(), + data_layout(), + absolute_tolerance(parser.add_option<SimpleOption<float>>("abs_tolerance", -1.0f)), + relative_tolerance(parser.add_option<SimpleOption<float>>("rel_tolerance", -1.0f)), + tolerance_number(parser.add_option<SimpleOption<float>>("tolerance_num", -1.0f)), + 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<PaddingMode> available_padding_modes + { + PaddingMode::Valid, + PaddingMode::Same + }; + + const std::set<arm_compute::graph::Target> supported_targets + { + Target::NEON, + Target::CL, + Target::GC, + }; + + const std::set<arm_compute::DataType> supported_data_types + { + DataType::F16, + DataType::F32, + DataType::QASYMM8, + }; + + 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<PaddingMode>>("padding_mode", available_padding_modes, PaddingMode::Valid); + target = parser.add_option<EnumOption<Target>>("target", supported_targets, Target::NEON); + data_type = parser.add_option<EnumOption<DataType>>("type", supported_data_types, DataType::F32); + 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); + + target->set_help("Target to execute on"); + data_type->set_help("Data type to use"); + 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"); + data_layout->set_help("Data layout to use"); + absolute_tolerance->set_help("Absolute tolerance used for verification"); + relative_tolerance->set_help("Absolute tolerance used for verification"); + tolerance_number->set_help("Absolute tolerance used for verification"); + 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"); + } + + /** 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() = default; + + 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 */ + ToggleOption *help; /**< show help message */ + SimpleOption<int> *threads; /**< Number of threads option */ + EnumOption<arm_compute::graph::Target> *target; /**< Graph execution target */ + EnumOption<arm_compute::DataType> *data_type; /**< Graph data type */ + EnumOption<PaddingMode> *padding_mode; /**< Padding mode */ + EnumOption<arm_compute::graph::ConvolutionMethod> *conv_mode; /**< Convolution method */ + EnumOption<arm_compute::DataLayout> *data_layout; /**< Graph data layout */ + SimpleOption<float> *absolute_tolerance; /**< Absolute tolerance used in verification */ + SimpleOption<float> *relative_tolerance; /**< Relative tolerance used in verification */ + SimpleOption<float> *tolerance_number; /**< Tolerance number used in verification */ + 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 */ +}; + +/** Consumes the convolution graph options and creates a structure containing any information + * + * @param[in] options Options to consume + * + * @return Convolutionparams structure containing the common graph parameters + */ +ExampleParams consume_covolution_graph_parameters(ConvolutionOptions &options) +{ + ExampleParams common_params; + + common_params.common_params.help = options.help->is_set() ? options.help->value() : false; + common_params.common_params.threads = options.threads->value(); + common_params.common_params.target = options.target->value(); + + common_params.input.width = options.width->value(); + common_params.input.height = options.height->value(); + common_params.input.fm = options.channels->value(); + common_params.input.batch = options.batch->value(); + common_params.input.quant_info.scale = options.scale->value(); + common_params.input.quant_info.offset = options.offset->value(); + common_params.input.npy = options.input_npy->value(); + common_params.input.range_low = options.input_range_low->value(); + common_params.input.range_high = options.input_range_high->value(); + + common_params.weights.width = options.weights_width->value(); + common_params.weights.height = options.weights_height->value(); + common_params.weights.fm = options.OFM->value(); + common_params.weights.npy = options.weights_npy->value(); + common_params.weights.quant_info.scale = options.weights_scale->value(); + common_params.weights.quant_info.offset = options.weights_offset->value(); + common_params.weights.range_low = options.weights_range_low->value(); + common_params.weights.range_high = options.weights_range_high->value(); + + common_params.bias.npy = options.bias_npy->value(); + + common_params.output.quant_info.scale = options.output_scale->value(); + common_params.output.quant_info.offset = options.output_offset->value(); + common_params.output.npy = options.output_npy->value(); + + common_params.convolution.padding_mode = options.padding_mode->value(); + common_params.convolution.padding_top = options.padding_top->value(); + common_params.convolution.padding_bottom = options.padding_bottom->value(); + common_params.convolution.padding_left = options.padding_left->value(); + common_params.convolution.padding_right = options.padding_right->value(); + common_params.convolution.padding_stride_x = options.stride_x->value(); + common_params.convolution.padding_stride_y = options.stride_y->value(); + common_params.convolution.convolution_method = options.conv_mode->value(); + common_params.convolution.data_type = options.data_type->value(); + common_params.convolution.data_layout = options.data_layout->value(); + + common_params.verification.absolute_tolerance = options.absolute_tolerance->value(); + common_params.verification.relative_tolerance = options.relative_tolerance->value(); + common_params.verification.tolerance_number = options.tolerance_number->value(); + + return common_params; +} + +/** Calculate stride information. + * + * Depending on the selected padding mode create the desired PadStrideInfo + * + * @param[in] params Convolution parameters supplied by the user. + * + * @return PadStrideInfo with the correct padding mode. + */ +inline PadStrideInfo calculate_convolution_padding(ExampleParams params) +{ + switch(params.convolution.padding_mode) + { + case PaddingMode::Manual: + { + return PadStrideInfo(params.convolution.padding_stride_x, params.convolution.padding_stride_y, params.convolution.padding_left, params.convolution.padding_right, params.convolution.padding_top, + params.convolution.padding_bottom, DimensionRoundingType::FLOOR); + } + case PaddingMode::Valid: + { + return PadStrideInfo(); + } + case PaddingMode::Same: + { + return arm_compute::calculate_same_pad(TensorShape(params.input.width, params.input.height), TensorShape(params.weights.width, params.weights.height), + PadStrideInfo(params.convolution.padding_stride_x, + params.convolution.padding_stride_y)); + } + default: + ARM_COMPUTE_ERROR("NOT SUPPORTED!"); + } +} + +/** ConvolutionLayer Graph example validation accessor class */ +template <typename D> +class ConvolutionVerifyAccessor final : public graph::ITensorAccessor +{ +public: + using TBias = typename std::conditional<std::is_same<typename std::decay<D>::type, uint8_t>::value, int32_t, D>::type; + + /** Constructor + * + * @param[in] params Convolution parameters + */ + explicit ConvolutionVerifyAccessor(ExampleParams ¶ms) + : _params(std::move(params)) + { + } + + // Inherited methods overriden: + bool access_tensor(ITensor &tensor) override + { + if(_params.output.npy.empty()) + { + const RelativeTolerance<float> rel_tolerance(relative_tolenace(_params.verification.relative_tolerance)); /**< Relative tolerance */ + const AbsoluteTolerance<float> abs_tolerance(absolute_tolerance(_params.verification.absolute_tolerance)); /**< Absolute tolerance */ + const float tolerance_num(tolerance_number(_params.verification.tolerance_number)); /**< Tolerance number */ + + //Create Input tensors + SimpleTensor<D> src{ TensorShape(_params.input.width, _params.input.height, _params.input.fm, _params.input.batch), _params.convolution.data_type, 1, _params.input.quant_info }; + SimpleTensor<D> weights{ TensorShape(_params.weights.width, _params.weights.height, _params.weights.fm), _params.convolution.data_type, 1, _params.weights.quant_info }; + SimpleTensor<TBias> bias{ TensorShape(_params.input.height), _params.convolution.data_type, 1, _params.input.quant_info }; + + //Fill the tenors with random values + fill_tensor<D>(src, 0, static_cast<D>(_params.input.range_low), static_cast<D>(_params.input.range_high)); + fill_tensor<D>(weights, 1, static_cast<D>(_params.weights.range_low), static_cast<D>(_params.weights.range_high)); + fill_tensor<TBias>(bias, 2, static_cast<TBias>(_params.input.range_low), static_cast<TBias>(_params.input.range_high)); + + // Calculate padding information + const PadStrideInfo padding_info = calculate_convolution_padding(_params); + + //Calculate reference + SimpleTensor<D> output = reference::convolution_layer<D>(src, weights, bias, permute_shape(tensor.info()->tensor_shape(), _params.convolution.data_layout, DataLayout::NCHW), padding_info, Size2D(1, + 1), + 1, + _params.output.quant_info); + + arm_compute::test::validation::validate(Accessor(tensor), output, rel_tolerance, tolerance_num, abs_tolerance); + } + else + { + //The user provided a reference file use an npy accessor to validate + NumPyAccessor(_params.output.npy, tensor.info()->tensor_shape(), tensor.info()->data_type()).access_tensor(tensor); + } + return false; + } + +private: + /** Fill tensor with Random values. + * + * Validate the given tensor against the reference result. + * + * @param[out] tensor The tensor we want to file + * @param[in] seed seed for the randomization function + * @param[in] low lower bound for random values + * @param[in] high upper bound for random values + * + * @return None. + */ + template <typename T> + void fill_tensor(arm_compute::test::SimpleTensor<T> &tensor, std::random_device::result_type seed, T low, T high) + { + std::mt19937 gen(seed); + switch(tensor.data_type()) + { + case arm_compute::DataType::QASYMM8: + { + uint8_t qasymm8_low = tensor.quantization_info().quantize(low, RoundingPolicy::TO_NEAREST_UP); + uint8_t qasymm8_high = tensor.quantization_info().quantize(high, RoundingPolicy::TO_NEAREST_UP); + + std::uniform_int_distribution<uint8_t> distribution(qasymm8_low, qasymm8_high); + + for(int i = 0; i < tensor.num_elements(); ++i) + { + tensor[i] = tensor.quantization_info().quantize(distribution(gen), RoundingPolicy::TO_NEAREST_UP); + } + + break; + } + case arm_compute::DataType::S32: + { + std::uniform_int_distribution<int32_t> distribution(static_cast<int32_t>(low), static_cast<uint32_t>(high)); + + for(int i = 0; i < tensor.num_elements(); ++i) + { + tensor[i] = distribution(gen); + } + + break; + } + + case arm_compute::DataType::F16: + { + std::uniform_real_distribution<float> distribution(static_cast<half>(low), static_cast<half>(high)); + + for(int i = 0; i < tensor.num_elements(); ++i) + { + tensor[i] = static_cast<half>(distribution(gen)); + } + break; + } + case arm_compute::DataType::F32: + { + std::uniform_real_distribution<float> distribution(static_cast<float>(low), static_cast<float>(high)); + + for(int i = 0; i < tensor.num_elements(); ++i) + { + tensor[i] = distribution(gen); + } + + break; + } + default: + ARM_COMPUTE_ERROR("NOT SUPPORTED!"); + } + } + /** Select relative tolerance. + * + * Select relative tolerance if not supplied by user. + * + * @param[in] user_value supplied relative tolerance. -1 designates no user input + * + * @return Appropriate relative tolerance. + */ + float relative_tolenace(float user_value) + { + 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(user_value == -1) + { + if(_params.convolution.convolution_method == arm_compute::graph::ConvolutionMethod::Winograd + && _params.convolution.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.convolution.data_type); + } + } + + return user_value; + } + + /** Select absolute tolerance. + * + * Select absolute tolerance if not supplied by user. + * + * @param[in] user_value supplied absolute tolerance. -1 designates no user input + * + * @return Appropriate absolute tolerance. + */ + float absolute_tolerance(float user_value) + { + 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 } + } + } + }; + + if(user_value == -1) + { + return absolute_tolerance.at(_params.common_params.target).at(_params.convolution.data_type); + } + return user_value; + } + /** Select tolerance number. + * + * Select tolerance number if not supplied by user. + * + * @param[in] user_value supplied tolerance number. -1 designates no user input + * + * @return Appropriate tolerance number. + */ + float tolerance_number(float user_value) + { + 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 } + } + } + }; + + if(user_value == -1) + { + return absolute_tolerance.at(_params.common_params.target).at(_params.convolution.data_type); + } + return user_value; + } + + ExampleParams _params; +}; + +/** Generates appropriate convolution verify accessor + * + * @param[in] params User supplied parameters for convolution. + * + * @return A convolution verify accessor for the requested datatype. + */ +inline std::unique_ptr<graph::ITensorAccessor> get_convolution_verify_accessor(ExampleParams params) +{ + switch(params.convolution.data_type) + { + case DataType::QASYMM8: + { + return arm_compute::support::cpp14::make_unique<ConvolutionVerifyAccessor<uint8_t>>( + params); + } + case DataType::F16: + { + return arm_compute::support::cpp14::make_unique<ConvolutionVerifyAccessor<half>>( + params); + } + case DataType::F32: + { + return arm_compute::support::cpp14::make_unique<ConvolutionVerifyAccessor<float>>( + params); + } + default: + ARM_COMPUTE_ERROR("NOT SUPPORTED!"); + } +} +/** Generates appropriate accessor according to the specified graph parameters + * + * @param[in] graph_parameters Graph parameters + * @param[in] lower Lower random values bound + * @param[in] upper Upper random values bound + * @param[in] seed Random generator seed + * + * @return An appropriate tensor accessor + */ +inline std::unique_ptr<graph::ITensorAccessor> get_accessor(const TensorParams &tensor, PixelValue lower, PixelValue upper, const std::random_device::result_type seed = 0) +{ + if(!tensor.npy.empty()) + { + return arm_compute::support::cpp14::make_unique<NumPyBinLoader>(tensor.npy); + } + else + { + return arm_compute::support::cpp14::make_unique<RandomAccessor>(lower, upper, seed); + } +} +} // namespace + +class GraphConvolutionValidateExample final : public ValidateExample +{ +public: + GraphConvolutionValidateExample() + : graph(0, "Convolution Graph example") + { + } + bool do_setup(int argc, char **argv) override + { + CommandLineParser parser; + + ConvolutionOptions Options(parser); + + parser.parse(argc, argv); + + ExampleParams params = consume_covolution_graph_parameters(Options); + + if(params.common_params.help) + { + parser.print_help(argv[0]); + return false; + } + + std::cout << params << std::endl; + + // Calculate padding information + const PadStrideInfo padding_info = calculate_convolution_padding(params); + + // Create input descriptor + const TensorShape input_shape = permute_shape(TensorShape(params.input.width, params.input.height, params.input.fm, params.input.batch), DataLayout::NCHW, params.convolution.data_layout); + TensorDescriptor input_descriptor = TensorDescriptor(input_shape, params.convolution.data_type, params.input.quant_info, params.convolution.data_layout); + + const PixelValue lower = PixelValue(params.input.range_low, params.convolution.data_type, params.input.quant_info); + const PixelValue upper = PixelValue(params.input.range_high, params.convolution.data_type, params.input.quant_info); + + const PixelValue weights_lower = PixelValue(params.weights.range_low, params.convolution.data_type, params.weights.quant_info); + const PixelValue weights_upper = PixelValue(params.weights.range_high, params.convolution.data_type, params.weights.quant_info); + + graph << params.common_params.target + << params.convolution.convolution_method + << InputLayer(input_descriptor, get_accessor(params.input, lower, upper, 0)) + << 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) + << OutputLayer(get_convolution_verify_accessor(params)); + + GraphConfig config; + config.num_threads = params.common_params.threads; + + graph.finalize(params.common_params.target, config); + + return true; + } + + void do_run() override + { + graph.run(); + } + + void do_teardown() override + { + } + +private: + Stream graph; +}; + +/** 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); +} diff --git a/tests/validation/reference/ConvolutionLayer.cpp b/tests/validation/reference/ConvolutionLayer.cpp index f41a6fc8c4..69090117fe 100644 --- a/tests/validation/reference/ConvolutionLayer.cpp +++ b/tests/validation/reference/ConvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2018 ARM Limited. + * Copyright (c) 2017-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -111,10 +111,15 @@ SimpleTensor<T> convolution_layer_nchw(const SimpleTensor<T> &src, const SimpleT } template <typename T, typename TB> SimpleTensor<T> convolution_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &bias, const TensorShape &output_shape, const PadStrideInfo &info, - const Size2D &dilation, unsigned int num_groups) + const Size2D &dilation, unsigned int num_groups, QuantizationInfo out_quant_info) { + // if no explicit quantization has been set you the same as src + if(out_quant_info == QuantizationInfo()) + { + out_quant_info = src.quantization_info(); + } // Create reference - SimpleTensor<T> dst{ output_shape, src.data_type(), 1, src.quantization_info() }; + SimpleTensor<T> dst{ output_shape, src.data_type(), 1, out_quant_info }; if(src.data_layout() == DataLayout::NHWC) { @@ -131,11 +136,11 @@ SimpleTensor<T> convolution_layer(const SimpleTensor<T> &src, const SimpleTensor } template SimpleTensor<float> convolution_layer(const SimpleTensor<float> &src, const SimpleTensor<float> &weights, const SimpleTensor<float> &bias, const TensorShape &output_shape, - const PadStrideInfo &info, const Size2D &dilation, unsigned int num_groups); + const PadStrideInfo &info, const Size2D &dilation, unsigned int num_groups, QuantizationInfo out_quant_info); template SimpleTensor<half> convolution_layer(const SimpleTensor<half> &src, const SimpleTensor<half> &weights, const SimpleTensor<half> &bias, const TensorShape &output_shape, - const PadStrideInfo &info, const Size2D &dilation, unsigned int num_groups); + const PadStrideInfo &info, const Size2D &dilation, unsigned int num_groups, QuantizationInfo out_quant_info); template SimpleTensor<uint8_t> convolution_layer(const SimpleTensor<uint8_t> &src, const SimpleTensor<uint8_t> &weights, const SimpleTensor<int32_t> &bias, const TensorShape &output_shape, - const PadStrideInfo &info, const Size2D &dilation, unsigned int num_groups); + const PadStrideInfo &info, const Size2D &dilation, unsigned int num_groups, QuantizationInfo out_quant_info); } // namespace reference } // namespace validation } // namespace test diff --git a/tests/validation/reference/ConvolutionLayer.h b/tests/validation/reference/ConvolutionLayer.h index ccce53a209..c51a9b3ad7 100644 --- a/tests/validation/reference/ConvolutionLayer.h +++ b/tests/validation/reference/ConvolutionLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2018 ARM Limited. + * Copyright (c) 2017-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -37,7 +37,7 @@ namespace reference { template <typename T, typename TB> SimpleTensor<T> convolution_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &bias, const TensorShape &output_shape, const PadStrideInfo &info, - const Size2D &dilation = Size2D(1U, 1U), unsigned int num_groups = 1); + const Size2D &dilation = Size2D(1U, 1U), unsigned int num_groups = 1, QuantizationInfo out_quant_info = QuantizationInfo()); } // namespace reference } // namespace validation } // namespace test diff --git a/utils/GraphUtils.cpp b/utils/GraphUtils.cpp index ab2c753eac..b714c55136 100644 --- a/utils/GraphUtils.cpp +++ b/utils/GraphUtils.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2018 ARM Limited. + * Copyright (c) 2017-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -604,6 +604,7 @@ bool RandomAccessor::access_tensor(ITensor &tensor) { switch(tensor.info()->data_type()) { + case DataType::QASYMM8: case DataType::U8: { std::uniform_int_distribution<uint8_t> distribution_u8(_lower.get<uint8_t>(), _upper.get<uint8_t>()); @@ -654,7 +655,7 @@ bool RandomAccessor::access_tensor(ITensor &tensor) } case DataType::F16: { - std::uniform_real_distribution<float> distribution_f16(_lower.get<float>(), _upper.get<float>()); + std::uniform_real_distribution<float> distribution_f16(_lower.get<half>(), _upper.get<half>()); fill<half>(tensor, distribution_f16); break; } |