From 32af1f8ed8466647abb4f0532c70f72530a1a9ca Mon Sep 17 00:00:00 2001 From: John Richardson Date: Tue, 5 Jun 2018 12:47:20 +0100 Subject: COMPMID-761: Add CL/NEON Convolution benchmark tests Change-Id: I684baff3bfdff2244e04facd2d85d84609b7caff Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/134769 Reviewed-by: Anthony Barbier Tested-by: Jenkins --- tests/Utils.h | 55 +++++++ tests/benchmark/CL/Convolution.cpp | 206 +++++++++++++++++++++++++ tests/benchmark/NEON/Convolution.cpp | 206 +++++++++++++++++++++++++ tests/benchmark/fixtures/ConvolutionFixture.h | 173 +++++++++++++++++++++ tests/validation/fixtures/ConvolutionFixture.h | 43 +----- 5 files changed, 642 insertions(+), 41 deletions(-) create mode 100644 tests/benchmark/CL/Convolution.cpp create mode 100644 tests/benchmark/NEON/Convolution.cpp create mode 100644 tests/benchmark/fixtures/ConvolutionFixture.h diff --git a/tests/Utils.h b/tests/Utils.h index d0eebb1204..278af414db 100644 --- a/tests/Utils.h +++ b/tests/Utils.h @@ -596,6 +596,61 @@ inline T create_pyramid(const PyramidInfo &pyramid_info) return pyramid; } +/** Initialize a convolution matrix. + * + * @param[in, out] conv The input convolution matrix. + * @param[in] width The width of the convolution matrix. + * @param[in] height The height of the convolution matrix. + * @param[in] seed The random seed to be used. + */ +inline void init_conv(int16_t *conv, unsigned int width, unsigned int height, std::random_device::result_type seed) +{ + std::mt19937 gen(seed); + std::uniform_int_distribution distribution_int16(-32768, 32767); + + for(unsigned int i = 0; i < width * height; ++i) + { + conv[i] = distribution_int16(gen); + } +} + +/** Initialize a separable convolution matrix. + * + * @param[in, out] conv The input convolution matrix. + * @param[in] width The width of the convolution matrix. + * @param[in] height The height of the convolution matrix. + * @param[in] seed The random seed to be used. + */ +inline void init_separable_conv(int16_t *conv, unsigned int width, unsigned int height, std::random_device::result_type seed) +{ + std::mt19937 gen(seed); + // Set it between -128 and 127 to ensure the matrix does not overflow + std::uniform_int_distribution distribution_int16(-128, 127); + + int16_t conv_row[width]; + int16_t conv_col[height]; + + conv_row[0] = conv_col[0] = 1; + for(unsigned int i = 1; i < width; ++i) + { + conv_row[i] = distribution_int16(gen); + } + + for(unsigned int i = 1; i < height; ++i) + { + conv_col[i] = distribution_int16(gen); + } + + // Multiply two matrices + for(unsigned int i = 0; i < width; ++i) + { + for(unsigned int j = 0; j < height; ++j) + { + conv[i * width + j] = conv_col[i] * conv_row[j]; + } + } +} + /** Create a vector of random ROIs. * * @param[in] shape The shape of the input tensor. diff --git a/tests/benchmark/CL/Convolution.cpp b/tests/benchmark/CL/Convolution.cpp new file mode 100644 index 0000000000..04622aa363 --- /dev/null +++ b/tests/benchmark/CL/Convolution.cpp @@ -0,0 +1,206 @@ +/* + * Copyright (c) 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/core/Types.h" +#include "arm_compute/runtime/CL/CLTensor.h" +#include "arm_compute/runtime/CL/functions/CLConvolution.h" +#include "tests/CL/CLAccessor.h" +#include "tests/benchmark/fixtures/ConvolutionFixture.h" +#include "tests/datasets/BorderModeDataset.h" +#include "tests/datasets/ShapeDatasets.h" +#include "tests/framework/Macros.h" +#include "tests/framework/datasets/Datasets.h" +#include "utils/TypePrinter.h" + +namespace arm_compute +{ +namespace test +{ +namespace benchmark +{ +namespace +{ +// *INDENT-OFF* +// clang-format off + +#define CONVOLUTION_SQUARE_DATA_TEST_CASE(TEST_NAME, MODE, SHAPES, DT, FILTER_SIZE) \ + REGISTER_FIXTURE_DATA_TEST_CASE(TEST_NAME, CLConvolutionFixture, framework::DatasetMode::MODE, \ + combine(combine(combine( \ + datasets::SHAPES, \ + framework::dataset::make("DataType", DataType::DT)), \ + datasets::BorderModes()), \ + framework::dataset::make("FilterSize", { FILTER_SIZE }))); + +#define CONVOLUTION_RECTANGLE_DATA_TEST_CASE(TEST_NAME, MODE, SHAPES, DT) \ + REGISTER_FIXTURE_DATA_TEST_CASE(TEST_NAME, CLConvolutionFixture, framework::DatasetMode::MODE, \ + combine(combine(combine(combine( \ + datasets::SHAPES, \ + framework::dataset::make("DataType", DataType::DT)), \ + datasets::BorderModes()), \ + framework::dataset::make("FilterSize", { 3, 5, 7, 9 })), \ + framework::dataset::make("FilterSize", { 3, 5, 7, 9 }))); + +#define CONVOLUTION_SEPARABLE_DATA_TEST_CASE(TEST_NAME, MODE, SHAPES, DT, FILTER_SIZE) \ + CONVOLUTION_SQUARE_DATA_TEST_CASE(TEST_NAME, MODE, SHAPES, DT, FILTER_SIZE) + +// clang-format on +// *INDENT-ON* + +} // namespace + +TEST_SUITE(CL) +TEST_SUITE(CustomConvolution) + +TEST_SUITE(Square3x3) + +using CLConvolutionFixture = ConvolutionSquareFixture; + +TEST_SUITE(U8) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), U8, 3) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), U8, 3) +TEST_SUITE_END() // U8 + +TEST_SUITE(S16) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), S16, 3) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), S16, 3) +TEST_SUITE_END() // S16 + +TEST_SUITE_END() // Square3x3 + +TEST_SUITE(Square5x5) + +using CLConvolutionFixture = ConvolutionSquareFixture; + +TEST_SUITE(U8) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), U8, 5) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), U8, 5) +TEST_SUITE_END() // U8 + +TEST_SUITE(S16) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), S16, 5) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), S16, 5) +TEST_SUITE_END() // S16 + +TEST_SUITE_END() // Square5x5 + +TEST_SUITE(Square7x7) + +using CLConvolutionFixture = ConvolutionSquareFixture; + +TEST_SUITE(U8) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), U8, 7) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), U8, 7) +TEST_SUITE_END() // U8 + +TEST_SUITE(S16) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), S16, 7) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), S16, 7) +TEST_SUITE_END() // S16 + +TEST_SUITE_END() // Square7x7 + +TEST_SUITE(Square9x9) + +using CLConvolutionFixture = ConvolutionSquareFixture; + +TEST_SUITE(U8) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), U8, 9) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), U8, 9) +TEST_SUITE_END() // U8 + +TEST_SUITE(S16) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), S16, 9) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), S16, 9) +TEST_SUITE_END() // S16 + +TEST_SUITE_END() // Square9x9 + +TEST_SUITE(Rectangle) + +using CLConvolutionFixture = ConvolutionRectangleFixture; + +TEST_SUITE(U8) +CONVOLUTION_RECTANGLE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), U8) +CONVOLUTION_RECTANGLE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), U8) +TEST_SUITE_END() // U8 + +TEST_SUITE(S16) +CONVOLUTION_RECTANGLE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), S16) +CONVOLUTION_RECTANGLE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), S16) +TEST_SUITE_END() // S16 + +TEST_SUITE_END() // Rectangle + +TEST_SUITE(Separable5x5) + +using CLConvolutionFixture = ConvolutionSeperableFixture; + +TEST_SUITE(U8) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), U8, 5) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), U8, 5) +TEST_SUITE_END() // U8 + +TEST_SUITE(S16) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), S16, 5) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), S16, 5) +TEST_SUITE_END() // S16 + +TEST_SUITE_END() // Separable5x5 + +TEST_SUITE(Separable7x7) + +using CLConvolutionFixture = ConvolutionSeperableFixture; + +TEST_SUITE(U8) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), U8, 7) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), U8, 7) +TEST_SUITE_END() // U8 + +TEST_SUITE(S16) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), S16, 7) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), S16, 7) +TEST_SUITE_END() // S16 + +TEST_SUITE_END() // Separable7x7 + +TEST_SUITE(Separable9x9) + +using CLConvolutionFixture = ConvolutionSeperableFixture; + +TEST_SUITE(U8) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), U8, 9) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), U8, 9) +TEST_SUITE_END() // U8 + +TEST_SUITE(S16) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), S16, 9) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), S16, 9) +TEST_SUITE_END() // S16 + +TEST_SUITE_END() // Separable9x9 + +TEST_SUITE_END() // CustomConvolution +TEST_SUITE_END() // CL +} // namespace benchmark +} // namespace test +} // namespace arm_compute diff --git a/tests/benchmark/NEON/Convolution.cpp b/tests/benchmark/NEON/Convolution.cpp new file mode 100644 index 0000000000..29ff60a48a --- /dev/null +++ b/tests/benchmark/NEON/Convolution.cpp @@ -0,0 +1,206 @@ +/* + * Copyright (c) 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/core/Types.h" +#include "arm_compute/runtime//Tensor.h" +#include "arm_compute/runtime/NEON/functions/NEConvolution.h" +#include "tests/NEON/Accessor.h" +#include "tests/benchmark/fixtures/ConvolutionFixture.h" +#include "tests/datasets/BorderModeDataset.h" +#include "tests/datasets/ShapeDatasets.h" +#include "tests/framework/Macros.h" +#include "tests/framework/datasets/Datasets.h" +#include "utils/TypePrinter.h" + +namespace arm_compute +{ +namespace test +{ +namespace benchmark +{ +namespace +{ +// *INDENT-OFF* +// clang-format off + +#define CONVOLUTION_SQUARE_DATA_TEST_CASE(TEST_NAME, MODE, SHAPES, DT, FILTER_SIZE) \ + REGISTER_FIXTURE_DATA_TEST_CASE(TEST_NAME, NEConvolutionFixture, framework::DatasetMode::MODE, \ + combine(combine(combine( \ + datasets::SHAPES, \ + framework::dataset::make("DataType", DataType::DT)), \ + datasets::BorderModes()), \ + framework::dataset::make("FilterSize", { FILTER_SIZE }))); + +#define CONVOLUTION_RECTANGLE_DATA_TEST_CASE(TEST_NAME, MODE, SHAPES, DT) \ + REGISTER_FIXTURE_DATA_TEST_CASE(TEST_NAME, NEConvolutionFixture, framework::DatasetMode::MODE, \ + combine(combine(combine(combine( \ + datasets::SHAPES, \ + framework::dataset::make("DataType", DataType::DT)), \ + datasets::BorderModes()), \ + framework::dataset::make("FilterSize", { 3, 5, 7, 9 })), \ + framework::dataset::make("FilterSize", { 3, 5, 7, 9 }))); + +#define CONVOLUTION_SEPARABLE_DATA_TEST_CASE(TEST_NAME, MODE, SHAPES, DT, FILTER_SIZE) \ + CONVOLUTION_SQUARE_DATA_TEST_CASE(TEST_NAME, MODE, SHAPES, DT, FILTER_SIZE) + +// clang-format on +// *INDENT-ON* + +} // namespace + +TEST_SUITE(NEON) +TEST_SUITE(CustomConvolution) + +TEST_SUITE(Square3x3) + +using NEConvolutionFixture = ConvolutionSquareFixture; + +TEST_SUITE(U8) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), U8, 3) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), U8, 3) +TEST_SUITE_END() // U8 + +TEST_SUITE(S16) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), S16, 3) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), S16, 3) +TEST_SUITE_END() // S16 + +TEST_SUITE_END() // Square3x3 + +TEST_SUITE(Square5x5) + +using NEConvolutionFixture = ConvolutionSquareFixture; + +TEST_SUITE(U8) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), U8, 5) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), U8, 5) +TEST_SUITE_END() // U8 + +TEST_SUITE(S16) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), S16, 5) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), S16, 5) +TEST_SUITE_END() // S16 + +TEST_SUITE_END() // Square5x5 + +TEST_SUITE(Square7x7) + +using NEConvolutionFixture = ConvolutionSquareFixture; + +TEST_SUITE(U8) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), U8, 7) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), U8, 7) +TEST_SUITE_END() // U8 + +TEST_SUITE(S16) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), S16, 7) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), S16, 7) +TEST_SUITE_END() // S16 + +TEST_SUITE_END() // Square7x7 + +TEST_SUITE(Square9x9) + +using NEConvolutionFixture = ConvolutionSquareFixture; + +TEST_SUITE(U8) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), U8, 9) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), U8, 9) +TEST_SUITE_END() // U8 + +TEST_SUITE(S16) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), S16, 9) +CONVOLUTION_SQUARE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), S16, 9) +TEST_SUITE_END() // S16 + +TEST_SUITE_END() // Square9x9 + +TEST_SUITE(Rectangle) + +using NEConvolutionFixture = ConvolutionRectangleFixture; + +TEST_SUITE(U8) +CONVOLUTION_RECTANGLE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), U8) +CONVOLUTION_RECTANGLE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), U8) +TEST_SUITE_END() // U8 + +TEST_SUITE(S16) +CONVOLUTION_RECTANGLE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), S16) +CONVOLUTION_RECTANGLE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), S16) +TEST_SUITE_END() // S16 + +TEST_SUITE_END() // Rectangle + +TEST_SUITE(Separable5x5) + +using NEConvolutionFixture = ConvolutionSeperableFixture; + +TEST_SUITE(U8) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), U8, 5) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), U8, 5) +TEST_SUITE_END() // U8 + +TEST_SUITE(S16) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), S16, 5) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), S16, 5) +TEST_SUITE_END() // S16 + +TEST_SUITE_END() // Separable5x5 + +TEST_SUITE(Separable7x7) + +using NEConvolutionFixture = ConvolutionSeperableFixture; + +TEST_SUITE(U8) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), U8, 7) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), U8, 7) +TEST_SUITE_END() // U8 + +TEST_SUITE(S16) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), S16, 7) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), S16, 7) +TEST_SUITE_END() // S16 + +TEST_SUITE_END() // Separable7x7 + +TEST_SUITE(Separable9x9) + +using NEConvolutionFixture = ConvolutionSeperableFixture; + +TEST_SUITE(U8) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), U8, 9) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), U8, 9) +TEST_SUITE_END() // U8 + +TEST_SUITE(S16) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunSmall, PRECOMMIT, SmallShapes(), S16, 9) +CONVOLUTION_SEPARABLE_DATA_TEST_CASE(RunLarge, NIGHTLY, LargeShapes(), S16, 9) +TEST_SUITE_END() // S16 + +TEST_SUITE_END() // Separable9x9 + +TEST_SUITE_END() // CustomConvolution +TEST_SUITE_END() // NEON +} // namespace benchmark +} // namespace test +} // namespace arm_compute diff --git a/tests/benchmark/fixtures/ConvolutionFixture.h b/tests/benchmark/fixtures/ConvolutionFixture.h new file mode 100644 index 0000000000..3f9c2a4f27 --- /dev/null +++ b/tests/benchmark/fixtures/ConvolutionFixture.h @@ -0,0 +1,173 @@ +/* + * Copyright (c) 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. + */ +#ifndef ARM_COMPUTE_TEST_CONVOLUTIONFIXTURE +#define ARM_COMPUTE_TEST_CONVOLUTIONFIXTURE + +#include "arm_compute/core/TensorShape.h" +#include "arm_compute/core/Types.h" +#include "tests/Globals.h" +#include "tests/Utils.h" +#include "tests/framework/Fixture.h" + +namespace arm_compute +{ +namespace test +{ +namespace benchmark +{ +/** Parent fixture that can be used for NEON and CL */ +template +class ConvolutionFixture : public framework::Fixture +{ +public: + template + void setup(TensorShape src_shape, DataType output_data_type, BorderMode border_mode, unsigned int width, unsigned int height, bool is_separable = false) + { + std::mt19937 gen(library->seed()); + const uint8_t constant_border_value = 0; + + // Generate random scale value between 1 and 255. + std::uniform_int_distribution distribution_scale(1, 255); + const uint32_t scale = distribution_scale(gen); + + ARM_COMPUTE_ERROR_ON(3 != width && 5 != width && 7 != width && 9 != width); + ARM_COMPUTE_ERROR_ON(3 != height && 5 != height && 7 != height && 9 != height); + + std::vector conv(width * height); + + _width = width; + _height = height; + + if(is_separable) + { + init_separable_conv(conv.data(), width, height, seed); + } + else + { + init_conv(conv.data(), width, height, seed); + } + + // Create tensors + src = create_tensor(src_shape, DataType::U8); + dst = create_tensor(src_shape, output_data_type); + + // Configure function + configure_target(convolution_func, src, dst, conv.data(), scale, border_mode, constant_border_value); + + // Allocate tensors + src.allocator()->allocate(); + dst.allocator()->allocate(); + + // Fill tensors + library->fill_tensor_uniform(Accessor(src), 0); + library->fill_tensor_uniform(Accessor(dst), 1); + } + + void run() + { + convolution_func.run(); + } + + void sync() + { + sync_if_necessary(); + sync_tensor_if_necessary(dst); + } + +protected: + virtual void configure_target(Function &func, TensorType &src, TensorType &dst, const int16_t *conv, uint32_t scale, + BorderMode border_mode, uint8_t border_value) = 0; + +protected: + unsigned int _width{}; + unsigned int _height{}; + Function convolution_func{}; + +private: + const std::random_device::result_type seed = 0; + TensorType src{}; + TensorType dst{}; +}; + +/** Child fixture used for square convolutions */ +template +class ConvolutionSquareFixture : public ConvolutionFixture +{ +public: + template + void setup(TensorShape src_shape, DataType output_data_type, BorderMode border_mode, unsigned int width) + { + ConvolutionFixture::setup(src_shape, output_data_type, border_mode, width, width); + } + +protected: + void configure_target(Function &func, TensorType &src, TensorType &dst, const int16_t *conv, uint32_t scale, + BorderMode border_mode, uint8_t constant_border_value) + { + this->convolution_func.configure(&src, &dst, conv, scale, border_mode, constant_border_value); + } +}; + +/** Child fixture used for rectangular convolutions */ +template +class ConvolutionRectangleFixture : public ConvolutionFixture +{ +public: + template + void setup(TensorShape src_shape, DataType output_data_type, BorderMode border_mode, unsigned int width, unsigned int height) + { + ConvolutionFixture::setup(src_shape, output_data_type, border_mode, width, height); + } + +protected: + void configure_target(Function &func, TensorType &src, TensorType &dst, const int16_t *conv, uint32_t scale, + BorderMode border_mode, uint8_t constant_border_value) + { + this->convolution_func.configure(&src, &dst, conv, this->_width, this->_height, scale, border_mode, constant_border_value); + } +}; + +/** Child fixture used for separable convolutions */ +template +class ConvolutionSeperableFixture : public ConvolutionFixture +{ +public: + template + void setup(TensorShape src_shape, DataType output_data_type, BorderMode border_mode, unsigned int width) + { + ConvolutionFixture::setup(src_shape, output_data_type, border_mode, width, width, true); + } + +protected: + void configure_target(Function &func, TensorType &src, TensorType &dst, const int16_t *conv, uint32_t scale, + BorderMode border_mode, uint8_t constant_border_value) + { + this->convolution_func.configure(&src, &dst, conv, scale, border_mode, constant_border_value); + } +}; + +} // namespace benchmark +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_CONVOLUTIONFIXTURE */ diff --git a/tests/validation/fixtures/ConvolutionFixture.h b/tests/validation/fixtures/ConvolutionFixture.h index 8ebb924c65..741ebe5eb9 100644 --- a/tests/validation/fixtures/ConvolutionFixture.h +++ b/tests/validation/fixtures/ConvolutionFixture.h @@ -66,56 +66,17 @@ protected: if(is_separable) { - create_separable_conv(conv.data()); + init_separable_conv(conv.data(), width, height, library->seed()); } else { - create_conv(conv.data()); + init_conv(conv.data(), width, height, library->seed()); } _target = compute_target(shape, output_data_type, conv.data(), scale, border_mode, constant_border_value); _reference = compute_reference(shape, output_data_type, conv.data(), scale, border_mode, constant_border_value); } - void - create_conv(int16_t *conv) - { - std::mt19937 gen(library->seed()); - std::uniform_int_distribution distribution_int16(-32768, 32767); - - for(unsigned int i = 0; i < _width * _height; ++i) - { - conv[i] = distribution_int16(gen); - } - } - - void - create_separable_conv(int16_t *conv) - { - std::mt19937 gen(library->seed()); - // Set it between -128 and 127 to ensure the matrix does not overflow - std::uniform_int_distribution distribution_int16(-128, 127); - - int16_t conv_row[_width]; - int16_t conv_col[_height]; - - conv_row[0] = conv_col[0] = 1; - for(unsigned int i = 1; i < _width; ++i) - { - conv_row[i] = distribution_int16(gen); - conv_col[i] = distribution_int16(gen); - } - - // Multiply two matrices - for(unsigned int i = 0; i < _width; ++i) - { - for(unsigned int j = 0; j < _height; ++j) - { - conv[i * _width + j] = conv_col[i] * conv_row[j]; - } - } - } - template void fill(U &&tensor, int i) { -- cgit v1.2.1