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author | Sanghoon Lee <sanghoon.lee@arm.com> | 2017-11-29 11:23:14 +0000 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:42:33 +0000 |
commit | c8a85bac94a2d647fa8fdcd6efe9fd7af9ff4d29 (patch) | |
tree | 983c61d214486e51e61e960f67c5ad0f7ba17b74 /tests/validation/CL/Convolution.cpp | |
parent | 284c2045de0811f423a44d2e665f4f45a9e702fa (diff) | |
download | ComputeLibrary-c8a85bac94a2d647fa8fdcd6efe9fd7af9ff4d29.tar.gz |
COMPMID-563 - Implement reference and CL/NEON validation for Custom_Convolution (Output U8)
Change-Id: I57a6db857474929322206ee7440e088bc0bbbbe2
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/111080
Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
Diffstat (limited to 'tests/validation/CL/Convolution.cpp')
-rw-r--r-- | tests/validation/CL/Convolution.cpp | 325 |
1 files changed, 325 insertions, 0 deletions
diff --git a/tests/validation/CL/Convolution.cpp b/tests/validation/CL/Convolution.cpp new file mode 100644 index 0000000000..c836edabb8 --- /dev/null +++ b/tests/validation/CL/Convolution.cpp @@ -0,0 +1,325 @@ +/* + * Copyright (c) 2017 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/functions/CLConvolution.h" +#include "arm_compute/runtime/Tensor.h" +#include "arm_compute/runtime/TensorAllocator.h" +#include "tests/CL/CLAccessor.h" +#include "tests/PaddingCalculator.h" +#include "tests/datasets/BorderModeDataset.h" +#include "tests/datasets/ShapeDatasets.h" +#include "tests/framework/Asserts.h" +#include "tests/framework/Macros.h" +#include "tests/framework/datasets/Datasets.h" +#include "tests/validation/Validation.h" +#include "tests/validation/fixtures/ConvolutionFixture.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace +{ +/* Convolution3x3 */ +constexpr unsigned int filter_size_3x3 = 3; /* Size of the kernel/filter in number of elements. */ +constexpr BorderSize border_size_3x3(filter_size_3x3 / 2); /* Border size of the kernel/filter around its central element. */ + +/* Convolution5x5 */ +constexpr unsigned int filter_size_5x5 = 5; /* Size of the kernel/filter in number of elements. */ +constexpr BorderSize border_size_5x5(filter_size_5x5 / 2); /* Border size of the kernel/filter around its central element. */ + +/* Convolution7x7 */ +constexpr unsigned int filter_size_7x7 = 7; /* Size of the kernel/filter in number of elements. */ +constexpr BorderSize border_size_7x7(filter_size_7x7 / 2); /* Border size of the kernel/filter around its central element. */ + +/* Convolution9x9 */ +constexpr unsigned int filter_size_9x9 = 9; /* Size of the kernel/filter in number of elements. */ +constexpr BorderSize border_size_9x9(filter_size_9x9 / 2); /* Border size of the kernel/filter around its central element. */ +} // namespace + +TEST_SUITE(CL) +TEST_SUITE(CustomConvolution) +TEST_SUITE(CustomConvolution3x3) + +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), + datasets::BorderModes()), + shape, data_type, border_mode) +{ + // Create tensors + CLTensor src = create_tensor<CLTensor>(shape, data_type); + CLTensor dst = create_tensor<CLTensor>(shape, data_type); + + // Create conv matrix + int16_t conv[9]; + + // Generate random scale value between 0 and 255. + std::mt19937 gen(library->seed()); + std::uniform_int_distribution<uint8_t> distribution(0, 255); + const uint32_t scale = distribution(gen); + + ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Create and configure function + CLConvolution3x3 convolution; + convolution.configure(&src, &dst, conv, scale, border_mode); + + // Validate valid region + const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_3x3); + validate(dst.info()->valid_region(), dst_valid_region); + + // Validate padding + PaddingCalculator calculator(shape.x(), 8); + calculator.set_border_size(1); + calculator.set_border_mode(border_mode); + + const PaddingSize dst_padding = calculator.required_padding(); + + calculator.set_accessed_elements(16); + calculator.set_access_offset(-1); + + const PaddingSize src_padding = calculator.required_padding(); + + validate(src.info()->padding(), src_padding); + validate(dst.info()->padding(), dst_padding); +} + +template <typename T> +using CLConvolutionFixture = ConvolutionValidationFixture<CLTensor, CLAccessor, CLConvolution3x3, T, filter_size_3x3>; + +FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", + DataType::U8)), + datasets::BorderModes())) +{ + // Validate output + validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_3x3)); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", + DataType::U8)), + datasets::BorderModes())) +{ + // Validate output + validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_3x3)); +} +TEST_SUITE_END() /* Custom_Convolution 3x3 */ + +TEST_SUITE(CustomConvolution5x5) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), + datasets::BorderModes()), + shape, data_type, border_mode) +{ + // Create tensors + CLTensor src = create_tensor<CLTensor>(shape, data_type); + CLTensor dst = create_tensor<CLTensor>(shape, data_type); + + // Create conv matrix + int16_t conv[25]; + + // Generate random scale value between 0 and 255. + std::mt19937 gen(library->seed()); + std::uniform_int_distribution<uint8_t> distribution(0, 255); + const uint32_t scale = distribution(gen); + + ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Create and configure function + CLConvolution5x5 convolution; + convolution.configure(&src, &dst, conv, scale, border_mode); + + // Validate valid region + const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_5x5); + validate(dst.info()->valid_region(), dst_valid_region); + + // Validate padding + PaddingCalculator calculator(shape.x(), 8); + calculator.set_border_size(2); + calculator.set_border_mode(border_mode); + + const PaddingSize dst_padding = calculator.required_padding(); + + calculator.set_accessed_elements(16); + calculator.set_access_offset(-2); + + const PaddingSize src_padding = calculator.required_padding(); + + validate(src.info()->padding(), src_padding); + validate(dst.info()->padding(), dst_padding); +} + +template <typename T> +using CLConvolutionFixture = ConvolutionValidationFixture<CLTensor, CLAccessor, CLConvolution5x5, T, filter_size_5x5>; + +FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", + DataType::U8)), + datasets::BorderModes())) +{ + // Validate output + validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_5x5)); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", + DataType::U8)), + datasets::BorderModes())) +{ + // Validate output + validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_5x5)); +} +TEST_SUITE_END() /* Custom Convolution 5x5 */ + +TEST_SUITE(CustomConvolution7x7) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), + datasets::BorderModes()), + shape, data_type, border_mode) +{ + // Create tensors + CLTensor src = create_tensor<CLTensor>(shape, data_type); + CLTensor dst = create_tensor<CLTensor>(shape, data_type); + + // Create conv matrix + int16_t conv[49]; + + // Generate random scale value between 0 and 255. + std::mt19937 gen(library->seed()); + std::uniform_int_distribution<uint8_t> distribution(0, 255); + const uint32_t scale = distribution(gen); + + ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Create and configure function + CLConvolution7x7 convolution; + convolution.configure(&src, &dst, conv, scale, border_mode); + + // Validate valid region + const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_7x7); + validate(dst.info()->valid_region(), dst_valid_region); + + // Validate padding + PaddingCalculator calculator(shape.x(), 8); + calculator.set_border_size(3); + calculator.set_border_mode(border_mode); + + const PaddingSize dst_padding = calculator.required_padding(); + + calculator.set_accessed_elements(16); + calculator.set_access_offset(-3); + + const PaddingSize src_padding = calculator.required_padding(); + + validate(src.info()->padding(), src_padding); + validate(dst.info()->padding(), dst_padding); +} + +template <typename T> +using CLConvolutionFixture = ConvolutionValidationFixture<CLTensor, CLAccessor, CLConvolution7x7, T, filter_size_7x7>; + +FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", + DataType::U8)), + datasets::BorderModes())) +{ + // Validate output + validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_7x7)); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", + DataType::U8)), + datasets::BorderModes())) +{ + // Validate output + validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_7x7)); +} +TEST_SUITE_END() /* Custom Convolution 7x7 */ + +TEST_SUITE(CustomConvolution9x9) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), + datasets::BorderModes()), + shape, data_type, border_mode) +{ + // Create tensors + CLTensor src = create_tensor<CLTensor>(shape, data_type); + CLTensor dst = create_tensor<CLTensor>(shape, data_type); + + // Create conv matrix + int16_t conv[81]; + + // Generate random scale value between 0 and 255. + std::mt19937 gen(library->seed()); + std::uniform_int_distribution<uint8_t> distribution(0, 255); + const uint32_t scale = distribution(gen); + + ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Create and configure function + CLConvolution9x9 convolution; + convolution.configure(&src, &dst, conv, scale, border_mode); + + // Validate valid region + const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_9x9); + validate(dst.info()->valid_region(), dst_valid_region); + + // Validate padding + PaddingCalculator calculator(shape.x(), 8); + calculator.set_border_size(4); + calculator.set_border_mode(border_mode); + + const PaddingSize dst_padding = calculator.required_padding(); + + calculator.set_accessed_elements(16); + calculator.set_access_offset(-4); + + const PaddingSize src_padding = calculator.required_padding(); + + validate(src.info()->padding(), src_padding); + validate(dst.info()->padding(), dst_padding); +} + +template <typename T> +using CLConvolutionFixture = ConvolutionValidationFixture<CLTensor, CLAccessor, CLConvolution9x9, T, filter_size_9x9>; + +FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", + DataType::U8)), + datasets::BorderModes())) +{ + // Validate output + validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_9x9)); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", + DataType::U8)), + datasets::BorderModes())) +{ + // Validate output + validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_9x9)); +} +TEST_SUITE_END() /* Custom Convolution 9x9 */ +TEST_SUITE_END() +TEST_SUITE_END() +} // namespace validation +} // namespace test +} // namespace arm_compute |