126 lines
7.5 KiB
C++
126 lines
7.5 KiB
C++
/*
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* Copyright (c) 2017-2020 Arm Limited.
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*
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* SPDX-License-Identifier: MIT
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to
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* deal in the Software without restriction, including without limitation the
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* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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* sell copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*/
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#include "arm_compute/core/Types.h"
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#include "arm_compute/runtime/GLES_COMPUTE/GCTensor.h"
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#include "arm_compute/runtime/GLES_COMPUTE/GCTensorAllocator.h"
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#include "arm_compute/runtime/GLES_COMPUTE/functions/GCConvolutionLayer.h"
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#include "tests/GLES_COMPUTE/GCAccessor.h"
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#include "tests/PaddingCalculator.h"
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#include "tests/datasets/LargeConvolutionLayerDataset.h"
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#include "tests/datasets/SmallConvolutionLayerDataset.h"
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#include "tests/framework/Asserts.h"
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#include "tests/framework/Macros.h"
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#include "tests/framework/datasets/Datasets.h"
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#include "tests/validation/Validation.h"
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#include "tests/validation/fixtures/ConvolutionLayerFixture.h"
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namespace arm_compute
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{
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namespace test
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{
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namespace validation
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{
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namespace
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{
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RelativeTolerance<half_float::half> tolerance_f16(half_float::half(0.2)); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
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RelativeTolerance<float> tolerance_f32(0.00001f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
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constexpr float tolerance_num = 0.07f; /**< Tolerance number */
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/** CNN data types */
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const auto CNNDataTypes = framework::dataset::make("DataType",
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{
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DataType::F16,
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DataType::F32,
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});
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const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo",
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{
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ActivationLayerInfo(),
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ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
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ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 0.5f)
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});
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} // namespace
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TEST_SUITE(GC)
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TEST_SUITE(ConvolutionLayer)
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template <typename T>
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using GCConvolutionLayerFixture = ConvolutionValidationFixture<GCTensor, GCAccessor, GCConvolutionLayer, T>;
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TEST_SUITE(Float)
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TEST_SUITE(FP16)
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FIXTURE_DATA_TEST_CASE(RunSmall, GCConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerReducedDataset(),
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framework::dataset::make("ReshapeWeights", { true })),
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framework::dataset::make("DataType",
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DataType::F16)),
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framework::dataset::make("DataLayout",
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DataLayout::NCHW)),
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ActivationFunctionsDataset))
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{
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// Validate output
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validate(GCAccessor(_target), _reference, tolerance_f16, tolerance_num);
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}
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FIXTURE_DATA_TEST_CASE(RunLarge, GCConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeConvolutionLayerDataset(),
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framework::dataset::make("ReshapeWeights", { true })),
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framework::dataset::make("DataType",
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DataType::F16)),
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framework::dataset::make("DataLayout",
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DataLayout::NCHW)),
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ActivationFunctionsDataset))
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{
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// Validate output
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validate(GCAccessor(_target), _reference, tolerance_f16, tolerance_num);
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}
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TEST_SUITE_END()
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TEST_SUITE(FP32)
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FIXTURE_DATA_TEST_CASE(RunSmall, GCConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerReducedDataset(),
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framework::dataset::make("ReshapeWeights", { true })),
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framework::dataset::make("DataType", DataType::F32)),
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framework::dataset::make("DataLayout",
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DataLayout::NCHW)),
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ActivationFunctionsDataset))
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{
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// Validate output
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validate(GCAccessor(_target), _reference, tolerance_f32, tolerance_num);
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}
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FIXTURE_DATA_TEST_CASE(RunLarge, GCConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeConvolutionLayerDataset(),
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framework::dataset::make("ReshapeWeights", { true })),
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framework::dataset::make("DataType", DataType::F32)),
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framework::dataset::make("DataLayout",
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DataLayout::NCHW)),
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ActivationFunctionsDataset))
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{
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// Validate output
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validate(GCAccessor(_target), _reference, tolerance_f32, tolerance_num);
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}
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TEST_SUITE_END()
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TEST_SUITE_END()
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TEST_SUITE_END()
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TEST_SUITE_END()
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} // namespace validation
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} // namespace test
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} // namespace arm_compute
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