919 lines
66 KiB
C++
919 lines
66 KiB
C++
/*
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* Copyright (c) 2018-2020 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/Helpers.h"
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#include "arm_compute/core/Types.h"
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#include "arm_compute/core/utils/misc/ShapeCalculator.h"
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#include "arm_compute/runtime/CL/CLTensor.h"
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#include "arm_compute/runtime/CL/CLTensorAllocator.h"
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#include "arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h"
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#include "arm_compute/runtime/CL/functions/CLWinogradInputTransform.h"
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#include "src/core/CL/kernels/CLWinogradFilterTransformKernel.h"
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#include "src/core/CL/kernels/CLWinogradOutputTransformKernel.h"
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#include "tests/CL/CLAccessor.h"
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#include "tests/CL/Helper.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/ShapeDatasets.h"
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#include "tests/datasets/SmallConvolutionLayerDataset.h"
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#include "tests/datasets/WinogradInputTransformDataset.h"
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#include "tests/datasets/WinogradOutputTransformDataset.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/WinogradConvolutionLayerFixture.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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// *INDENT-OFF*
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// clang-format off
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constexpr AbsoluteTolerance<float> tolerance_f32(0.002f);
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const AbsoluteTolerance<half> tolerance_f16(half(0.5f));
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constexpr AbsoluteTolerance<float> tolerance_convolution_layer_f32(0.1f);
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const AbsoluteTolerance<half> tolerance_convolution_layer_f16(half(0.4f));
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RelativeTolerance<half_float::half> rel_tolerance_f16(half(0.2)); /**< Tolerance value for comparing reference's output against implementation's output for FP16 data types */
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constexpr float tolerance_num = 0.05f; /**< Tolerance number */
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constexpr float abs_tolerance_convolution_layer_f16 = 2.5f; /**< Tolerance number */
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constexpr float tolerance_num_f16 = 0.15f; /**< Tolerance number */
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// Input transform
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const auto SmallWinogradInputTransformDatasetNCHW =
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framework::dataset::concat(datasets::SmallWinogradInputTransformDataset2x2_3x3(),
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framework::dataset::concat(datasets::SmallWinogradInputTransformDataset2x1_3x1(),
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framework::dataset::concat(datasets::SmallWinogradInputTransformDataset1x2_1x3(),
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framework::dataset::concat(datasets::SmallWinogradInputTransformDataset4x4_3x3(),
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framework::dataset::concat(datasets::SmallWinogradInputTransformDataset4x1_3x1(),
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framework::dataset::concat(datasets::SmallWinogradInputTransformDataset1x4_1x3(),
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framework::dataset::concat(datasets::SmallWinogradInputTransformDataset4x4_5x5(),
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framework::dataset::concat(datasets::SmallWinogradInputTransformDataset4x1_5x1(),
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datasets::SmallWinogradInputTransformDataset1x4_1x5()))))))));
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const auto SmallWinogradInputTransformDatasetNHWC = framework::dataset::concat(datasets::SmallWinogradInputTransformDataset4x4_3x3(),
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framework::dataset::concat(datasets::SmallWinogradInputTransformDataset4x1_3x1(),
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framework::dataset::concat(datasets::SmallWinogradInputTransformDataset1x4_1x3(),
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framework::dataset::concat(datasets::SmallWinogradInputTransformDataset4x4_5x5(),
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framework::dataset::concat(datasets::SmallWinogradInputTransformDataset4x1_5x1(),
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framework::dataset::concat(datasets::SmallWinogradInputTransformDataset1x4_1x5(),
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framework::dataset::concat(datasets::SmallWinogradInputTransformDataset2x1_7x1(),
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datasets::SmallWinogradInputTransformDataset1x2_1x7())))))));
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const auto SmallWinogradInputTransformDatasetNHWC_FP32 = framework::dataset::concat(SmallWinogradInputTransformDatasetNHWC,
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datasets::SmallWinogradInputTransformDataset2x2_7x7());
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const auto LargeWinogradInputTransformDatasetNCHW =
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framework::dataset::concat(datasets::LargeWinogradInputTransformDataset2x2_3x3(),
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framework::dataset::concat(datasets::LargeWinogradInputTransformDataset2x1_3x1(),
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framework::dataset::concat(datasets::LargeWinogradInputTransformDataset1x2_1x3(),
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framework::dataset::concat(datasets::LargeWinogradInputTransformDataset4x4_3x3(),
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framework::dataset::concat(datasets::LargeWinogradInputTransformDataset4x1_3x1(),
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framework::dataset::concat(datasets::LargeWinogradInputTransformDataset1x4_1x3(),
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framework::dataset::concat(datasets::LargeWinogradInputTransformDataset4x4_5x5(),
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framework::dataset::concat(datasets::LargeWinogradInputTransformDataset4x1_5x1(),
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datasets::LargeWinogradInputTransformDataset1x4_1x5()))))))));
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const auto LargeWinogradInputTransformDatasetNHWC =
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framework::dataset::concat(datasets::LargeWinogradInputTransformDataset4x4_3x3(),
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framework::dataset::concat(datasets::LargeWinogradInputTransformDataset4x4_5x5(),
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framework::dataset::concat(datasets::LargeWinogradInputTransformDataset4x1_5x1(),
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datasets::LargeWinogradInputTransformDataset1x4_1x5())));
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const auto LargeWinogradInputTransformDatasetNHWC_FP32 =
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framework::dataset::concat(LargeWinogradInputTransformDatasetNHWC,
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(datasets::LargeWinogradInputTransformDataset2x2_7x7()));
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// Filter transform
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const auto SmallWinogradFilterTransformDatasetNCHW =
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framework::dataset::concat(combine(datasets::Small3x3Shapes(), framework::dataset::make("OutputTile", { Size2D(2U, 2U), Size2D(4U, 4U) })),
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framework::dataset::concat(combine(datasets::Small3x1Shapes(), framework::dataset::make("OutputTile", { Size2D(2U, 1U), Size2D(4U, 1U) })),
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framework::dataset::concat(combine(datasets::Small1x3Shapes(), framework::dataset::make("OutputTile", { Size2D(1U, 2U), Size2D(1U, 4U) })),
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framework::dataset::concat(combine(datasets::Small5x5Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 4U) })),
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framework::dataset::concat(combine(datasets::Small5x1Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 1U) })),
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combine(datasets::Small1x5Shapes(), framework::dataset::make("OutputTile", { Size2D(1U, 4U) })))))));
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const auto SmallWinogradFilterTransformDatasetNHWC_F16 =
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framework::dataset::concat(combine(datasets::Small3x3Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 4U) })),
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framework::dataset::concat(combine(datasets::Small3x1Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 1U) })),
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framework::dataset::concat(combine(datasets::Small1x3Shapes(), framework::dataset::make("OutputTile", { Size2D(1U, 4U) })),
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framework::dataset::concat(combine(datasets::Small5x5Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 4U) })),
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framework::dataset::concat(combine(datasets::Small5x1Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 1U) })),
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framework::dataset::concat(combine(datasets::Small1x5Shapes(), framework::dataset::make("OutputTile", { Size2D(1U, 4U) })),
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framework::dataset::concat(combine(datasets::Small1x7Shapes(), framework::dataset::make("OutputTile", { Size2D(1U, 2U) })),
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combine(datasets::Small7x1Shapes(), framework::dataset::make("OutputTile", { Size2D(2U, 1U) })))))))));
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const auto SmallWinogradFilterTransformDatasetNHWC_F32 =
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framework::dataset::concat(SmallWinogradFilterTransformDatasetNHWC_F16,
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combine(datasets::Small7x7Shapes(), framework::dataset::make("OutputTile", { Size2D(2U, 2U) })));
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const auto LargeWinogradFilterTransformDatasetNCHW =
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framework::dataset::concat(combine(datasets::Large3x3Shapes(), framework::dataset::make("OutputTile", { Size2D(2U, 2U), Size2D(4U, 4U) })),
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framework::dataset::concat(combine(datasets::Large3x1Shapes(), framework::dataset::make("OutputTile", { Size2D(2U, 1U), Size2D(4U, 1U) })),
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framework::dataset::concat(combine(datasets::Large1x3Shapes(), framework::dataset::make("OutputTile", { Size2D(1U, 2U), Size2D(1U, 4U) })),
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framework::dataset::concat(combine(datasets::Large5x5Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 4U) })),
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framework::dataset::concat(combine(datasets::Large5x1Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 1U) })),
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combine(datasets::Large1x5Shapes(), framework::dataset::make("OutputTile", { Size2D(1U, 4U) })))))));
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const auto LargeWinogradFilterTransformDatasetNHWC_F16 =
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framework::dataset::concat(combine(datasets::Large3x3Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 4U) })),
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framework::dataset::concat(combine(datasets::Large3x1Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 1U) })),
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framework::dataset::concat(combine(datasets::Large1x3Shapes(), framework::dataset::make("OutputTile", { Size2D(1U, 4U) })),
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framework::dataset::concat(combine(datasets::Large5x5Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 4U) })),
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framework::dataset::concat(combine(datasets::Large5x1Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 1U) })),
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framework::dataset::concat(combine(datasets::Large1x5Shapes(), framework::dataset::make("OutputTile", { Size2D(1U, 4U) })),
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framework::dataset::concat(combine(datasets::Large7x1Shapes(), framework::dataset::make("OutputTile", { Size2D(2U, 1U) })),
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combine(datasets::Large1x7Shapes(), framework::dataset::make("OutputTile", { Size2D(1U, 2U) })))))))));
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const auto LargeWinogradFilterTransformDatasetNHWC_F32 =
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framework::dataset::concat(LargeWinogradFilterTransformDatasetNHWC_F16,
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combine(datasets::Large7x7Shapes(), framework::dataset::make("OutputTile", { Size2D(2U, 2U) })));
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// Output transform
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const auto SmallWinogradOutputTransformDatasetNCHW = datasets::SmallWinogradOutputTransformDatasetNCHW();
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const auto SmallWinogradOutputTransformDatasetNHWC_F16 = datasets::SmallWinogradOutputTransformDatasetNHWC_F16();
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const auto SmallWinogradOutputTransformDatasetNHWC_F32 = datasets::SmallWinogradOutputTransformDatasetNHWC_F32();
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const auto LargeWinogradOutputTransformDatasetNCHW = datasets::LargeWinogradOutputTransformDatasetNCHW();
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const auto LargeWinogradOutputTransformDatasetNHWC_F16 = datasets::LargeWinogradOutputTransformDatasetNHWC_F16();
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const auto LargeWinogradOutputTransformDatasetNHWC_F32 = datasets::LargeWinogradOutputTransformDatasetNHWC_F32();
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//Activation Functions
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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),
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ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU),
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ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LEAKY_RELU)
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});
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const auto ActivationFunctionsSmallDataset = framework::dataset::make("ActivationInfo",
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{
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ActivationLayerInfo(),
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ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU),
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ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LEAKY_RELU),
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ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::SOFT_RELU)
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});
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} // namespace
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using namespace arm_compute::misc::shape_calculator;
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TEST_SUITE(CL)
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TEST_SUITE(Winograd)
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TEST_SUITE(InputTransform)
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DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
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framework::dataset::make("InputInfo",{
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TensorInfo(TensorShape(53U, 21U, 5U, 3U), 1, DataType::F16), // F16 not supported
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TensorInfo(TensorShape(53U, 21U, 5U, 3U), 1, DataType::QASYMM8), // QASYMM8 not supported
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TensorInfo(TensorShape(53U, 21U, 5U, 3U), 1, DataType::F32), // Kernel size not supported
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TensorInfo(TensorShape(53U, 21U, 5U, 3U), 1, DataType::F32), // Strides not supported
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TensorInfo(TensorShape(53U, 33U, 4U), 1, DataType::F32), // Padding needed
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TensorInfo(TensorShape(34U, 42U, 7U, 3U), 1, DataType::F32), // Padding needed
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TensorInfo(TensorShape(31U, 37U, 37U), 1, DataType::F32) // Padding needed
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}),
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framework::dataset::make("OutputInfo", {
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TensorInfo(TensorShape(5U, 5U, 16U, 3U), 1, DataType::F16),
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TensorInfo(TensorShape(5U, 5U, 16U, 3U), 1, DataType::QASYMM8),
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TensorInfo(TensorShape(5U, 5U, 16U, 3U), 1, DataType::F32),
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TensorInfo(TensorShape(5U, 1U, 16U, 3U), 1, DataType::F32),
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TensorInfo(TensorShape(4U, 442U, 16U), 1, DataType::F32),
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TensorInfo(TensorShape(7U, 320U, 16U, 3U), 1, DataType::F32),
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TensorInfo(TensorShape(37U, 304U, 16U), 1, DataType::F32)
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})),
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framework::dataset::make("WinogradInfo", {
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WinogradInfo(Size2D(2, 2), Size2D(3, 3), Size2D(53U, 21U), PadStrideInfo(1, 1, 1, 0), DataLayout::NCHW),
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WinogradInfo(Size2D(2, 2), Size2D(3, 3), Size2D(53U, 21U), PadStrideInfo(1, 1, 0, 0), DataLayout::NCHW),
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WinogradInfo(Size2D(2, 2), Size2D(3, 3), Size2D(53U, 21U), PadStrideInfo(1, 1, 1, 1), DataLayout::NCHW),
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WinogradInfo(Size2D(2, 2), Size2D(3, 3), Size2D(53U, 21U), PadStrideInfo(2, 1, 1, 1), DataLayout::NCHW),
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WinogradInfo(Size2D(2, 2), Size2D(3, 3), Size2D(53U, 33U), PadStrideInfo(1, 1, 0, 1), DataLayout::NCHW),
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WinogradInfo(Size2D(2, 2), Size2D(3, 3), Size2D(34U, 42U), PadStrideInfo(1, 1, 0, 0), DataLayout::NCHW),
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WinogradInfo(Size2D(2, 2), Size2D(3, 3), Size2D(31U, 37U), PadStrideInfo(1, 1, 1, 1), DataLayout::NCHW)
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})),
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framework::dataset::make("Expected", { false, false, false, false, false, false, false })),
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input_info, output_info, winograd_info, expected)
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{
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ARM_COMPUTE_EXPECT(bool(CLWinogradInputTransform::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), winograd_info)) == expected, framework::LogLevel::ERRORS);
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}
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using CLWinogradInputTransformFixtureFP32 = WinogradInputTransformValidationFixture<CLTensor, CLAccessor, CLWinogradInputTransform, float>;
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using CLWinogradInputTransformFixtureFP16 = WinogradInputTransformValidationFixture<CLTensor, CLAccessor, CLWinogradInputTransform, half>;
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TEST_SUITE(NCHW)
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TEST_SUITE(FP32)
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FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradInputTransformFixtureFP32, framework::DatasetMode::PRECOMMIT, combine(combine(SmallWinogradInputTransformDatasetNCHW,
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framework::dataset::make("DataLayout", { DataLayout::NCHW })),
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framework::dataset::make("DataType", { DataType::F32 })))
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{
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validate(CLAccessor(_target), _reference, tolerance_f32);
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}
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FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradInputTransformFixtureFP32, framework::DatasetMode::NIGHTLY, combine(combine(LargeWinogradInputTransformDatasetNCHW,
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framework::dataset::make("DataLayout", { DataLayout::NCHW })),
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framework::dataset::make("DataType", { DataType::F32 })))
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{
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validate(CLAccessor(_target), _reference, tolerance_f32);
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}
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TEST_SUITE_END() // FP32
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TEST_SUITE(FP16)
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FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradInputTransformFixtureFP16, framework::DatasetMode::PRECOMMIT, combine(combine(SmallWinogradInputTransformDatasetNCHW,
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framework::dataset::make("DataLayout", { DataLayout::NCHW })),
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framework::dataset::make("DataType", { DataType::F16 })))
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{
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validate(CLAccessor(_target), _reference, tolerance_f16);
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}
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FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradInputTransformFixtureFP16, framework::DatasetMode::NIGHTLY, combine(combine(LargeWinogradInputTransformDatasetNCHW,
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framework::dataset::make("DataLayout", { DataLayout::NCHW })),
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framework::dataset::make("DataType", { DataType::F16 })))
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{
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validate(CLAccessor(_target), _reference, tolerance_f16);
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}
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TEST_SUITE_END() // FP16
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TEST_SUITE_END() // NCHW
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TEST_SUITE(NHWC)
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TEST_SUITE(FP16)
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FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradInputTransformFixtureFP16, framework::DatasetMode::PRECOMMIT, combine(combine(SmallWinogradInputTransformDatasetNHWC,
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framework::dataset::make("DataLayout", { DataLayout::NHWC })),
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framework::dataset::make("DataType", { DataType::F16 })))
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{
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validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num_f16);
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}
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FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradInputTransformFixtureFP16, framework::DatasetMode::NIGHTLY, combine(combine(LargeWinogradInputTransformDatasetNHWC,
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framework::dataset::make("DataLayout", { DataLayout::NHWC })),
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framework::dataset::make("DataType", { DataType::F16 })))
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{
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validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num_f16);
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}
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TEST_SUITE_END() // FP16
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TEST_SUITE(FP32)
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FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradInputTransformFixtureFP32, framework::DatasetMode::PRECOMMIT, combine(combine(SmallWinogradInputTransformDatasetNHWC_FP32,
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framework::dataset::make("DataLayout", { DataLayout::NHWC })),
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framework::dataset::make("DataType", { DataType::F32 })))
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{
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validate(CLAccessor(_target), _reference, tolerance_f32);
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}
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FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradInputTransformFixtureFP32, framework::DatasetMode::NIGHTLY, combine(combine(LargeWinogradInputTransformDatasetNHWC_FP32,
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framework::dataset::make("DataLayout", { DataLayout::NHWC })),
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framework::dataset::make("DataType", { DataType::F32 })))
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{
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validate(CLAccessor(_target), _reference, tolerance_f32);
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}
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TEST_SUITE_END() // FP32
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TEST_SUITE_END() // NHWC
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TEST_SUITE_END() // InputTransform
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TEST_SUITE(FilterTransform)
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DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
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framework::dataset::make("InputInfo",{
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TensorInfo(TensorShape(3U, 3U, 5U, 3U), 1, DataType::F16), // F16 supported
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TensorInfo(TensorShape(3U, 3U, 5U, 3U), 1, DataType::QASYMM8), // QASYMM8 not supported
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TensorInfo(TensorShape(5U, 5U, 5U, 3U), 1, DataType::F32), // Kernel size not supported
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TensorInfo(TensorShape(3U, 3U), 1, DataType::F32), // Output tile not supported
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TensorInfo(TensorShape(3U, 3U, 5U, 3U), 1, DataType::F32), // valid
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TensorInfo(TensorShape(3U, 3U, 37U, 2U), 1, DataType::F32), // valid
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TensorInfo(TensorShape(3U, 3U, 37U, 22U), 1, DataType::F32) // valid
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}),
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|
framework::dataset::make("OutputInfo", {
|
|
TensorInfo(TensorShape(3U, 5U, 16U), 1, DataType::F16),
|
|
TensorInfo(TensorShape(3U, 5U, 16U), 1, DataType::QASYMM8),
|
|
TensorInfo(TensorShape(3U, 5U, 16U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(1U, 1U, 16U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(3U, 5U, 16U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(2U, 37U, 16U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(22U, 37U, 36U), 1, DataType::F32)
|
|
})),
|
|
framework::dataset::make("WinogradInfo", {
|
|
WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D() /* Not needed */, PadStrideInfo() /* Not needed */, DataLayout::NCHW /* Not needed */ ),
|
|
WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D() /* Not needed */, PadStrideInfo() /* Not needed */, DataLayout::NCHW /* Not needed */ ),
|
|
WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D() /* Not needed */, PadStrideInfo() /* Not needed */, DataLayout::NCHW /* Not needed */ ),
|
|
WinogradInfo(Size2D(3U, 3U), Size2D(3U, 3U), Size2D() /* Not needed */, PadStrideInfo() /* Not needed */, DataLayout::NCHW /* Not needed */ ),
|
|
WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D() /* Not needed */, PadStrideInfo() /* Not needed */, DataLayout::NCHW /* Not needed */ ),
|
|
WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D() /* Not needed */, PadStrideInfo() /* Not needed */, DataLayout::NCHW /* Not needed */ ),
|
|
WinogradInfo(Size2D(4U, 4U), Size2D(3U, 3U), Size2D() /* Not needed */, PadStrideInfo() /* Not needed */, DataLayout::NCHW /* Not needed */ )
|
|
})),
|
|
framework::dataset::make("Expected", { true, false, false, false, true, true, true })),
|
|
input_info, output_info, winograd_info, expected)
|
|
{
|
|
ARM_COMPUTE_EXPECT(bool(CLWinogradFilterTransformKernel::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), winograd_info)) == expected, framework::LogLevel::ERRORS);
|
|
}
|
|
|
|
using CLWinogradFilterTransform = CLSynthetizeFunctionWithZeroConstantBorder<CLWinogradFilterTransformKernel, 0>;
|
|
using CLWinogradFilterTransformFixtureFP32 = WinogradFilterTransformValidationFixture<CLTensor, CLAccessor, CLWinogradFilterTransform, float>;
|
|
using CLWinogradFilterTransformFixtureFP16 = WinogradFilterTransformValidationFixture<CLTensor, CLAccessor, CLWinogradFilterTransform, half>;
|
|
|
|
TEST_SUITE(NCHW)
|
|
TEST_SUITE(FP32)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradFilterTransformFixtureFP32, framework::DatasetMode::PRECOMMIT,
|
|
combine(combine(SmallWinogradFilterTransformDatasetNCHW,
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW })),
|
|
framework::dataset::make("DataType", { DataType::F32 })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_f32);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradFilterTransformFixtureFP32, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(LargeWinogradFilterTransformDatasetNCHW,
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW })),
|
|
framework::dataset::make("DataType", { DataType::F32 })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_f32);
|
|
}
|
|
TEST_SUITE_END() // FP32
|
|
TEST_SUITE(FP16)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradFilterTransformFixtureFP16, framework::DatasetMode::PRECOMMIT,
|
|
combine(combine(SmallWinogradFilterTransformDatasetNCHW,
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW })),
|
|
framework::dataset::make("DataType", { DataType::F16 })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_f16);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradFilterTransformFixtureFP16, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(LargeWinogradFilterTransformDatasetNCHW,
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW })),
|
|
framework::dataset::make("DataType", { DataType::F16 })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_f16);
|
|
}
|
|
TEST_SUITE_END() // FP16
|
|
TEST_SUITE_END() // NCHW
|
|
|
|
TEST_SUITE(NHWC)
|
|
TEST_SUITE(FP16)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradFilterTransformFixtureFP16, framework::DatasetMode::PRECOMMIT,
|
|
combine(combine(SmallWinogradFilterTransformDatasetNHWC_F16,
|
|
framework::dataset::make("DataLayout", { DataLayout::NHWC })),
|
|
framework::dataset::make("DataType", { DataType::F16 })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num_f16);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradFilterTransformFixtureFP16, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(LargeWinogradFilterTransformDatasetNHWC_F16,
|
|
framework::dataset::make("DataLayout", { DataLayout::NHWC })),
|
|
framework::dataset::make("DataType", { DataType::F16 })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num_f16);
|
|
}
|
|
TEST_SUITE_END() // FP16
|
|
TEST_SUITE(FP32)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradFilterTransformFixtureFP32, framework::DatasetMode::PRECOMMIT,
|
|
combine(combine(SmallWinogradFilterTransformDatasetNHWC_F32,
|
|
framework::dataset::make("DataLayout", { DataLayout::NHWC })),
|
|
framework::dataset::make("DataType", { DataType::F32 })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_f32);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradFilterTransformFixtureFP32, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(LargeWinogradFilterTransformDatasetNHWC_F32,
|
|
framework::dataset::make("DataLayout", { DataLayout::NHWC })),
|
|
framework::dataset::make("DataType", { DataType::F32 })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_f32);
|
|
}
|
|
TEST_SUITE_END() // FP32
|
|
TEST_SUITE_END() // NHWC
|
|
TEST_SUITE_END() // FilterTransform
|
|
|
|
TEST_SUITE(OutputTransform)
|
|
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
|
|
framework::dataset::make("InputInfo",{
|
|
TensorInfo(TensorShape(512U, 49U, 16U, 5U), 1, DataType::F16), // F16 supported
|
|
TensorInfo(TensorShape(512U, 49U, 16U, 5U), 1, DataType::QASYMM8), // QASYMM8 not supported
|
|
TensorInfo(TensorShape(512U, 49U, 16U, 5U), 1, DataType::F32), // Kernel size not supported
|
|
TensorInfo(TensorShape(512U, 49U, 16U, 5U), 1, DataType::F32), // Valid
|
|
TensorInfo(TensorShape(13U, 108U, 16U, 4U), 1, DataType::F32), // Padding needed
|
|
TensorInfo(TensorShape(7U, 20U, 16U, 7U), 1, DataType::F32), // Valid
|
|
TensorInfo(TensorShape(7U, 20U, 16U, 7U), 1, DataType::F32), // Wrong WinogradInfo
|
|
TensorInfo(TensorShape(7U, 256U, 36U, 3U), 1, DataType::F32), // Valid
|
|
TensorInfo(TensorShape(7U, 256U, 16U, 3U), 1, DataType::F32) // Wrong number of batches
|
|
}),
|
|
framework::dataset::make("BiasInfo", {
|
|
TensorInfo(TensorShape(512U), 1, DataType::F16),
|
|
TensorInfo(TensorShape(512U), 1, DataType::QASYMM8),
|
|
TensorInfo(TensorShape(512U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(512U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(13U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(7U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(7U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(7U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(7U), 1, DataType::F32)
|
|
})),
|
|
framework::dataset::make("OutputInfo", {
|
|
TensorInfo(TensorShape(14U, 14U, 512U, 5U), 1, DataType::F16),
|
|
TensorInfo(TensorShape(14U, 14U, 512U, 5U), 1, DataType::QASYMM8),
|
|
TensorInfo(TensorShape(14U, 14U, 512U, 5U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(14U, 14U, 512U, 5U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(17U, 23U, 13U, 4U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(8U, 10U, 7U, 7U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(7U, 9U, 7U, 7U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(64U, 64U, 7U, 3U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(64U, 64U, 7U, 3U), 1, DataType::F32)
|
|
})),
|
|
framework::dataset::make("WinogradInfo", {
|
|
WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(14U, 14U), PadStrideInfo(1, 1, 1, 1), DataLayout::NCHW),
|
|
WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(14U, 14U), PadStrideInfo(1, 1, 1, 1), DataLayout::NCHW),
|
|
WinogradInfo(Size2D(2U, 2U), Size2D(5U, 5U), Size2D(14U, 14U), PadStrideInfo(1, 1, 1, 1), DataLayout::NCHW),
|
|
WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(14U, 14U), PadStrideInfo(1, 1, 1, 1), DataLayout::NCHW),
|
|
WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(17U, 23U), PadStrideInfo(1, 1, 1, 1), DataLayout::NCHW),
|
|
WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(8U, 10U), PadStrideInfo(1, 1, 1, 1), DataLayout::NCHW),
|
|
WinogradInfo(Size2D(2U, 3U), Size2D(3U, 3U), Size2D(8U, 10U), PadStrideInfo(1, 1, 0, 0), DataLayout::NCHW),
|
|
WinogradInfo(Size2D(4U, 4U), Size2D(3U, 3U), Size2D(64U, 64U), PadStrideInfo(1, 1, 1, 1), DataLayout::NCHW),
|
|
WinogradInfo(Size2D(4U, 4U), Size2D(3U, 3U), Size2D(64U, 64U), PadStrideInfo(1, 1, 1, 1), DataLayout::NCHW)
|
|
})),
|
|
framework::dataset::make("Expected", { true, false, false, true, false, true, false, true, false })),
|
|
input_info, bias_info, output_info, winograd_info, expected)
|
|
{
|
|
ARM_COMPUTE_EXPECT(bool(CLWinogradOutputTransformKernel::validate(&input_info.clone()->set_is_resizable(false), &bias_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), winograd_info)) == expected, framework::LogLevel::ERRORS);
|
|
}
|
|
|
|
using CLWinogradOutputTransform = CLSynthetizeFunctionWithZeroConstantBorder<CLWinogradOutputTransformKernel, 0>;
|
|
using CLWinogradOutputTransformFixtureFP32 = WinogradOutputTransformValidationFixture<CLTensor, CLAccessor, CLWinogradOutputTransform, float>;
|
|
using CLWinogradOutputTransformFixtureFP16 = WinogradOutputTransformValidationFixture<CLTensor, CLAccessor, CLWinogradOutputTransform, half>;
|
|
|
|
TEST_SUITE(NCHW)
|
|
TEST_SUITE(FP16)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradOutputTransformFixtureFP16, framework::DatasetMode::ALL,
|
|
combine(combine(SmallWinogradOutputTransformDatasetNCHW,
|
|
framework::dataset::make("DataType", { DataType::F16 })),
|
|
framework::dataset::make("ActivationInfo",{ ActivationLayerInfo() }) ))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_f16);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradOutputTransformFixtureFP16, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(LargeWinogradOutputTransformDatasetNCHW,
|
|
framework::dataset::make("DataType", { DataType::F16 })),
|
|
framework::dataset::make("ActivationInfo",{ ActivationLayerInfo() }) ))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_f16);
|
|
}
|
|
TEST_SUITE_END() // FP16
|
|
TEST_SUITE(FP32)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradOutputTransformFixtureFP32, framework::DatasetMode::ALL,
|
|
combine(combine(SmallWinogradOutputTransformDatasetNCHW,
|
|
framework::dataset::make("DataType", { DataType::F32 })),
|
|
framework::dataset::make("ActivationInfo",{ ActivationLayerInfo() }) ))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_f32);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradOutputTransformFixtureFP32, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(LargeWinogradOutputTransformDatasetNCHW,
|
|
framework::dataset::make("DataType", { DataType::F32 })),
|
|
framework::dataset::make("ActivationInfo",{ ActivationLayerInfo() }) ))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_f32);
|
|
}
|
|
TEST_SUITE_END() // FP32
|
|
TEST_SUITE_END() // NCHW
|
|
|
|
TEST_SUITE(NHWC)
|
|
TEST_SUITE(FP16)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradOutputTransformFixtureFP16, framework::DatasetMode::ALL,
|
|
combine(combine(SmallWinogradOutputTransformDatasetNHWC_F16,
|
|
framework::dataset::make("DataType", { DataType::F16 })),
|
|
framework::dataset::make("ActivationInfo",{ ActivationLayerInfo() }) ))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num_f16);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradOutputTransformFixtureFP16, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(LargeWinogradOutputTransformDatasetNHWC_F16,
|
|
framework::dataset::make("DataType", { DataType::F16 })),
|
|
framework::dataset::make("ActivationInfo",{ ActivationLayerInfo() }) ))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num_f16);
|
|
}
|
|
TEST_SUITE_END() // FP16
|
|
TEST_SUITE(FP32)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradOutputTransformFixtureFP32, framework::DatasetMode::ALL,
|
|
combine(combine(SmallWinogradOutputTransformDatasetNHWC_F32,
|
|
framework::dataset::make("DataType", { DataType::F32 })),
|
|
framework::dataset::make("ActivationInfo",{ ActivationLayerInfo() }) ))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_f32);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradOutputTransformFixtureFP32, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(LargeWinogradOutputTransformDatasetNHWC_F32,
|
|
framework::dataset::make("DataType", { DataType::F32 })),
|
|
framework::dataset::make("ActivationInfo",{ ActivationLayerInfo() }) ))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_f32);
|
|
}
|
|
TEST_SUITE_END() // FP32
|
|
TEST_SUITE_END() // NHWC
|
|
TEST_SUITE_END() // OutputTransform
|
|
|
|
TEST_SUITE(ConvolutionLayer)
|
|
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(
|
|
framework::dataset::make("InputInfo", {
|
|
TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F16), // Insufficient padding
|
|
TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32), // Datatype mismatch
|
|
TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32), // Stride y not supported
|
|
TensorInfo(TensorShape(16U, 16U, 8U), 1, DataType::F32), // Padding needed
|
|
TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32) // Kernel size not supported
|
|
}),
|
|
framework::dataset::make("WeightsInfo", {
|
|
TensorInfo(TensorShape(3U, 3U, 2U, 19U), 1, DataType::F16),
|
|
TensorInfo(TensorShape(3U, 3U, 2U, 19U), 1, DataType::QASYMM8),
|
|
TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(3U, 3U, 8U, 16U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16)
|
|
})),
|
|
framework::dataset::make("BiasesInfo", {
|
|
TensorInfo(TensorShape(19U), 1, DataType::F16),
|
|
TensorInfo(TensorShape(19U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(21U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(16U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(16U), 1, DataType::F32)
|
|
})),
|
|
framework::dataset::make("OutputInfo", {
|
|
TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::F16),
|
|
TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(16U, 16U, 16U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(11U, 12U, 16U, 4U), 1, DataType::F32)
|
|
})),
|
|
framework::dataset::make("ConvInfo", {
|
|
PadStrideInfo(1, 1, 1, 1),
|
|
PadStrideInfo(1, 1, 1, 1),
|
|
PadStrideInfo(1, 2, 0, 0),
|
|
PadStrideInfo(1, 1, 1, 1),
|
|
PadStrideInfo(1, 1, 1, 0)
|
|
})),
|
|
framework::dataset::make("Expected", { false, false, false, false, false })),
|
|
input_info, weights_info, bias_info, output_info, conv_info, expected)
|
|
{
|
|
ARM_COMPUTE_EXPECT(bool(CLWinogradConvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &bias_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info)) == expected, framework::LogLevel::ERRORS);
|
|
}
|
|
|
|
TEST_SUITE(FP32)
|
|
using CLWinogradConvolutionLayerFastMathFixture = WinogradConvolutionLayerFastMathValidationFixture<CLTensor, CLAccessor, CLWinogradConvolutionLayer, float>;
|
|
TEST_SUITE(Conv3x3)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::PRECOMMIT,
|
|
combine(combine(combine(datasets::SmallWinogradConvolutionLayer3x3Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F32 })),
|
|
ActivationFunctionsSmallDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(combine(datasets::LargeWinogradConvolutionLayer3x3Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F32 })),
|
|
ActivationFunctionsDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
|
|
}
|
|
TEST_SUITE_END() // Conv3x3
|
|
|
|
TEST_SUITE(Conv3x1)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::PRECOMMIT,
|
|
combine(combine(combine(datasets::SmallWinogradConvolutionLayer3x1Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F32 })),
|
|
ActivationFunctionsSmallDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(combine(datasets::LargeWinogradConvolutionLayer3x1Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F32 })),
|
|
ActivationFunctionsDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
|
|
}
|
|
TEST_SUITE_END() // Conv3x1
|
|
|
|
TEST_SUITE(Conv1x3)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::PRECOMMIT,
|
|
combine(combine(combine(datasets::SmallWinogradConvolutionLayer1x3Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F32 })),
|
|
ActivationFunctionsSmallDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(combine(datasets::LargeWinogradConvolutionLayer1x3Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F32 })),
|
|
ActivationFunctionsDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
|
|
}
|
|
TEST_SUITE_END() // Conv1x3
|
|
|
|
TEST_SUITE(Conv5x5)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::PRECOMMIT,
|
|
combine(combine(combine(datasets::SmallWinogradConvolutionLayer5x5Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F32 })),
|
|
ActivationFunctionsSmallDataset ),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(combine(datasets::LargeWinogradConvolutionLayer5x5Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F32 })),
|
|
ActivationFunctionsDataset ),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
|
|
}
|
|
TEST_SUITE_END() // Conv5x5
|
|
|
|
TEST_SUITE(Conv5x1)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::PRECOMMIT,
|
|
combine(combine(combine(datasets::SmallWinogradConvolutionLayer5x1Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F32 })),
|
|
ActivationFunctionsSmallDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(combine(datasets::LargeWinogradConvolutionLayer5x1Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F32 })),
|
|
ActivationFunctionsDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
|
|
}
|
|
TEST_SUITE_END() // Conv5x1
|
|
|
|
TEST_SUITE(Conv1x5)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::PRECOMMIT,
|
|
combine(combine(combine(datasets::SmallWinogradConvolutionLayer1x5Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F32 })),
|
|
ActivationFunctionsSmallDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(combine(datasets::LargeWinogradConvolutionLayer1x5Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F32 })),
|
|
ActivationFunctionsDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
|
|
}
|
|
TEST_SUITE_END() // Conv1x5
|
|
TEST_SUITE_END() // FP32
|
|
|
|
|
|
TEST_SUITE(FP16)
|
|
|
|
using CLWinogradConvolutionLayerFastMathFixture16 = WinogradConvolutionLayerFastMathValidationFixture<CLTensor, CLAccessor, CLWinogradConvolutionLayer, half, float>;
|
|
TEST_SUITE(Conv3x3)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::PRECOMMIT,
|
|
combine(combine(combine(datasets::SmallWinogradConvolutionLayer3x3Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F16 })),
|
|
ActivationFunctionsSmallDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_f16);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(combine(datasets::LargeWinogradConvolutionLayer3x3Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F16 })),
|
|
ActivationFunctionsDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_convolution_layer_f16);
|
|
}
|
|
TEST_SUITE_END() // Conv3x3
|
|
|
|
TEST_SUITE(Conv3x1)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::PRECOMMIT,
|
|
combine(combine(combine(datasets::SmallWinogradConvolutionLayer3x1Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F16 })),
|
|
ActivationFunctionsSmallDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_f16);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(combine(datasets::LargeWinogradConvolutionLayer3x1Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F16 })),
|
|
ActivationFunctionsDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_convolution_layer_f16);
|
|
}
|
|
TEST_SUITE_END() // Conv3x1
|
|
|
|
TEST_SUITE(Conv1x3)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::PRECOMMIT,
|
|
combine(combine(combine(datasets::SmallWinogradConvolutionLayer1x3Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F16 })),
|
|
ActivationFunctionsSmallDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_f16);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(combine(datasets::LargeWinogradConvolutionLayer1x3Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F16 })),
|
|
ActivationFunctionsDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_convolution_layer_f16);
|
|
}
|
|
TEST_SUITE_END() // Conv1x3
|
|
|
|
TEST_SUITE(Conv5x5)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::PRECOMMIT,
|
|
combine(combine(combine(datasets::SmallWinogradConvolutionLayer5x5Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F16 })),
|
|
ActivationFunctionsSmallDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_f16);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(combine(datasets::LargeWinogradConvolutionLayer5x5Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F16 })),
|
|
ActivationFunctionsDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_convolution_layer_f16);
|
|
}
|
|
TEST_SUITE_END() // Conv5x5
|
|
|
|
TEST_SUITE(Conv5x1)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::PRECOMMIT,
|
|
combine(combine(combine(datasets::SmallWinogradConvolutionLayer5x1Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F16 })),
|
|
ActivationFunctionsSmallDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_f16);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(combine(datasets::LargeWinogradConvolutionLayer5x1Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F16 })),
|
|
ActivationFunctionsDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_convolution_layer_f16);
|
|
}
|
|
TEST_SUITE_END() // Conv5x1
|
|
|
|
TEST_SUITE(Conv1x5)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::PRECOMMIT,
|
|
combine(combine(combine(datasets::SmallWinogradConvolutionLayer1x5Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F16 })),
|
|
ActivationFunctionsSmallDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_f16);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(combine(datasets::LargeWinogradConvolutionLayer1x5Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F16 })),
|
|
ActivationFunctionsDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
|
|
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_convolution_layer_f16);
|
|
}
|
|
TEST_SUITE_END() // Conv1x5
|
|
|
|
TEST_SUITE(Conv1x7)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::PRECOMMIT,
|
|
combine(combine(combine(datasets::SmallWinogradConvolutionLayer1x7Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F16 })),
|
|
ActivationFunctionsSmallDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NHWC })))
|
|
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_f16);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(combine(datasets::LargeWinogradConvolutionLayer1x7Dataset(),
|
|
framework::dataset::make("DataType", { DataType::F16 })),
|
|
ActivationFunctionsDataset),
|
|
framework::dataset::make("DataLayout", { DataLayout::NHWC })))
|
|
|
|
{
|
|
// Validate output
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_convolution_layer_f16);
|
|
}
|
|
TEST_SUITE_END() // Conv1x7
|
|
|
|
TEST_SUITE_END() // FP16
|
|
|
|
TEST_SUITE_END() // ConvolutionLayer
|
|
TEST_SUITE_END() // Winograd
|
|
TEST_SUITE_END() // CL
|
|
} // namespace validation
|
|
} // namespace test
|
|
} // namespace arm_compute
|