| /* |
| * Copyright (c) 2018-2021 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/Helpers.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| #include "arm_compute/runtime/CL/CLTensor.h" |
| #include "arm_compute/runtime/CL/CLTensorAllocator.h" |
| #include "arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h" |
| #include "tests/CL/CLAccessor.h" |
| #include "tests/CL/Helper.h" |
| #include "tests/PaddingCalculator.h" |
| #include "tests/datasets/LargeConvolutionLayerDataset.h" |
| #include "tests/datasets/ShapeDatasets.h" |
| #include "tests/datasets/SmallConvolutionLayerDataset.h" |
| #include "tests/datasets/WinogradInputTransformDataset.h" |
| #include "tests/datasets/WinogradOutputTransformDataset.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/WinogradConvolutionLayerFixture.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace |
| { |
| // *INDENT-OFF* |
| // clang-format off |
| const AbsoluteTolerance<half> tolerance_f16(half(1.f)); |
| constexpr AbsoluteTolerance<float> tolerance_convolution_layer_f32(0.1f); |
| const AbsoluteTolerance<half> tolerance_convolution_layer_f16(half(0.4f)); |
| 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 */ |
| constexpr float tolerance_num = 0.05f; /**< Tolerance number */ |
| constexpr float abs_tolerance_convolution_layer_f16 = 2.5f; /**< Tolerance number */ |
| constexpr float tolerance_num_f16 = 0.15f; /**< Tolerance number */ |
| |
| //Activation Functions |
| const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", |
| { |
| ActivationLayerInfo(), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LEAKY_RELU) |
| }); |
| const auto ActivationFunctionsSmallDataset = framework::dataset::make("ActivationInfo", |
| { |
| ActivationLayerInfo(), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LEAKY_RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::SOFT_RELU) |
| }); |
| |
| } // namespace |
| |
| using namespace arm_compute::misc::shape_calculator; |
| |
| TEST_SUITE(CL) |
| TEST_SUITE(Winograd) |
| |
| 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>; |
| using CLWinogradConvolutionLayerFastMathMixedDataLayoutFixture = WinogradConvolutionLayerFastMathValidationFixture<CLTensor, CLAccessor, CLWinogradConvolutionLayer, float, float, true, true>; |
| 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(RunMixedDataLayout, CLWinogradConvolutionLayerFastMathMixedDataLayoutFixture, framework::DatasetMode::PRECOMMIT, |
| combine(combine(combine(combine(combine(combine(combine(combine( |
| framework::dataset::make("Input", TensorShape(8U, 8U, 32U)), |
| framework::dataset::make("Weight", TensorShape(1U, 3U, 32U, 1U))), |
| framework::dataset::make("Bias", TensorShape(1U))), |
| framework::dataset::make("Output", TensorShape(8U, 6U, 1U))), |
| framework::dataset::make("PadStrideInfo", PadStrideInfo(1, 1, 0, 0))), |
| framework::dataset::make("Dilation", Size2D(1U, 1U))), |
| 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 |
