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| author | Gian Marco Iodice <gianmarco.iodice@arm.com> | 2018-07-03 12:22:09 +0100 |
|---|---|---|
| committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:54:10 +0000 |
| commit | 876be2a0d11874d871860dbd22481f831d6878f6 (patch) | |
| tree | 907afac009513f882b39b2770b187635cebd1664 /tests/validation/CL/Winograd.cpp | |
| parent | 09daf4ddf5940d18ce95e7dd0859d1dace3b133e (diff) | |
| download | ComputeLibrary-876be2a0d11874d871860dbd22481f831d6878f6.tar.gz | |
COMPMID-1339 - Implementing Winograd Convolution Layer 1x5 and 5x1 kernels on OpenCL NCHW
Change-Id: Ia293cd89651146a0e27e5f7c74ca9c924807e83c
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/138707
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Diffstat (limited to 'tests/validation/CL/Winograd.cpp')
| -rw-r--r-- | tests/validation/CL/Winograd.cpp | 64 |
1 files changed, 60 insertions, 4 deletions
diff --git a/tests/validation/CL/Winograd.cpp b/tests/validation/CL/Winograd.cpp index 501afaccf9..849d0c13bc 100644 --- a/tests/validation/CL/Winograd.cpp +++ b/tests/validation/CL/Winograd.cpp @@ -65,7 +65,9 @@ const auto SmallWinogradInputTransformDatasetNCHW = framework::dataset::concat(datasets::SmallWinogradInputTransformDataset4x4_3x3(), framework::dataset::concat(datasets::SmallWinogradInputTransformDataset4x1_3x1(), framework::dataset::concat(datasets::SmallWinogradInputTransformDataset1x4_1x3(), - datasets::SmallWinogradInputTransformDataset4x4_5x5())))))); + framework::dataset::concat(datasets::SmallWinogradInputTransformDataset4x4_5x5(), + framework::dataset::concat(datasets::SmallWinogradInputTransformDataset4x1_5x1(), + datasets::SmallWinogradInputTransformDataset1x4_1x5())))))))); const auto SmallWinogradInputTransformDatasetNHWC = framework::dataset::concat(datasets::SmallWinogradInputTransformDataset4x4_3x3(), datasets::SmallWinogradInputTransformDataset4x4_5x5()); @@ -77,7 +79,9 @@ const auto LargeWinogradInputTransformDatasetNCHW = framework::dataset::concat(datasets::LargeWinogradInputTransformDataset4x4_3x3(), framework::dataset::concat(datasets::LargeWinogradInputTransformDataset4x1_3x1(), framework::dataset::concat(datasets::LargeWinogradInputTransformDataset1x4_1x3(), - datasets::LargeWinogradInputTransformDataset4x4_5x5())))))); + framework::dataset::concat(datasets::LargeWinogradInputTransformDataset4x4_5x5(), + framework::dataset::concat(datasets::LargeWinogradInputTransformDataset4x1_5x1(), + datasets::LargeWinogradInputTransformDataset1x4_1x5())))))))); const auto LargeWinogradInputTransformDatasetNHWC = framework::dataset::concat(datasets::LargeWinogradInputTransformDataset4x4_3x3(), @@ -88,7 +92,9 @@ const auto SmallWinogradFilterTransformDatasetNCHW = framework::dataset::concat(combine(datasets::Small3x3Shapes(), framework::dataset::make("OutputTile", { Size2D(2U, 2U), Size2D(4U, 4U) })), framework::dataset::concat(combine(datasets::Small3x1Shapes(), framework::dataset::make("OutputTile", { Size2D(2U, 1U), Size2D(4U, 1U) })), framework::dataset::concat(combine(datasets::Small1x3Shapes(), framework::dataset::make("OutputTile", { Size2D(1U, 2U), Size2D(1U, 4U) })), - combine(datasets::Small5x5Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 4U) }))))); + framework::dataset::concat(combine(datasets::Small5x5Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 4U) })), + framework::dataset::concat(combine(datasets::Small5x1Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 1U) })), + combine(datasets::Small1x5Shapes(), framework::dataset::make("OutputTile", { Size2D(1U, 4U) }))))))); const auto SmallWinogradFilterTransformDatasetNHWC = framework::dataset::concat(combine(datasets::Small3x3Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 4U) })), @@ -98,7 +104,9 @@ const auto LargeWinogradFilterTransformDatasetNCHW = framework::dataset::concat(combine(datasets::Large3x3Shapes(), framework::dataset::make("OutputTile", { Size2D(2U, 2U), Size2D(4U, 4U) })), framework::dataset::concat(combine(datasets::Large3x1Shapes(), framework::dataset::make("OutputTile", { Size2D(2U, 1U), Size2D(4U, 1U) })), framework::dataset::concat(combine(datasets::Large1x3Shapes(), framework::dataset::make("OutputTile", { Size2D(1U, 2U), Size2D(1U, 4U) })), - combine(datasets::Large5x5Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 4U) }))))); + framework::dataset::concat(combine(datasets::Large5x5Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 4U) })), + framework::dataset::concat(combine(datasets::Large5x1Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 1U) })), + combine(datasets::Large1x5Shapes(), framework::dataset::make("OutputTile", { Size2D(1U, 4U) }))))))); const auto LargeWinogradFilterTransformDatasetNHWC = framework::dataset::concat(combine(datasets::Large3x3Shapes(), framework::dataset::make("OutputTile", { Size2D(4U, 4U) })), @@ -643,6 +651,54 @@ FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture, fram } 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 })), + framework::dataset::make("ActivationLayerInfo", { ActivationLayerInfo() })), + framework::dataset::make("DataLayout", { DataLayout::NCHW }))) + +{ + // 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 })), + framework::dataset::make("ActivationLayerInfo", { ActivationLayerInfo() })), + framework::dataset::make("DataLayout", { DataLayout::NCHW }))) + +{ + // 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 })), + framework::dataset::make("ActivationLayerInfo", { ActivationLayerInfo() })), + framework::dataset::make("DataLayout", { DataLayout::NCHW }))) + +{ + // 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 })), + framework::dataset::make("ActivationLayerInfo", { ActivationLayerInfo() })), + framework::dataset::make("DataLayout", { DataLayout::NCHW }))) + +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32); +} +TEST_SUITE_END() // Conv1x5 + TEST_SUITE_END() // ConvolutionLayer TEST_SUITE_END() // Winograd TEST_SUITE_END() // CL |