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| author | Giorgio Arena <giorgio.arena@arm.com> | 2018-05-03 15:57:48 +0100 |
|---|---|---|
| committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:52:35 +0000 |
| commit | a3221e6772dc371cf5de7e525bf5c22b58ad6d08 (patch) | |
| tree | 14d224e07d92dbbd97966de0b6b0aa8e6a288022 /tests/validation/NEON/ConvolutionLayer.cpp | |
| parent | 20b4313365ea2ed31f59fd757f68f791f076e6bc (diff) | |
| download | ComputeLibrary-a3221e6772dc371cf5de7e525bf5c22b58ad6d08.tar.gz | |
COMPMID-1106 Add fast math support in NEWinogradConvolutionLayer
Change-Id: I5fcbbb3b6f22204f0aaebbc319dfdf03593577e8
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/130067
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Diffstat (limited to 'tests/validation/NEON/ConvolutionLayer.cpp')
| -rw-r--r-- | tests/validation/NEON/ConvolutionLayer.cpp | 59 |
1 files changed, 32 insertions, 27 deletions
diff --git a/tests/validation/NEON/ConvolutionLayer.cpp b/tests/validation/NEON/ConvolutionLayer.cpp index 330480e4d8..9043d582d4 100644 --- a/tests/validation/NEON/ConvolutionLayer.cpp +++ b/tests/validation/NEON/ConvolutionLayer.cpp @@ -76,43 +76,48 @@ const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo TEST_SUITE(NEON) TEST_SUITE(ConvolutionLayer) -DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip( - framework::dataset::make("InputInfo", { TensorInfo(TensorShape(8U, 8U, 2U), 1, DataType::F32, 0), - TensorInfo(TensorShape(23U, 27U, 32U, 4U), 1, DataType::F32, 0), - TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32, 0), - TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32, 0) - }), - framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), - TensorInfo(TensorShape(3U, 3U, 32U, 21U), 1, DataType::F32, 0), - TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), - TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16, 0) - })), - framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(6U, 6U, 1U), 1, DataType::F32, 0), - TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32, 0), - TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0), - TensorInfo(TensorShape(11U, 12U, 16U, 4U), 1, DataType::F32, 0) - })), - framework::dataset::make("ConvInfo", { PadStrideInfo(1, 1, 0, 0), - PadStrideInfo(1, 1, 0, 0), - PadStrideInfo(2, 1, 0, 0), - PadStrideInfo(3, 2, 1, 0) +DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( + framework::dataset::make("InputInfo", { TensorInfo(TensorShape(18U, 18U, 32U), 1, DataType::F32, 0), + TensorInfo(TensorShape(23U, 27U, 32U, 4U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32, 0), + TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32, 0) + }), + framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 32U, 21U), 1, DataType::F32, 0), + TensorInfo(TensorShape(5U, 5U, 32U, 21U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), + TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16, 0) + })), + framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(16U, 16U, 21U), 1, DataType::F32, 0), + TensorInfo(TensorShape(19U, 23U, 21U, 4U), 1, DataType::F32, 0), + TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0), + TensorInfo(TensorShape(11U, 12U, 16U, 4U), 1, DataType::F32, 0) + })), + framework::dataset::make("ConvInfo", { PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(2, 1, 0, 0), + PadStrideInfo(3, 2, 1, 0) + })), + framework::dataset::make("FastMath", { true, + true, + false, + false })), - framework::dataset::make("Expected", { ConvolutionMethod::GEMM, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM })), - input_info, weights_info, output_info, conv_info, expected) + framework::dataset::make("Expected", { ConvolutionMethod::WINOGRAD, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM })), + input_info, weights_info, output_info, conv_info, fast_math, expected) { - ConvolutionMethod is_valid = NEConvolutionLayer::get_convolution_method(&input_info.clone()->set_is_resizable(false), - &weights_info.clone()->set_is_resizable(false), - &output_info.clone()->set_is_resizable(false), conv_info); + ConvolutionMethod is_valid = NEConvolutionLayer::get_convolution_method(&input_info.clone()->set_is_resizable(true), + &weights_info.clone()->set_is_resizable(true), + &output_info.clone()->set_is_resizable(true), conv_info, WeightsInfo(), Size2D(1U, 1U), ActivationLayerInfo(), fast_math); ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); } TEST_SUITE_END() TEST_SUITE(WinogradLayer) template <typename T> -using NEWinogradConvolutionLayerFixture = WinogradConvolutionLayerValidationFixture<Tensor, Accessor, NEWinogradConvolutionLayer, T>; +using NEWinogradConvolutionLayerFixture = WinogradConvolutionLayerFastMathValidationFixture<Tensor, Accessor, NEWinogradConvolutionLayer, T>; template <typename T> -using NEWinogradConvolutionLayerNoBiasFixture = WinogradConvolutionLayerValidationFixture<Tensor, Accessor, NEWinogradConvolutionLayer, T, false>; +using NEWinogradConvolutionLayerNoBiasFixture = WinogradConvolutionLayerFastMathValidationFixture<Tensor, Accessor, NEWinogradConvolutionLayer, T, false>; TEST_SUITE(FP32) FIXTURE_DATA_TEST_CASE(RunSmall, NEWinogradConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, |