diff options
| 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 | |
| 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')
| -rw-r--r-- | tests/validation/NEON/ConvolutionLayer.cpp | 59 | ||||
| -rw-r--r-- | tests/validation/fixtures/WinogradConvolutionLayerFixture.h | 16 |
2 files changed, 44 insertions, 31 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, diff --git a/tests/validation/fixtures/WinogradConvolutionLayerFixture.h b/tests/validation/fixtures/WinogradConvolutionLayerFixture.h index e15931eafb..ef596e0bae 100644 --- a/tests/validation/fixtures/WinogradConvolutionLayerFixture.h +++ b/tests/validation/fixtures/WinogradConvolutionLayerFixture.h @@ -153,7 +153,7 @@ protected: SimpleTensor<T> _reference{}; }; -template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool use_bias = true> class WinogradConvolutionLayerFastMathValidationFixture : public framework::Fixture { public: @@ -198,8 +198,9 @@ protected: // Create and configure function FunctionType conv; - ARM_COMPUTE_EXPECT(static_cast<bool>(conv.validate(src.info(), weights.info(), bias.info(), dst.info(), info, act_info, true /* Enable fast math */)), framework::LogLevel::ERRORS); - conv.configure(&src, &weights, &bias, &dst, info, act_info, true /* Enable fast math */); + ARM_COMPUTE_EXPECT(static_cast<bool>(conv.validate(src.info(), weights.info(), (use_bias) ? bias.info() : nullptr, dst.info(), info, act_info, true /* Enable fast math */)), + framework::LogLevel::ERRORS); + conv.configure(&src, &weights, (use_bias) ? &bias : nullptr, &dst, info, act_info, true /* Enable fast math */); ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS); @@ -239,7 +240,14 @@ protected: // Fill reference fill(src, 0, -1.f, 1.f); fill(weights, 1, -1.f, 1.f); - fill(bias, 2, -1.f, 1.f); + if(use_bias) + { + fill(bias, 2, -1.f, 1.f); + } + else + { + fill(bias, 2, 0.f, 0.f); + } WinogradInfo winograd_info(Size2D(4U, 4U), Size2D(weights_shape[0], weights_shape[1]), |