diff options
Diffstat (limited to 'tests/validation/CL/ConvolutionLayer.cpp')
| -rw-r--r-- | tests/validation/CL/ConvolutionLayer.cpp | 291 |
1 files changed, 19 insertions, 272 deletions
diff --git a/tests/validation/CL/ConvolutionLayer.cpp b/tests/validation/CL/ConvolutionLayer.cpp index bced540d2a..986d76708d 100644 --- a/tests/validation/CL/ConvolutionLayer.cpp +++ b/tests/validation/CL/ConvolutionLayer.cpp @@ -22,7 +22,6 @@ * SOFTWARE. */ #include "arm_compute/core/Types.h" -#include "arm_compute/core/experimental/PostOps.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "arm_compute/runtime/CL/CLTensor.h" #include "arm_compute/runtime/CL/CLTensorAllocator.h" @@ -69,53 +68,30 @@ constexpr float tolerance_num = 0.07f; /**< T const auto CNNDataTypes = framework::dataset::make("DataType", { DataType::F16, - DataType::F32, - DataType::QASYMM8, - DataType::QASYMM8_SIGNED, + DataType::F32, + DataType::QASYMM8, + DataType::QASYMM8_SIGNED, }); /** Grouped CNN data types */ const auto GroupedCNNDataTypes = framework::dataset::make("DataType", { DataType::F16, - DataType::F32 + DataType::F32 }); -const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", +const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", { ActivationLayerInfo(), - ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), - ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 0.5f), - ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.5f) + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 0.5f), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.5f) }); const auto ActivationFunctionsSmallDataset = framework::dataset::make("ActivationInfo", { ActivationLayerInfo(), - ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.5f) + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.5f) }); - -bool is_post_op_list_valid_in_gemmconv(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &output_shape, DataType data_type, DataLayout data_layout, - const PadStrideInfo &conv_info, const experimental::PostOpList<ITensorInfo *> &post_ops) -{ - const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); - const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); - const int idx_kernels = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES); - - const auto dilation = Size2D(1U, 1U); - const unsigned int num_groups = 1U; - - TensorInfo input_info(input_shape, 1, data_type, data_layout); - TensorInfo weights_info(weights_shape, 1, data_type, data_layout); - - TensorInfo output_info(output_shape, 1, data_type, data_layout); - - WeightsInfo w_info(false, weights_info.dimension(idx_width), weights_info.dimension(idx_height), weights_info.dimension(idx_kernels)); - - const auto status = CLGEMMConvolutionLayer::validate(&input_info.clone()->set_is_resizable(true), - &weights_info.clone()->set_is_resizable(true), nullptr, &output_info.clone()->set_is_resizable(true), - conv_info, w_info, dilation, ActivationLayerInfo(), num_groups, post_ops); - return bool(status); -} } // namespace TEST_SUITE(CL) @@ -207,72 +183,6 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z enable_fast_math); ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); } - -DATA_TEST_CASE(ValidatePostOpSupportInConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip( - framework::dataset::make("InputInfo", { TensorInfo(TensorShape(2U, 17U, 31U), 1, DataType::F32, DataLayout::NHWC), // Select GEMM - TensorInfo(TensorShape(17U, 31U, 32U), 1, DataType::F32, DataLayout::NCHW), // Select WINOGRAD - TensorInfo(TensorShape(27U, 27U, 48U), 1, DataType::F32, DataLayout::NCHW), // Select Direct - TensorInfo(TensorShape(27U, 27U, 48U), 1, DataType::F32, DataLayout::NCHW), // Select FFT - }), - framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(2U, 1U, 1U, 19U), 1, DataType::F32, DataLayout::NHWC), - TensorInfo(TensorShape(5U, 5U, 32U, 19U), 1, DataType::F32, DataLayout::NCHW), - TensorInfo(TensorShape(5U, 5U, 48U, 128U), 1, DataType::F32, DataLayout::NCHW), - TensorInfo(TensorShape(11U, 11U, 48U, 24), 1, DataType::F32, DataLayout::NCHW), - })), - framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(19U, 17U, 31U), 1, DataType::F32, DataLayout::NHWC), - TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::F32, DataLayout::NCHW), - TensorInfo(TensorShape(27U, 27U, 128U), 1, DataType::F32, DataLayout::NCHW), - TensorInfo(TensorShape(27U, 27U, 24U), 1, DataType::F32, DataLayout::NCHW), - })), - framework::dataset::make("ConvInfo", { PadStrideInfo(1U, 1U, 0U, 0U), - PadStrideInfo(1U, 1U, 2U, 2U), - PadStrideInfo(1U, 1U, 2U, 2U), - PadStrideInfo(1U, 1U, 5U, 5U), - })), - framework::dataset::make("EnableFastMath", { false, true, false, false})), - framework::dataset::make("ExpectedMethod",{ ConvolutionMethod::GEMM, - ConvolutionMethod::WINOGRAD, - ConvolutionMethod::DIRECT, - ConvolutionMethod::FFT, - })), - framework::dataset::make("PostOpSupported",{ true, false, false, false - })), - input_info, weights_info, output_info, conv_info, enable_fast_math, expected_method, post_op_supported) -{ - const int idx_width = get_data_layout_dimension_index(input_info.data_layout(), DataLayoutDimension::WIDTH); - const int idx_height = get_data_layout_dimension_index(input_info.data_layout(), DataLayoutDimension::HEIGHT); - const int idx_kernels = get_data_layout_dimension_index(input_info.data_layout(), DataLayoutDimension::BATCHES); - - const auto dilation = Size2D(1U, 1U); - const unsigned int num_groups = 1U; - - WeightsInfo w_info(false, weights_info.dimension(idx_width), weights_info.dimension(idx_height), weights_info.dimension(idx_kernels)); - - experimental::PostOpList<ITensorInfo*> post_ops{}; - post_ops.push_back_op<experimental::PostOpAct<ITensorInfo*>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::LINEAR, 0.5F, 0.0F}); - - ConvolutionMethod actual_method = CLConvolutionLayer::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(), - ActivationLayerInfo(), - GPUTarget::BIFROST, - dilation, - enable_fast_math); - ARM_COMPUTE_EXPECT(actual_method == expected_method, framework::LogLevel::ERRORS); - const auto is_valid = CLConvolutionLayer::validate(&input_info.clone()->set_is_resizable(true), - &weights_info.clone()->set_is_resizable(true), - nullptr, - &output_info.clone()->set_is_resizable(true), - conv_info, - w_info, - dilation, - ActivationLayerInfo(), - enable_fast_math, - num_groups, - post_ops); - ARM_COMPUTE_EXPECT( bool(is_valid) == post_op_supported, framework::LogLevel::ERRORS); -} // clang-format on // *INDENT-ON* TEST_SUITE_END() // ConvolutionLayer @@ -285,167 +195,11 @@ using CLGEMMConvolutionLayerMixedDataLayoutFixture = ConvolutionValidationFixtur template <typename T> using CLConvolutionValidationWithPaddingFixture = ConvolutionValidationWithPaddingFixture<CLTensor, CLAccessor, CLGEMMConvolutionLayer, T>; -TEST_SUITE(ValidateFusedPostOpsConfigs) -TEST_SUITE(Invalid) -TEST_CASE(UnsupportedPostOpSequence, framework::DatasetMode::ALL) -{ - const auto data_type = DataType::F32; - const auto data_layout = DataLayout::NHWC; - const auto conv_info = PadStrideInfo(1, 1, 0, 0); - const auto input_shape = TensorShape(16U, 14U, 12U, 2U); - const auto weights_shape = TensorShape(16U, 1U, 1U, 24U); - - const auto output_shape = misc::shape_calculator::compute_deep_convolution_shape(input_shape, data_layout, weights_shape, conv_info); - - const TensorShape post_op_arg0_shape(output_shape); - TensorInfo post_op_arg_info(post_op_arg0_shape, 1, data_type); - auto post_op_arg1_info = post_op_arg_info.clone(); - - // Unsupported sequence of post ops - experimental::PostOpList<ITensorInfo *> post_ops{}; - post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo *>>( - &post_op_arg_info, - 1, - ConvertPolicy::SATURATE); - post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo *>>( - post_op_arg1_info.get(), - 0, - ConvertPolicy::SATURATE); - - ARM_COMPUTE_EXPECT(is_post_op_list_valid_in_gemmconv(input_shape, weights_shape, output_shape, data_type, data_layout, conv_info, post_ops) == false, framework::LogLevel::ERRORS); -} -TEST_CASE(OnlyNHWCIsSupported, framework::DatasetMode::ALL) -{ - const auto data_type = DataType::F32; - const auto data_layout = DataLayout::NCHW; - const auto conv_info = PadStrideInfo(1, 1, 0, 0); - const auto input_shape = TensorShape(14U, 12U, 16U, 2U); - const auto weights_shape = TensorShape(1U, 1U, 16U, 24U); - - const auto output_shape = misc::shape_calculator::compute_deep_convolution_shape(input_shape, data_layout, weights_shape, conv_info); - - const TensorShape post_op_arg0_shape(output_shape); - TensorInfo post_op_arg_info(post_op_arg0_shape, 1, data_type); - - experimental::PostOpList<ITensorInfo *> post_ops{}; - post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo *>>( - &post_op_arg_info, - 1, - ConvertPolicy::SATURATE); - - ARM_COMPUTE_EXPECT(is_post_op_list_valid_in_gemmconv(input_shape, weights_shape, output_shape, data_type, data_layout, conv_info, post_ops) == false, framework::LogLevel::ERRORS); -} -TEST_CASE(OnlyFloatingTypeIsSupported, framework::DatasetMode::ALL) -{ - const auto data_type = DataType::QASYMM8; - const auto data_layout = DataLayout::NHWC; - const auto conv_info = PadStrideInfo(1, 1, 0, 0); - const auto input_shape = TensorShape(16U, 14U, 12U, 2U); - const auto weights_shape = TensorShape(16U, 1U, 1U, 24U); - - const auto output_shape = misc::shape_calculator::compute_deep_convolution_shape(input_shape, data_layout, weights_shape, conv_info); - - const TensorShape post_op_arg0_shape(output_shape); - TensorInfo post_op_arg_info(post_op_arg0_shape, 1, data_type); - - experimental::PostOpList<ITensorInfo *> post_ops{}; - post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo *>>( - &post_op_arg_info, - 1, - ConvertPolicy::SATURATE); - - ARM_COMPUTE_EXPECT(is_post_op_list_valid_in_gemmconv(input_shape, weights_shape, output_shape, data_type, data_layout, conv_info, post_ops) == false, framework::LogLevel::ERRORS); -} -TEST_CASE(OnlyConv1x1Stride1IsSupported_UnsupportedKernelSize, framework::DatasetMode::ALL) -{ - const auto data_type = DataType::F32; - const auto data_layout = DataLayout::NHWC; - const auto conv_info = PadStrideInfo(1, 1, 0, 0); - const auto input_shape = TensorShape(16U, 14U, 12U, 2U); - const auto weights_shape = TensorShape(16U, 3U, 3U, 24U); - - const auto output_shape = misc::shape_calculator::compute_deep_convolution_shape(input_shape, data_layout, weights_shape, conv_info); - - const TensorShape post_op_arg0_shape(output_shape); - TensorInfo post_op_arg_info(post_op_arg0_shape, 1, data_type); - - experimental::PostOpList<ITensorInfo *> post_ops{}; - post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo *>>( - &post_op_arg_info, - 1, - ConvertPolicy::SATURATE); - - ARM_COMPUTE_EXPECT(is_post_op_list_valid_in_gemmconv(input_shape, weights_shape, output_shape, data_type, data_layout, conv_info, post_ops) == false, framework::LogLevel::ERRORS); -} -TEST_CASE(OnlyConv1x1Stride1IsSupported_UnsupportedStride, framework::DatasetMode::ALL) -{ - const auto data_type = DataType::F32; - const auto data_layout = DataLayout::NHWC; - const auto conv_info = PadStrideInfo(3, 3, 0, 0); - const auto input_shape = TensorShape(16U, 14U, 12U, 2U); - const auto weights_shape = TensorShape(16U, 1U, 1U, 24U); - - const auto output_shape = misc::shape_calculator::compute_deep_convolution_shape(input_shape, data_layout, weights_shape, conv_info); - - const TensorShape post_op_arg0_shape(output_shape); - TensorInfo post_op_arg_info(post_op_arg0_shape, 1, data_type); - - experimental::PostOpList<ITensorInfo *> post_ops{}; - post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo *>>( - &post_op_arg_info, - 1, - ConvertPolicy::SATURATE); - - ARM_COMPUTE_EXPECT(is_post_op_list_valid_in_gemmconv(input_shape, weights_shape, output_shape, data_type, data_layout, conv_info, post_ops) == false, framework::LogLevel::ERRORS); -} -TEST_SUITE_END() // Invalid -TEST_SUITE(Valid) -TEST_CASE(EmptyPostOpList, framework::DatasetMode::ALL) -{ - const auto data_type = DataType::F32; - const auto data_layout = DataLayout::NHWC; - const auto conv_info = PadStrideInfo(1, 1, 0, 0); - const auto input_shape = TensorShape(16U, 14U, 12U, 2U); - const auto weights_shape = TensorShape(16U, 1U, 1U, 24U); - - const auto output_shape = misc::shape_calculator::compute_deep_convolution_shape(input_shape, data_layout, weights_shape, conv_info); - - experimental::PostOpList<ITensorInfo *> post_ops{}; - - ARM_COMPUTE_EXPECT(is_post_op_list_valid_in_gemmconv(input_shape, weights_shape, output_shape, data_type, data_layout, conv_info, post_ops) == true, framework::LogLevel::ERRORS); -} -TEST_CASE(SupportedPostOps, framework::DatasetMode::ALL) -{ - const auto data_type = DataType::F32; - const auto data_layout = DataLayout::NHWC; - const auto conv_info = PadStrideInfo(1, 1, 0, 0); - const auto input_shape = TensorShape(16U, 14U, 12U, 2U); - const auto weights_shape = TensorShape(16U, 1U, 1U, 24U); - - const auto output_shape = misc::shape_calculator::compute_deep_convolution_shape(input_shape, data_layout, weights_shape, conv_info); - - TensorShape post_op_arg0_shape(output_shape); - post_op_arg0_shape[1] = 1; // Broadcast in "Y" (second) dimension - TensorInfo post_op_arg_info(post_op_arg0_shape, 1, data_type); - - experimental::PostOpList<ITensorInfo *> post_ops{}; - post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo *>>( - &post_op_arg_info, - 1, - ConvertPolicy::SATURATE); - - ARM_COMPUTE_EXPECT(is_post_op_list_valid_in_gemmconv(input_shape, weights_shape, output_shape, data_type, data_layout, conv_info, post_ops) == true, framework::LogLevel::ERRORS); -} -TEST_SUITE_END() // Valid -TEST_SUITE_END() // ValidateFusedPostOps TEST_SUITE(Float) TEST_SUITE(FP16) FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixture<half>, framework::DatasetMode::ALL, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", - DataType::F16)), - framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), + framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), ActivationFunctionsSmallDataset)) { // Validate output @@ -456,10 +210,7 @@ TEST_SUITE_END() // FP16 TEST_SUITE(FP32) FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixture<float>, framework::DatasetMode::ALL, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", - DataType::F32)), - framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), + framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), ActivationFunctionsSmallDataset)) { // Validate output @@ -503,16 +254,16 @@ using CLGEMMConvolutionLayerQuantizedMixedDataLayoutFixture = ConvolutionValidat template <typename T> using CLGEMMConvolutionLayerQuantizedPerChannelFixture = ConvolutionValidationQuantizedPerChannelFixture<CLTensor, CLAccessor, CLGEMMConvolutionLayer, T, int8_t>; -const auto QuantizedActivationFunctionsDataset = framework::dataset::make("ActivationInfo", +const auto QuantizedActivationFunctionsDataset = framework::dataset::make("ActivationInfo", { ActivationLayerInfo(), - ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), - ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f) + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f) }); const auto QuantizedActivationFunctionsSmallDataset = framework::dataset::make("ActivationInfo", { ActivationLayerInfo(), - ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f) + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f) }); TEST_SUITE(Quantized) @@ -520,8 +271,8 @@ TEST_SUITE(Quantized) const auto QuantizationData = framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, 10), - QuantizationInfo(0.3f, 3), - QuantizationInfo(1.1f, 10), + QuantizationInfo(0.3f, 3), + QuantizationInfo(1.1f, 10), }); TEST_SUITE(QASYMM8) @@ -637,9 +388,7 @@ TEST_SUITE(Float) TEST_SUITE(FP32) FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMGroupedConvolutionLayerFixture<float>, framework::DatasetMode::ALL, combine(combine(combine(combine(datasets::SmallGroupedConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", DataType::F32)), - framework::dataset::make("DataLayout", { DataLayout::NCHW })), + framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("DataLayout", { DataLayout::NCHW })), ActivationFunctionsSmallDataset)) { // Validate output @@ -661,9 +410,7 @@ TEST_SUITE_END() // FP32 TEST_SUITE(FP16) FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMGroupedConvolutionLayerFixture<half>, framework::DatasetMode::ALL, combine(combine(combine(combine(datasets::SmallGroupedConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", DataType::F16)), - framework::dataset::make("DataLayout", { DataLayout::NCHW })), + framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("DataLayout", { DataLayout::NCHW })), ActivationFunctionsSmallDataset)) { // Validate output |