From ca62c6f53eb7244e6fed9f7e932608aa2496d9eb Mon Sep 17 00:00:00 2001 From: Manuel Bottini Date: Tue, 23 Mar 2021 11:50:34 +0000 Subject: Mixed data-layout testing on high priority operators Change data layouts after the configure in validation tests for: - Scale - Pooling - FullyConnected - DepthwiseConvolution - DirectConvolution - FFTConvolution - WinogradConvolution - GEMMConvolution (Indirect GEMM included) Extending fixtures Fixes for new mixed data layout tests Resolves: COMPMID-4162 Change-Id: I2f2eb2075f7e24ab3872249d88cadb57b82c5dde Signed-off-by: Manuel Bottini Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5326 Comments-Addressed: Arm Jenkins Tested-by: Arm Jenkins Reviewed-by: Georgios Pinitas --- .../fixtures/WinogradConvolutionLayerFixture.h | 241 ++++++++++----------- 1 file changed, 117 insertions(+), 124 deletions(-) (limited to 'tests/validation/fixtures/WinogradConvolutionLayerFixture.h') diff --git a/tests/validation/fixtures/WinogradConvolutionLayerFixture.h b/tests/validation/fixtures/WinogradConvolutionLayerFixture.h index 03ec920c4e..f956963e14 100644 --- a/tests/validation/fixtures/WinogradConvolutionLayerFixture.h +++ b/tests/validation/fixtures/WinogradConvolutionLayerFixture.h @@ -51,130 +51,38 @@ namespace validation { using namespace arm_compute::misc::shape_calculator; -template -class WinogradConvolutionLayerValidationFixture : public framework::Fixture +template +class WinogradConvolutionLayerFastMathValidationFixture : public framework::Fixture { public: template void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, - DataType data_type, ActivationLayerInfo act_info) + DataType data_type, ActivationLayerInfo act_info, const DataLayout &data_layout) + { ARM_COMPUTE_UNUSED(dilation); - - _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, act_info); - _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, act_info); + _mixed_layout = mixed_layout; + _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, act_info, data_layout); + _reference = compute_reference(input_shape, weights_shape, bias_shape, info, data_type, act_info); } protected: - template - void fill(U &&tensor, int i, float min, float max) - { - switch(tensor.data_type()) - { - case DataType::F16: - { - arm_compute::utils::uniform_real_distribution_16bit distribution{ float(min), float(max) }; - library->fill(tensor, distribution, i); - break; - } - case DataType::F32: - { - std::uniform_real_distribution distribution(min, max); - library->fill(tensor, distribution, i); - break; - } - default: - { - ARM_COMPUTE_ERROR("Not supported"); - } - } - } - TensorType compute_target(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, const PadStrideInfo &info, - DataType data_type, ActivationLayerInfo act_info) + void mix_layout(FunctionType &layer, TensorType &src, TensorType &dst) { - // Create tensors - TensorType src = create_tensor(input_shape, data_type, 1); - TensorType weights = create_tensor(weights_shape, data_type, 1); - TensorType bias = create_tensor(bias_shape, data_type, 1); - TensorType dst = create_tensor(output_shape, data_type, 1); - - // Create and configure function - FunctionType conv; - ARM_COMPUTE_EXPECT(static_cast(conv.validate(src.info(), weights.info(), (use_bias) ? bias.info() : nullptr, dst.info(), info, act_info)), framework::LogLevel::ERRORS); - conv.configure(&src, &weights, (use_bias) ? &bias : nullptr, &dst, info, act_info); - - ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); - - // Allocate tensors - src.allocator()->allocate(); - weights.allocator()->allocate(); - dst.allocator()->allocate(); - bias.allocator()->allocate(); - - ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!weights.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!bias.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); - - // Fill tensors - fill(AccessorType(src), 0, -1.f, 1.f); - fill(AccessorType(weights), 1, -1.f, 1.f); - fill(AccessorType(bias), 2, -1.f, 1.f); - - // Compute Winograd Convolution function - conv.run(); - - return dst; - } - - SimpleTensor compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info, - DataType data_type, ActivationLayerInfo act_info) - { - // Create reference - SimpleTensor src{ input_shape, data_type, 1 }; - SimpleTensor weights{ weights_shape, data_type, 1 }; - SimpleTensor bias{ bias_shape, data_type, 1 }; - - // Fill reference - fill(src, 0, -1.f, 1.f); - fill(weights, 1, -1.f, 1.f); - if(use_bias) - { - fill(bias, 2, -1.f, 1.f); - } - else - { - fill(bias, 2, 0.f, 0.f); - } + const DataLayout data_layout = src.info()->data_layout(); + // Test Multi DataLayout graph cases, when the data layout changes after configure + src.info()->set_data_layout(data_layout == DataLayout::NCHW ? DataLayout::NHWC : DataLayout::NCHW); + dst.info()->set_data_layout(data_layout == DataLayout::NCHW ? DataLayout::NHWC : DataLayout::NCHW); - SimpleTensor conv_out = reference::convolution_layer(src, weights, bias, output_shape, info); - - return (act_info.enabled()) ? reference::activation_layer(conv_out, act_info) : conv_out; - } - - TensorType _target{}; - SimpleTensor _reference{}; -}; + // Compute Convolution function + layer.run(); -template -class WinogradConvolutionLayerFastMathValidationFixture : public framework::Fixture -{ -public: - template - void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, - DataType data_type, ActivationLayerInfo act_info, const DataLayout &data_layout) - - { - ARM_COMPUTE_UNUSED(dilation); - _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, act_info, data_layout); - _reference = compute_reference(input_shape, weights_shape, bias_shape, info, data_type, act_info); + // Reinstating original data layout for the test suite to properly check the values + src.info()->set_data_layout(data_layout); + dst.info()->set_data_layout(data_layout); } -protected: template void fill(U &&tensor, int i, float min, float max) { @@ -242,9 +150,15 @@ protected: fill(AccessorType(weights), 1, -0.5f, 0.5f); fill(AccessorType(bias), 2, -0.5f, 0.5f); - // Compute Winograd Convolution function - conv.run(); - + if(_mixed_layout) + { + mix_layout(conv, src, dst); + } + else + { + // Compute function + conv.run(); + } return dst; } @@ -321,9 +235,10 @@ protected: TensorType _target{}; SimpleTensor _reference{}; + bool _mixed_layout{false}; }; -template +template class WinogradInputTransformValidationFixture : public framework::Fixture { public: @@ -331,12 +246,30 @@ public: void setup(TensorShape input_shape, WinogradInfo winograd_info, DataLayout data_layout, DataType data_type) { TensorShape output_shape = compute_winograd_input_transform_shape(TensorInfo(input_shape, 1, data_type), winograd_info); - + _mixed_layout = mixed_layout; _target = compute_target(input_shape, output_shape, winograd_info, data_layout, data_type); _reference = compute_reference(input_shape, output_shape, winograd_info, data_type); } protected: + + void mix_layout(FunctionType &layer, TensorType &src, TensorType &dst) + { + const DataLayout data_layout_src = src.info()->data_layout(); + const DataLayout data_layout_dst = dst.info()->data_layout(); + + // Test Multi DataLayout graph cases, when the data layout changes after configure + src.info()->set_data_layout(data_layout_src == DataLayout::NCHW ? DataLayout::NHWC : DataLayout::NCHW); + dst.info()->set_data_layout(data_layout_dst == DataLayout::NCHW ? DataLayout::NHWC : DataLayout::NCHW); + + // Compute Convolution function + layer.run(); + + // Reinstating original data layout for the test suite to properly check the values + src.info()->set_data_layout(data_layout_src); + dst.info()->set_data_layout(data_layout_dst); + } + template void fill(U &&tensor, int i, float min, float max) { @@ -388,9 +321,15 @@ protected: // Fill tensors fill(AccessorType(src), 0, -1.f, 1.f); - // Compute Winograd input transform function - transf.run(); - + if(_mixed_layout) + { + mix_layout(transf, src, dst); + } + else + { + // Compute Winograd input transform function + transf.run(); + } return dst; } @@ -405,11 +344,12 @@ protected: return reference::winograd_input_transform(src, output_shape, winograd_info); } + bool _mixed_layout {false}; TensorType _target{}; SimpleTensor _reference{}; }; -template +template class WinogradFilterTransformValidationFixture : public framework::Fixture { public: @@ -419,11 +359,30 @@ public: WinogradInfo winograd_info(output_tile, Size2D(input_shape[0], input_shape[1]), Size2D() /* Not needed */, PadStrideInfo() /* Not needed */, DataLayout::NCHW /* Not needed */); TensorShape output_shape = compute_winograd_filter_transform_shape(TensorInfo(input_shape, 1, data_type), winograd_info); + _mixed_layout = mixed_layout; _target = compute_target(input_shape, output_shape, winograd_info, data_layout, data_type); _reference = compute_reference(input_shape, output_shape, winograd_info, data_type); } protected: + + void mix_layout(FunctionType &layer, TensorType &src, TensorType &dst) + { + const DataLayout data_layout_src = src.info()->data_layout(); + const DataLayout data_layout_dst = dst.info()->data_layout(); + + // Test Multi DataLayout graph cases, when the data layout changes after configure + src.info()->set_data_layout(data_layout_src == DataLayout::NCHW ? DataLayout::NHWC : DataLayout::NCHW); + dst.info()->set_data_layout(data_layout_dst == DataLayout::NCHW ? DataLayout::NHWC : DataLayout::NCHW); + + // Compute Convolution function + layer.run(); + + // Reinstating original data layout for the test suite to properly check the values + src.info()->set_data_layout(data_layout_src); + dst.info()->set_data_layout(data_layout_dst); + } + template void fill(U &&tensor, int i, float min, float max) { @@ -476,8 +435,15 @@ protected: // Fill tensors fill(AccessorType(src), 0, -1.f, 1.f); - filter_transform.run(); - + if(_mixed_layout) + { + mix_layout(filter_transform, src, dst); + } + else + { + // Compute Winograd filter transform function + filter_transform.run(); + } return dst; } @@ -492,11 +458,12 @@ protected: return reference::winograd_filter_transform(src, output_shape, winograd_info); } + bool _mixed_layout {false}; TensorType _target{}; SimpleTensor _reference{}; }; -template +template class WinogradOutputTransformValidationFixture : public framework::Fixture { public: @@ -508,6 +475,24 @@ public: } protected: + + void mix_layout(FunctionType &layer, TensorType &src, TensorType &dst) + { + const DataLayout data_layout_src = src.info()->data_layout(); + const DataLayout data_layout_dst = dst.info()->data_layout(); + + // Test Multi DataLayout graph cases, when the data layout changes after configure + src.info()->set_data_layout(data_layout_src == DataLayout::NCHW ? DataLayout::NHWC : DataLayout::NCHW); + dst.info()->set_data_layout(data_layout_dst == DataLayout::NCHW ? DataLayout::NHWC : DataLayout::NCHW); + + // Compute Convolution function + layer.run(); + + // Reinstating original data layout for the test suite to properly check the values + src.info()->set_data_layout(data_layout_src); + dst.info()->set_data_layout(data_layout_dst); + } + template void fill(U &&tensor, int i, float min, float max) { @@ -562,8 +547,15 @@ protected: fill(AccessorType(src), 0, -1.f, 1.f); fill(AccessorType(bias), 1, -1.f, 1.f); - output_transform.run(); - + if(_mixed_layout) + { + mix_layout(output_transform, src, dst); + } + else + { + // Compute Winograd output transform function + output_transform.run(); + } return dst; } @@ -585,10 +577,11 @@ protected: return (act_info.enabled()) ? reference::activation_layer(winograd_output, act_info) : winograd_output; } + bool _mixed_layout {false}; TensorType _target{}; SimpleTensor _reference{}; }; } // namespace validation } // namespace test } // namespace arm_compute -#endif /* ARM_COMPUTE_TEST_WINOGRAD_LAYER_FIXTURE */ +#endif /* ARM_COMPUTE_TEST_WINOGRAD_LAYER_FIXTURE */ \ No newline at end of file -- cgit v1.2.1