diff options
Diffstat (limited to 'tests/validation/fixtures/ConvolutionLayerFixture.h')
| -rw-r--r-- | tests/validation/fixtures/ConvolutionLayerFixture.h | 70 |
1 files changed, 64 insertions, 6 deletions
diff --git a/tests/validation/fixtures/ConvolutionLayerFixture.h b/tests/validation/fixtures/ConvolutionLayerFixture.h index 6dbf3d5731..0b3f070e9c 100644 --- a/tests/validation/fixtures/ConvolutionLayerFixture.h +++ b/tests/validation/fixtures/ConvolutionLayerFixture.h @@ -26,7 +26,9 @@ #include "arm_compute/core/TensorShape.h" #include "arm_compute/core/Types.h" +#include "arm_compute/graph/Utils.h" #include "arm_compute/runtime/NEON/NEScheduler.h" +#include "src/graph/mutators/MutatorUtils.h" #include "tests/AssetsLibrary.h" #include "tests/Globals.h" #include "tests/IAccessor.h" @@ -35,6 +37,7 @@ #include "tests/validation/Helpers.h" #include "tests/validation/reference/ActivationLayer.h" #include "tests/validation/reference/ConvolutionLayer.h" +#include "tests/validation/reference/PadLayer.h" #include "tests/validation/reference/Permute.h" #include "tests/validation/reference/Utils.h" @@ -70,7 +73,7 @@ public: template <typename...> void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, bool reshape_weights, DataType data_type, DataType weights_data_type, DataLayout data_layout, QuantizationInfo quantization_info, QuantizationInfo weight_quantization_info, ActivationLayerInfo act_info, - bool mixed_layout = false) + bool mixed_layout = false, PaddingList pre_pad_layer = PaddingList({})) { _mixed_layout = mixed_layout; _data_type = data_type; @@ -83,8 +86,8 @@ public: _weight_quantization_info = weight_quantization_info; _data_layout = data_layout; - _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, reshape_weights, dilation, act_info); - _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, dilation, act_info); + _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, reshape_weights, dilation, act_info, pre_pad_layer); + _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, dilation, act_info, pre_pad_layer); } protected: @@ -179,8 +182,9 @@ protected: } } + // given input is IN nchw format TensorType compute_target(TensorShape input_shape, TensorShape weights_shape, const TensorShape &bias_shape, TensorShape output_shape, const PadStrideInfo &info, - bool reshape_weights, const Size2D &dilation, const ActivationLayerInfo act_info) + bool reshape_weights, const Size2D &dilation, const ActivationLayerInfo act_info, PaddingList pre_pad_layer = PaddingList({})) { ARM_COMPUTE_ERROR_ON((input_shape[2] % weights_shape[2]) != 0); @@ -191,6 +195,18 @@ protected: permute(input_shape, PermutationVector(2U, 0U, 1U)); permute(weights_shape, PermutationVector(2U, 0U, 1U)); permute(output_shape, PermutationVector(2U, 0U, 1U)); + + if(pre_pad_layer.size() > 0) + { + // make sure paddings exist for each c,h,w dimensions + for(unsigned int i = 0; i < 3 - pre_pad_layer.size(); ++i) + { + pre_pad_layer.push_back({ 0, 0 }); + } + + // rotate padding info from nchw to nhwc + std::rotate(pre_pad_layer.begin(), pre_pad_layer.begin() + 2, pre_pad_layer.begin() + 3); + } } const int idx_width = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH); @@ -207,7 +223,30 @@ protected: // Create and configure function FunctionType conv; - detail::configure_conv_function(conv, &src, &weights, &bias, &dst, info, weights_info, dilation, act_info, num_groups); + + const unsigned int height_index = arm_compute::graph::get_dimension_idx(_data_layout, DataLayoutDimension::HEIGHT); + const unsigned int width_index = arm_compute::graph::get_dimension_idx(_data_layout, DataLayoutDimension::WIDTH); + + const PaddingInfo pad_w = width_index < pre_pad_layer.size() ? pre_pad_layer[width_index] : PaddingInfo(0, 0); + const PaddingInfo pad_h = height_index < pre_pad_layer.size() ? pre_pad_layer[height_index] : PaddingInfo(0, 0); + + if(pre_pad_layer.size() > 0 && arm_compute::graph::is_padding_in_height_or_width(_data_layout, pre_pad_layer)) + { + // this is the logic implemented in NodeFusionMutator -> fuse_pad_with_convolution + const PadStrideInfo new_conv_info( + info.stride().first, + info.stride().second, + info.pad_left() + pad_w.first, + info.pad_right() + pad_w.second, + info.pad_top() + pad_h.first, + info.pad_bottom() + pad_h.second, + info.round()); + detail::configure_conv_function(conv, &src, &weights, &bias, &dst, new_conv_info, weights_info, dilation, act_info, num_groups); + } + else + { + detail::configure_conv_function(conv, &src, &weights, &bias, &dst, info, weights_info, dilation, act_info, num_groups); + } ARM_COMPUTE_ASSERT(src.info()->is_resizable()); ARM_COMPUTE_ASSERT(weights.info()->is_resizable()); @@ -246,7 +285,7 @@ protected: } SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info, - const Size2D &dilation, const ActivationLayerInfo act_info) + const Size2D &dilation, const ActivationLayerInfo act_info, PaddingList pre_pad_layer = PaddingList({})) { ARM_COMPUTE_ERROR_ON((input_shape[2] % weights_shape[2]) != 0); @@ -273,6 +312,11 @@ protected: regularize_values(static_cast<void *>(weights.data()), weights.num_elements()); } + if(pre_pad_layer.size() > 0) + { + src = reference::pad_layer<T>(src, pre_pad_layer, PixelValue(0), PaddingMode::CONSTANT); + } + return (act_info.enabled()) ? reference::activation_layer<T>(reference::convolution_layer<T>(src, weights, bias, output_shape, info, dilation, num_groups), act_info) : reference::convolution_layer<T>(src, weights, bias, output_shape, info, dilation, num_groups); @@ -307,6 +351,20 @@ public: }; template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> +class ConvolutionValidationWithPaddingFixture : public ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T, T> +{ +public: + template <typename...> + void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, bool reshape_weights, DataType data_type, + DataLayout data_layout, ActivationLayerInfo act_info, PaddingList pre_pad_layer = PaddingList({})) + { + ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, reshape_weights, + data_type, data_type, data_layout, + QuantizationInfo(), QuantizationInfo(), act_info, mixed_layout, pre_pad_layer); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> class ConvolutionValidationQuantizedFixture : public ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T, T> { public: |