diff options
Diffstat (limited to 'tests')
| -rw-r--r-- | tests/validation/NEON/ConvolutionLayer.cpp | 18 | ||||
| -rw-r--r-- | tests/validation/fixtures/ConvolutionLayerFixture.h | 29 |
2 files changed, 42 insertions, 5 deletions
diff --git a/tests/validation/NEON/ConvolutionLayer.cpp b/tests/validation/NEON/ConvolutionLayer.cpp index 7a274906a6..98a5be5484 100644 --- a/tests/validation/NEON/ConvolutionLayer.cpp +++ b/tests/validation/NEON/ConvolutionLayer.cpp @@ -1032,6 +1032,8 @@ TEST_SUITE(GEMMConvolutionLayer) template <typename T> using NEGEMMConvolutionLayerFixture = ConvolutionValidationFixture<Tensor, Accessor, NEConvolutionLayer, T>; template <typename T> +using NEGEMMConvolutionLayerPaddedWeightsFixture = ConvolutionValidationPaddedWeightsFixture<Tensor, Accessor, NEConvolutionLayer, T>; +template <typename T> using NEGEMMConvolutionLayerMixedDataLayoutFixture = ConvolutionValidationFixture<Tensor, Accessor, NEConvolutionLayer, T, true>; /** Test case for memory injection in @ref cpu::CpuGemmConv2d. @@ -1184,9 +1186,25 @@ FIXTURE_DATA_TEST_CASE(RunMixedDataLayout, NEGEMMConvolutionLayerMixedDataLayout // Validate output validate(Accessor(_target), _reference, rel_tolerance_f32, 0.f, float(abs_tolerance_f32)); } +/** Padded weights + * CpuGemmConv2d uses two different paths for reshaping the weights based on if the weight tensor has holes (a common + * way to have "holes" in tensor is via extended paddings) + * + * We only need to test the padded weight path here on a single floating data type and a single layout, because the fallback path is agnostic of them + */ +FIXTURE_DATA_TEST_CASE(RunPaddedWeights, NEGEMMConvolutionLayerPaddedWeightsFixture<float>, framework::DatasetMode::ALL, combine(datasets::SmallConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true }), + framework::dataset::make("DataType", DataType::F32), + framework::dataset::make("DataLayout", { DataLayout::NHWC }) + )) +{ + // Validate output + validate(Accessor(_target), _reference, rel_tolerance_f32, 0.f, float(abs_tolerance_f32)); +} TEST_SUITE_END() // FP32 TEST_SUITE_END() // Float +// TODO: COMPMID-6596 Extend quantized tests with at least one suite where the weight is padded (the legacy case, see floating point's RunPaddedWeights) template <typename T> using NEGEMMConvolutionLayerQuantizedFixture = ConvolutionValidationQuantizedFixture<Tensor, Accessor, NEConvolutionLayer, T>; template <typename T> diff --git a/tests/validation/fixtures/ConvolutionLayerFixture.h b/tests/validation/fixtures/ConvolutionLayerFixture.h index 2051add225..0622e5e6f0 100644 --- a/tests/validation/fixtures/ConvolutionLayerFixture.h +++ b/tests/validation/fixtures/ConvolutionLayerFixture.h @@ -123,7 +123,7 @@ public: public: 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, PaddingList pre_pad_layer = PaddingList({})) + bool mixed_layout = false, PaddingList pre_pad_layer = PaddingList({}), bool padded_weights = false) { // This hash is used by random generators. There may be hash collisions but // this is intentional as it's a very easy way to make the the current @@ -151,7 +151,7 @@ public: _use_dynamic_output_quant = true; } - _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, reshape_weights, dilation, act_info, pre_pad_layer); + _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, reshape_weights, dilation, act_info, pre_pad_layer, padded_weights); _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, dilation, act_info, pre_pad_layer); } @@ -267,7 +267,7 @@ 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, PaddingList pre_pad_layer = PaddingList({})) + bool reshape_weights, const Size2D &dilation, const ActivationLayerInfo act_info, PaddingList pre_pad_layer = PaddingList({}), bool padded_weights = false) { ARM_COMPUTE_ERROR_ON((input_shape[2] % weights_shape[2]) != 0); @@ -335,8 +335,13 @@ protected: ARM_COMPUTE_ASSERT(weights.info()->is_resizable()); ARM_COMPUTE_ASSERT(bias.info()->is_resizable()); ARM_COMPUTE_ASSERT(dst.info()->is_resizable()); - - add_padding_x({ &src, &weights, &bias, &dst }, _data_layout); + // Test "add padding after configure" behavior. This behavior should not affect the correctness + add_padding_x({ &src, &bias, &dst }, _data_layout); + // Padding weights may affect code path in some backends + if (padded_weights) + { + add_padding_x({ &weights }, _data_layout); + } // Allocate tensors src.allocator()->allocate(); @@ -437,6 +442,19 @@ public: }; template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> +class ConvolutionValidationPaddedWeightsFixture : public ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T, T> +{ +public: + 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) + { + 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(), ActivationLayerInfo(), mixed_layout, PaddingList({}), true); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> class ConvolutionValidationWithPaddingFixture : public ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T, T> { public: @@ -481,6 +499,7 @@ public: } }; + #ifdef ARM_COMPUTE_ENABLE_FIXED_FORMAT_KERNELS inline TensorInfo prepare_weights(const TensorInfo tensor_info, const arm_compute::WeightFormat weight_format) { |