diff options
Diffstat (limited to 'tests/validation/fixtures')
-rw-r--r-- | tests/validation/fixtures/ConvolutionLayerFixture.h | 38 | ||||
-rw-r--r-- | tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h | 47 | ||||
-rw-r--r-- | tests/validation/fixtures/DirectConvolutionLayerFixture.h | 39 | ||||
-rw-r--r-- | tests/validation/fixtures/FFTFixture.h | 37 | ||||
-rw-r--r-- | tests/validation/fixtures/FullyConnectedLayerFixture.h | 39 | ||||
-rw-r--r-- | tests/validation/fixtures/PoolingLayerFixture.h | 40 | ||||
-rw-r--r-- | tests/validation/fixtures/ScaleFixture.h | 42 | ||||
-rw-r--r-- | tests/validation/fixtures/WinogradConvolutionLayerFixture.h | 241 |
8 files changed, 347 insertions, 176 deletions
diff --git a/tests/validation/fixtures/ConvolutionLayerFixture.h b/tests/validation/fixtures/ConvolutionLayerFixture.h index a4db49fc8e..07790e84d9 100644 --- a/tests/validation/fixtures/ConvolutionLayerFixture.h +++ b/tests/validation/fixtures/ConvolutionLayerFixture.h @@ -69,8 +69,9 @@ public: 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) + DataType data_type, DataType weights_data_type, DataLayout data_layout, QuantizationInfo quantization_info, QuantizationInfo weight_quantization_info, ActivationLayerInfo act_info, bool mixed_layout = false) { + _mixed_layout = mixed_layout; _data_type = data_type; _weights_data_type = weights_data_type; _is_quantized = is_data_type_quantized_asymmetric(data_type); @@ -86,6 +87,21 @@ public: } protected: + + void mix_layout(FunctionType &layer, TensorType &src, TensorType &dst) + { + // 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); + + // 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); + dst.info()->set_data_layout(_data_layout); + } + void regularize_values(void *values, size_t size) { float *fvalues = static_cast<float *>(values); @@ -214,8 +230,15 @@ protected: fill(AccessorType(weights), 1); fill(AccessorType(bias), 2); - // Compute NEConvolutionLayer function - conv.run(); + if(_mixed_layout) + { + mix_layout(conv, src, dst); + } + else + { + // Compute Convolution function + conv.run(); + } return dst; } @@ -264,9 +287,10 @@ protected: QuantizationInfo _weight_quantization_info{}; bool _is_quantized = false; bool _is_bfloat16 = false; + bool _mixed_layout = false; }; -template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> class ConvolutionValidationFixture : public ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T, T> { public: @@ -276,11 +300,11 @@ public: { 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); + QuantizationInfo(), QuantizationInfo(), act_info, mixed_layout); } }; -template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> class ConvolutionValidationQuantizedFixture : public ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T, T> { public: @@ -289,7 +313,7 @@ public: DataLayout data_layout, QuantizationInfo quantization_info, ActivationLayerInfo act_info) { 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, quantization_info, quantization_info, act_info); + data_type, data_type, data_layout, quantization_info, quantization_info, act_info, mixed_layout); } }; diff --git a/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h b/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h index d9806b5c84..0aa43d82b4 100644 --- a/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h +++ b/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h @@ -59,8 +59,9 @@ public: void setup(TensorShape in_shape, Size2D kernel_size, PadStrideInfo pad_stride_info, Size2D dilation, unsigned int depth_multiplier, DataType input_data_type, DataType weights_data_type, QuantizationInfo input_quantization_info, QuantizationInfo weights_quantization_info, QuantizationInfo output_quantization_info, - DataLayout data_layout, ActivationLayerInfo act_info) + DataLayout data_layout, ActivationLayerInfo act_info, bool mixed_layout = false) { + _mixed_layout = mixed_layout; _input_shape = in_shape; _input_data_type = input_data_type; _weights_data_type = weights_data_type; @@ -130,9 +131,16 @@ public: fill(AccessorType(_src), 0); fill(AccessorType(_weights), 1); fill(AccessorType(_biases), 2); - - // Compute function - _dwc.run(); + + if(_mixed_layout) + { + mix_layout(_dwc, _src, _target); + } + else + { + // Compute function + _dwc.run(); + } } void compute_reference() @@ -150,6 +158,21 @@ public: } protected: + + void mix_layout(FunctionType &layer, TensorType &src, TensorType &dst) + { + // 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); + + // 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); + dst.info()->set_data_layout(_data_layout); + } + template <typename U> void fill(U &&tensor, int i) { @@ -214,9 +237,10 @@ protected: ActivationLayerInfo _act_info{}; unsigned int _depth_multiplier{}; Size2D _dilation{}; + bool _mixed_layout{false}; }; -template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> class DepthwiseConvolutionLayerValidationFixture : public DepthwiseConvolutionLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T, T> { public: @@ -226,7 +250,7 @@ public: { DepthwiseConvolutionLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T, T>::setup(in_shape, kernel_size, pad_stride_info, dilation, depth_multiplier, data_type, data_type, QuantizationInfo(), QuantizationInfo(), QuantizationInfo(), - data_layout, act_info); + data_layout, act_info, mixed_layout); } }; @@ -434,8 +458,15 @@ public: fill(AccessorType(_weights), 1); fill(AccessorType(_biases), 2); + // 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); + _target.info()->set_data_layout(_data_layout == DataLayout::NCHW ? DataLayout::NHWC : DataLayout::NCHW); + // Compute function _dwc.run(); + + // Reinstating original data layout for the test suite to properly check the values + _target.info()->set_data_layout(_data_layout); } void compute_reference() @@ -496,7 +527,7 @@ protected: unsigned int _n0{}; }; -template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> class DepthwiseConvolutionLayerValidationQuantizedFixture : public DepthwiseConvolutionLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T, T> { public: @@ -506,7 +537,7 @@ public: { DepthwiseConvolutionLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T, T>::setup(in_shape, kernel_size, pad_stride_info, dilation, depth_multiplier, data_type, data_type, input_quantization_info, input_quantization_info, output_quantization_info, - data_layout, act_info); + data_layout, act_info, mixed_layout); } }; diff --git a/tests/validation/fixtures/DirectConvolutionLayerFixture.h b/tests/validation/fixtures/DirectConvolutionLayerFixture.h index 8e4de77535..5ed0b9f9a3 100644 --- a/tests/validation/fixtures/DirectConvolutionLayerFixture.h +++ b/tests/validation/fixtures/DirectConvolutionLayerFixture.h @@ -53,10 +53,11 @@ public: template <typename...> void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, - DataType data_type, QuantizationInfo quantization_info, ActivationLayerInfo act_info, DataLayout data_layout) + DataType data_type, QuantizationInfo quantization_info, ActivationLayerInfo act_info, DataLayout data_layout, bool mixed_layout = false) { _quantization_info = quantization_info; _data_type = data_type; + _mixed_layout = mixed_layout; TensorShape weights_shape(kernel_size, kernel_size, input_shape.z(), num_kernels); const TensorShape bias_shape(num_kernels); @@ -89,6 +90,22 @@ public: } protected: + + void mix_layout(FunctionType &layer, TensorType &src, TensorType &dst) + { + 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); + + // 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); + dst.info()->set_data_layout(data_layout); + } + template <typename U> void fill(U &&tensor, int i) { @@ -171,8 +188,15 @@ protected: fill(AccessorType(weights), 1); fill(AccessorType(bias), 2); - // Compute NEConvolutionLayer function - conv.run(); + if(_mixed_layout) + { + mix_layout(conv, src, dst); + } + else + { + // Compute Convolution function + conv.run(); + } return dst; } @@ -197,9 +221,10 @@ protected: SimpleTensor<T> _reference{}; QuantizationInfo _quantization_info{}; DataType _data_type{}; + bool _mixed_layout {false}; }; -template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> class DirectConvolutionValidationFixture : public DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T> { public: @@ -208,11 +233,11 @@ public: DataLayout data_layout) { DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, QuantizationInfo(), - act_info, data_layout); + act_info, data_layout, mixed_layout); } }; -template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> class DirectConvolutionValidationQuantizedFixture : public DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T> { public: @@ -221,7 +246,7 @@ public: ActivationLayerInfo act_info, DataLayout data_layout) { DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, quantization_info, - act_info, data_layout); + act_info, data_layout, mixed_layout); } }; diff --git a/tests/validation/fixtures/FFTFixture.h b/tests/validation/fixtures/FFTFixture.h index 86a97272a0..199730d5d0 100644 --- a/tests/validation/fixtures/FFTFixture.h +++ b/tests/validation/fixtures/FFTFixture.h @@ -134,8 +134,9 @@ class FFTConvolutionValidationGenericFixture : public framework::Fixture public: template <typename...> void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, - DataType data_type, DataLayout data_layout, ActivationLayerInfo act_info) + DataType data_type, DataLayout data_layout, ActivationLayerInfo act_info, bool mixed_layout = false) { + _mixed_layout = mixed_layout; _data_type = data_type; _data_layout = data_layout; @@ -144,6 +145,21 @@ public: } protected: + + void mix_layout(FunctionType &layer, TensorType &src, TensorType &dst) + { + // 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); + + // 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); + dst.info()->set_data_layout(_data_layout); + } + template <typename U> void fill(U &&tensor, int i) { @@ -209,10 +225,16 @@ protected: fill(AccessorType(src), 0); fill(AccessorType(weights), 1); fill(AccessorType(bias), 2); - - // Compute convolution function - conv.run(); - + + if(_mixed_layout) + { + mix_layout(conv, src, dst); + } + else + { + // Compute Convolution function + conv.run(); + } return dst; } @@ -239,9 +261,10 @@ protected: SimpleTensor<T> _reference{}; DataType _data_type{}; DataLayout _data_layout{}; + bool _mixed_layout{false}; }; -template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> class FFTConvolutionValidationFixture : public FFTConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T> { public: @@ -250,7 +273,7 @@ public: DataType data_type, DataLayout data_layout, ActivationLayerInfo act_info) { FFTConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, - data_type, data_layout, act_info); + data_type, data_layout, act_info, mixed_layout); } }; } // namespace validation diff --git a/tests/validation/fixtures/FullyConnectedLayerFixture.h b/tests/validation/fixtures/FullyConnectedLayerFixture.h index 3760cfb8b7..8f38aae187 100644 --- a/tests/validation/fixtures/FullyConnectedLayerFixture.h +++ b/tests/validation/fixtures/FullyConnectedLayerFixture.h @@ -56,11 +56,12 @@ public: public: template <typename...> void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, bool transpose_weights, bool reshape_weights, - DataType data_type, QuantizationInfo quantization_info, ActivationLayerInfo activation_info) + DataType data_type, QuantizationInfo quantization_info, ActivationLayerInfo activation_info, bool mixed_layout = false) { ARM_COMPUTE_UNUSED(weights_shape); ARM_COMPUTE_UNUSED(bias_shape); + _mixed_layout = mixed_layout; _data_type = data_type; _bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type; _quantization_info = quantization_info; @@ -71,6 +72,22 @@ public: } protected: + + void mix_layout(FunctionType &layer, TensorType &src, TensorType &dst) + { + 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); + + // 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); + dst.info()->set_data_layout(data_layout); + } + template <typename U> void fill(U &&tensor, int i) { @@ -189,8 +206,15 @@ protected: fill(AccessorType(weights), 1); } - // Compute NEFullyConnectedLayer function - fc.run(); + if(_mixed_layout) + { + mix_layout(fc, src, dst); + } + else + { + // Compute NEFullyConnectedLayer function + fc.run(); + } return dst; } @@ -214,11 +238,12 @@ protected: SimpleTensor<T> _reference{}; DataType _data_type{}; DataType _bias_data_type{}; + bool _mixed_layout{false}; QuantizationInfo _quantization_info{}; ActivationLayerInfo _activation_info{}; }; -template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> class FullyConnectedLayerValidationFixture : public FullyConnectedLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T> { public: @@ -228,11 +253,11 @@ public: { FullyConnectedLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, transpose_weights, reshape_weights, data_type, - QuantizationInfo(), activation_info); + QuantizationInfo(), activation_info, mixed_layout); } }; -template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> class FullyConnectedLayerValidationQuantizedFixture : public FullyConnectedLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T> { public: @@ -242,7 +267,7 @@ public: { FullyConnectedLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, transpose_weights, reshape_weights, data_type, - quantization_info, activation_info); + quantization_info, activation_info, mixed_layout); } }; } // namespace validation diff --git a/tests/validation/fixtures/PoolingLayerFixture.h b/tests/validation/fixtures/PoolingLayerFixture.h index af078d4ce3..ee81ff5538 100644 --- a/tests/validation/fixtures/PoolingLayerFixture.h +++ b/tests/validation/fixtures/PoolingLayerFixture.h @@ -47,14 +47,31 @@ class PoolingLayerValidationGenericFixture : public framework::Fixture public: template <typename...> void setup(TensorShape shape, PoolingLayerInfo pool_info, DataType data_type, DataLayout data_layout, bool indices = false, - QuantizationInfo input_qinfo = QuantizationInfo(), QuantizationInfo output_qinfo = QuantizationInfo()) + QuantizationInfo input_qinfo = QuantizationInfo(), QuantizationInfo output_qinfo = QuantizationInfo(), bool mixed_layout = false) { + _mixed_layout = mixed_layout; _pool_info = pool_info; _target = compute_target(shape, pool_info, data_type, data_layout, input_qinfo, output_qinfo, indices); _reference = compute_reference(shape, pool_info, data_type, data_layout, input_qinfo, output_qinfo, indices); } protected: + + void mix_layout(FunctionType &layer, TensorType &src, TensorType &dst) + { + 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); + + // 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); + dst.info()->set_data_layout(data_layout); + } + template <typename U> void fill(U &&tensor) { @@ -110,9 +127,15 @@ protected: // Fill tensors fill(AccessorType(src)); - // Compute function - pool_layer.run(); - + if(_mixed_layout) + { + mix_layout(pool_layer, src, dst); + } + else + { + // Compute function + pool_layer.run(); + } return dst; } @@ -129,6 +152,7 @@ protected: TensorType _target{}; SimpleTensor<T> _reference{}; PoolingLayerInfo _pool_info{}; + bool _mixed_layout{false}; TensorType _target_indices{}; SimpleTensor<uint32_t> _ref_indices{}; }; @@ -144,7 +168,7 @@ public: } }; -template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> class PoolingLayerValidationFixture : public PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T> { public: @@ -152,7 +176,7 @@ public: void setup(TensorShape shape, PoolingType pool_type, Size2D pool_size, PadStrideInfo pad_stride_info, bool exclude_padding, DataType data_type, DataLayout data_layout) { PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, PoolingLayerInfo(pool_type, pool_size, data_layout, pad_stride_info, exclude_padding), - data_type, data_layout); + data_type, data_layout, false, mixed_layout); } }; @@ -168,7 +192,7 @@ public: } }; -template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> class PoolingLayerValidationQuantizedFixture : public PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T> { public: @@ -177,7 +201,7 @@ public: QuantizationInfo input_qinfo = QuantizationInfo(), QuantizationInfo output_qinfo = QuantizationInfo()) { PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, PoolingLayerInfo(pool_type, pool_size, data_layout, pad_stride_info, exclude_padding), - data_type, data_layout, false, input_qinfo, output_qinfo); + data_type, data_layout, false, input_qinfo, output_qinfo, mixed_layout); } }; diff --git a/tests/validation/fixtures/ScaleFixture.h b/tests/validation/fixtures/ScaleFixture.h index dd521470e6..9e0f620abe 100644 --- a/tests/validation/fixtures/ScaleFixture.h +++ b/tests/validation/fixtures/ScaleFixture.h @@ -46,7 +46,7 @@ class ScaleValidationGenericFixture : public framework::Fixture public: template <typename...> void setup(TensorShape shape, DataType data_type, QuantizationInfo quantization_info, DataLayout data_layout, InterpolationPolicy policy, BorderMode border_mode, SamplingPolicy sampling_policy, - bool align_corners) + bool align_corners, bool mixed_layout) { _shape = shape; _policy = policy; @@ -55,6 +55,7 @@ public: _data_type = data_type; _quantization_info = quantization_info; _align_corners = align_corners; + _mixed_layout = mixed_layout; generate_scale(shape); @@ -67,6 +68,22 @@ public: } protected: + + void mix_layout(FunctionType &layer, TensorType &src, TensorType &dst) + { + 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); + + // 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); + dst.info()->set_data_layout(data_layout); + } + void generate_scale(const TensorShape &shape) { static constexpr float _min_scale{ 0.25f }; @@ -155,9 +172,15 @@ protected: // Fill tensors fill(AccessorType(src)); - // Compute function - scale.run(); - + if(_mixed_layout) + { + mix_layout(scale, src, dst); + } + else + { + // Compute function + scale.run(); + } return dst; } @@ -182,11 +205,12 @@ protected: DataType _data_type{}; QuantizationInfo _quantization_info{}; bool _align_corners{ false }; + bool _mixed_layout{ false }; float _scale_x{ 1.f }; float _scale_y{ 1.f }; }; -template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> class ScaleValidationQuantizedFixture : public ScaleValidationGenericFixture<TensorType, AccessorType, FunctionType, T> { public: @@ -201,10 +225,11 @@ public: policy, border_mode, sampling_policy, - align_corners); + align_corners, + mixed_layout); } }; -template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> class ScaleValidationFixture : public ScaleValidationGenericFixture<TensorType, AccessorType, FunctionType, T> { public: @@ -218,7 +243,8 @@ public: policy, border_mode, sampling_policy, - align_corners); + align_corners, + mixed_layout); } }; } // namespace validation 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 <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool use_bias = true> -class WinogradConvolutionLayerValidationFixture : public framework::Fixture +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, typename T1 = T, bool use_bias = true, bool mixed_layout = false> +class WinogradConvolutionLayerFastMathValidationFixture : public framework::Fixture { public: template <typename...> 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 <typename U> - void fill(U &&tensor, int i, float min, float max) - { - switch(tensor.data_type()) - { - case DataType::F16: - { - arm_compute::utils::uniform_real_distribution_16bit<half> distribution{ float(min), float(max) }; - library->fill(tensor, distribution, i); - break; - } - case DataType::F32: - { - std::uniform_real_distribution<float> 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<TensorType>(input_shape, data_type, 1); - TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1); - TensorType bias = create_tensor<TensorType>(bias_shape, data_type, 1); - TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1); - - // Create and configure function - FunctionType conv; - ARM_COMPUTE_EXPECT(static_cast<bool>(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<T> 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<T> src{ input_shape, data_type, 1 }; - SimpleTensor<T> weights{ weights_shape, data_type, 1 }; - SimpleTensor<T> 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<T> conv_out = reference::convolution_layer<T>(src, weights, bias, output_shape, info); - - return (act_info.enabled()) ? reference::activation_layer<T>(conv_out, act_info) : conv_out; - } - - TensorType _target{}; - SimpleTensor<T> _reference{}; -}; + // Compute Convolution function + layer.run(); -template <typename TensorType, typename AccessorType, typename FunctionType, typename T, typename T1 = T, bool use_bias = true> -class WinogradConvolutionLayerFastMathValidationFixture : public framework::Fixture -{ -public: - template <typename...> - 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 <typename U> 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<T> _reference{}; + bool _mixed_layout{false}; }; -template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> 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 <typename U> 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<T>(src, output_shape, winograd_info); } + bool _mixed_layout {false}; TensorType _target{}; SimpleTensor<T> _reference{}; }; -template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> 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 <typename U> 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<T>(src, output_shape, winograd_info); } + bool _mixed_layout {false}; TensorType _target{}; SimpleTensor<T> _reference{}; }; -template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> 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 <typename U> 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<T>(winograd_output, act_info) : winograd_output; } + bool _mixed_layout {false}; TensorType _target{}; SimpleTensor<T> _reference{}; }; } // namespace validation } // namespace test } // namespace arm_compute -#endif /* ARM_COMPUTE_TEST_WINOGRAD_LAYER_FIXTURE */ +#endif /* ARM_COMPUTE_TEST_WINOGRAD_LAYER_FIXTURE */
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