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Diffstat (limited to 'tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h')
-rw-r--r-- | tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h | 109 |
1 files changed, 109 insertions, 0 deletions
diff --git a/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h b/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h index b01e1760aa..30b8df9da5 100644 --- a/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h +++ b/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h @@ -193,6 +193,115 @@ public: }; template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class DepthwiseConvolutionLayerKernelValidationFixture : public DepthwiseConvolutionLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(size_t width, size_t height, size_t channel, size_t batch, Size2D kernel_size, size_t depth_multiplier, Size2D dilation, Size2D stride, bool padding_valid, DataType data_type, + DataLayout data_layout) + { + const TensorShape src_shape(width, height, channel, batch); + const TensorShape weights_shape(kernel_size.width, kernel_size.height, channel * depth_multiplier); + const TensorShape biases_shape(weights_shape.z()); + + PadStrideInfo conv_info; + if(padding_valid) + { + conv_info = PadStrideInfo(); + } + else + { + conv_info = calculate_same_pad(src_shape, weights_shape, PadStrideInfo(stride.width, stride.height), DataLayout::NCHW, dilation); + } + + _target = compute_target(src_shape, weights_shape, biases_shape, conv_info, dilation, depth_multiplier, data_type, data_layout); + _reference = compute_reference(src_shape, weights_shape, biases_shape, conv_info, dilation, depth_multiplier, data_type); + } + +protected: + template <typename U> + void fill(U &&tensor, int i) + { + switch(tensor.data_type()) + { + case DataType::F32: + { + std::uniform_real_distribution<> distribution(-1.0f, 1.0f); + library->fill(tensor, distribution, i); + break; + } + default: + library->fill_tensor_uniform(tensor, i); + } + } + + TensorType compute_target(TensorShape input_shape, TensorShape weights_shape, TensorShape biases_shape, PadStrideInfo &conv_info, Size2D dilation, + unsigned int depth_multiplier, const DataType data_type, const DataLayout data_layout) + { + if(data_layout == DataLayout::NHWC) + { + permute(input_shape, PermutationVector(2U, 0U, 1U)); + permute(weights_shape, PermutationVector(2U, 0U, 1U)); + } + + // Create tensors + TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, QuantizationInfo(), data_layout); + TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, QuantizationInfo(), data_layout); + TensorType biases = create_tensor<TensorType>(biases_shape, data_type, 1, QuantizationInfo(), data_layout); + TensorType dst = create_tensor<TensorType>(TensorShape(), data_type, 1, QuantizationInfo(), data_layout); + + // Create Depthwise Convolution configure function + FunctionType dwc; + dwc.configure(&src, &weights, &biases, &dst, conv_info, depth_multiplier, dilation); + + ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(biases.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Allocate tensors + src.allocator()->allocate(); + weights.allocator()->allocate(); + biases.allocator()->allocate(); + dst.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(!biases.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Fill tensors + fill(AccessorType(src), 0); + fill(AccessorType(weights), 1); + fill(AccessorType(biases), 2); + + // Compute function + dwc.run(); + + return dst; + } + + SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &biases_shape, const PadStrideInfo &conv_info, + const Size2D &dilation, unsigned int depth_multiplier, const DataType data_type) + { + SimpleTensor<T> src{ input_shape, data_type }; + SimpleTensor<T> weights{ weights_shape, data_type }; + SimpleTensor<T> biases{ biases_shape, data_type }; + + fill(src, 0); + fill(weights, 1); + fill(biases, 2); + + const TensorShape dst_shape = compute_depthwise_convolution_shape(TensorInfo(input_shape, 1, data_type), TensorInfo(weights_shape, 1, data_type), conv_info, + depth_multiplier, dilation); + return reference::depthwise_convolution(src, weights, biases, dst_shape, conv_info, depth_multiplier, dilation); + } + + TensorType _target{}; + SimpleTensor<T> _reference{}; +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> class DepthwiseConvolutionLayerValidationQuantizedFixture : public DepthwiseConvolutionLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T> { public: |