diff options
Diffstat (limited to 'arm_compute/core/NEON/kernels/convolution/winograd/winograd.hpp')
| -rw-r--r-- | arm_compute/core/NEON/kernels/convolution/winograd/winograd.hpp | 105 |
1 files changed, 58 insertions, 47 deletions
diff --git a/arm_compute/core/NEON/kernels/convolution/winograd/winograd.hpp b/arm_compute/core/NEON/kernels/convolution/winograd/winograd.hpp index 183c9c1061..bc0d9d4296 100644 --- a/arm_compute/core/NEON/kernels/convolution/winograd/winograd.hpp +++ b/arm_compute/core/NEON/kernels/convolution/winograd/winograd.hpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019 ARM Limited. + * Copyright (c) 2017-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -24,9 +24,10 @@ #pragma once -#include "convolution.hpp" -#include "tensor.hpp" -#include "utils.hpp" +#include "arm_compute/core/NEON/kernels/assembly/arm_gemm.hpp" + +#include <cstddef> +#include <utility> namespace winograd { @@ -308,7 +309,8 @@ class OutputTransform : public IOutputTransform int n_batches, /**< Number of batches in output tensor. */ int n_rows, /**< Number of rows in output tensor. */ int n_cols, /**< Number of columns in output tensor. */ - int n_channels /**< Number of channels in output tensor. */ + int n_channels, /**< Number of channels in output tensor. */ + const arm_gemm::Activation &activation ); OutputTransform(OutputTransform&) = delete; @@ -344,6 +346,7 @@ class OutputTransform : public IOutputTransform static constexpr int output_tile_cols = InnerTileCols - KernelCols + 1; const int _n_batches, _n_rows, _n_cols, _n_channels; + const TOut _output_min, _output_max; private: void transform_uncropped_tile( @@ -372,7 +375,9 @@ class OutputTransform : public IOutputTransform const TOut* biases, TOut* output, int output_row_stride, - int output_col_stride + int output_col_stride, + TOut output_min, + TOut output_max ); /** Get the working space for a thread. */ @@ -405,7 +410,8 @@ class OutputTransform<KernelRows, 1, InnerTileRows, 1, TIn, TOut, Roots> : int n_batches, /**< Number of batches in output tensor. */ int n_rows, /**< Number of rows in output tensor. */ int n_cols, /**< Number of columns in output tensor. */ - int n_channels /**< Number of channels in output tensor. */ + int n_channels, /**< Number of channels in output tensor. */ + const arm_gemm::Activation &activation ); /** Set pointers to the output tensor written by the transform. */ @@ -528,79 +534,84 @@ class WinogradGEMM typedef TIn InputType; /** Get the output shape of a convolution. */ - static Tensor4DShape get_output_shape( - const KernelShape &kernel_shape, - const Tensor4DShape &in_shape, - const PaddingType padding - ); - - /* Get the memory required to transform the kernel. - */ - static size_t get_kernel_transform_working_size(const KernelShape &shape); + static std::pair<unsigned int, unsigned int> get_output_shape( + const std::pair<unsigned int, unsigned int> input_shape, + bool padding_same); /** Get the memory required to store the kernel transformed into the * Winograd domain. */ - static size_t get_kernel_storage_size(const KernelShape &shape); + static size_t get_kernel_storage_size(unsigned int n_input_channels, + unsigned int n_output_channels); /** Get the memory required to store the input tensor transformed into * the Winograd domain. */ static size_t get_input_storage_size( - const KernelShape &kernel_shape, - const Tensor4DShape &input_shape, - const PaddingType padding_type - ); + unsigned int n_batches, // Number of batches + unsigned int n_rows, // Number of input rows + unsigned int n_cols, // Number of input columns + unsigned int n_channels, // Number of input channels + bool padding_same); /** Get the memory required to store the output tensor in the Winograd * domain. */ static size_t get_output_storage_size( - const KernelShape &kernel_shape, - const Tensor4DShape &input_shape, - const PaddingType padding_type - ); + unsigned int n_batches, // Number of batches + unsigned int n_rows, // Number of output rows + unsigned int n_cols, // Number of output columns + unsigned int n_channels // Number of output channels + ); /** Get the memory required to apply a Winograd operator to some input. */ static size_t get_working_space_size( - const KernelShape &kernel_shape, - const Tensor4DShape &input_shape, - const PaddingType padding_type - ); + unsigned int n_batches, + unsigned int n_rows, // Number of input rows + unsigned int n_cols, // Number of input columns + unsigned int n_input_channels, // Number of input channels + unsigned int n_output_channels, // Number of output channels + bool padding_same); /* Get the memory required by a single "input" matrix. */ static size_t get_input_matrix_size( - const KernelShape &kernel_shape, - const Tensor4DShape &input_shape, - const PaddingType padding_type - ); + unsigned int n_batches, // Number of batches + unsigned int n_rows, // Number of input rows + unsigned int n_cols, // Number of input columns + unsigned int n_channels, // Number of input channels + bool padding_same); static int get_input_matrix_stride( - const KernelShape &kernel_shape, - const Tensor4DShape &input_shape, - const PaddingType padding_type - ); + unsigned int n_batches, // Number of batches + unsigned int n_rows, // Number of input rows + unsigned int n_cols, // Number of input columns + unsigned int n_channels, // Number of input channels + bool padding_same); /* Get the memory required by a single "output" matrix. */ static size_t get_output_matrix_size( - const KernelShape &kernel_shape, - const Tensor4DShape &input_shape, - const PaddingType padding_type - ); + unsigned int n_batches, // Number of batches + unsigned int n_rows, // Number of output rows + unsigned int n_cols, // Number of output columns + unsigned int n_channels // Number of output channels + ); static int get_output_matrix_stride( - const KernelShape &kernel_shape, - const Tensor4DShape &input_shape, - const PaddingType padding_type - ); + unsigned int n_batches, // Number of batches + unsigned int n_rows, // Number of output rows + unsigned int n_cols, // Number of output columns + unsigned int n_channels // Number of output channels + ); /* Get the memory required by a single "kernel" matrix. */ - static size_t get_kernel_matrix_size(const KernelShape &shape); - static int get_kernel_matrix_stride(const KernelShape &shape); + static size_t get_kernel_matrix_size(unsigned int n_input_channels, + unsigned int n_output_channels); + static int get_kernel_matrix_stride(unsigned int n_input_channels, + unsigned int n_output_channels); static constexpr int M_BLOCK = 4; /** Size of block used by GEMM. */ static constexpr int N_BLOCK = 16; /** Size of block used by GEMM. */ |