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Diffstat (limited to 'arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp')
| -rw-r--r-- | arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp | 226 |
1 files changed, 0 insertions, 226 deletions
diff --git a/arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp b/arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp deleted file mode 100644 index 71b5fd516f..0000000000 --- a/arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp +++ /dev/null @@ -1,226 +0,0 @@ -/* - * Copyright (c) 2017 ARM Limited. - * - * SPDX-License-Identifier: MIT - * - * Permission is hereby granted, free of charge, to any person obtaining a copy - * of this software and associated documentation files (the "Software"), to - * deal in the Software without restriction, including without limitation the - * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or - * sell copies of the Software, and to permit persons to whom the Software is - * furnished to do so, subject to the following conditions: - * - * The above copyright notice and this permission notice shall be included in all - * copies or substantial portions of the Software. - * - * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR - * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, - * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE - * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER - * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, - * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE - * SOFTWARE. - */ - -#pragma once - -#include "arm_compute/core/NEON/kernels/convolution/common/alloc.hpp" -#include "arm_compute/core/NEON/kernels/convolution/common/convolution.hpp" -#include "gemm.hpp" -#include "arm_compute/core/NEON/kernels/convolution/common/shims.hpp" -#include "arm_compute/core/NEON/kernels/convolution/common/tensor.hpp" -#include "arm_compute/core/NEON/kernels/convolution/common/utils.hpp" -#include "winograd_input_transform.hpp" -#include "winograd_output_transform.hpp" - -#include <thread> -#include <utility> -#include <vector> - -// Generic Winograd implementation using GEMM -namespace winograd -{ - -template <int OutputTileRows, int OutputTileCols, int KernelRows, int KernelCols> -class WinogradGEMM -{ - public: - // Information about the specific Winograd instance - static constexpr int output_tile_rows = OutputTileRows; - static constexpr int output_tile_cols = OutputTileCols; - static constexpr int kernel_rows = KernelRows; - static constexpr int kernel_cols = KernelCols; - static constexpr int inner_tile_rows = output_tile_rows + kernel_rows - 1; - static constexpr int inner_tile_cols = output_tile_cols + kernel_cols - 1; - static constexpr int N_GEMMS = inner_tile_rows * inner_tile_cols; - - /** Transform weights from the spatial to the Winograd domain. */ - template <typename T> - struct WeightsTransform - { - /** Get the bytes read during the transform. */ - static inline size_t bytes_read(const KernelShape &shape) - { - return shape.size() * sizeof(T); - } - - /** Get the bytes written during the transform. */ - static inline size_t bytes_written(const KernelShape &shape) - { - const int inner_tile_size = inner_tile_rows * inner_tile_cols; - return (inner_tile_size * shape.n_input_channels * - shape.n_output_channels * sizeof(T)); - } - - /** Get the count of operations performed by the transform. */ - static int ops_performed(const KernelShape &shape); - - /** Apply the transform to a tensor. */ - static void execute( - const int n_output_channels, - const int n_input_channels, - const T* const input, - T* const output, - const int matrix_stride, - const int matrix_row_stride - ); - - /** Create a WeightsTransform operator fixed on a given problem and set - * of pointers. - */ - WeightsTransform( - const T* const input, - T* const output, - const int matrix_stride, /** Stride across matrices in the output. */ - const int matrix_row_stride, /** Stride across rows of the matrix. */ - const int n_output_channels, /** Number of filters. */ - const int n_input_channels /** Number of channels in each filter. */ - ); - - /** Get the window of work a given operator can perform. */ - unsigned int get_window() const; - - /** Perform work upon a window of the input. */ - void run(const unsigned int start, const unsigned int stop); - - private: - const T* const inptr; /** Fixed pointer to input data. */ - T* const outptr; /** Fixed pointer to output memory. */ - const int matrix_stride; /** Stride between output matrices. */ - const int matrix_row_stride; /** Stride within output matrices. */ - const int n_output_channels; /** Number of filters. */ - const int n_input_channels; /** Number of channels in each filter. */ - }; - - /** Transform input feature maps from the spatial to the Winograd domain. - */ - template <typename T> - using InputTransform = InputTransform< - KernelRows, KernelCols, - (OutputTileRows + KernelRows - 1), - (OutputTileCols + KernelCols - 1), - T - >; - - /** Transform output feature maps from the Winograd to the spatial domain. - */ - template <typename T> - using OutputTransform = OutputTransform< - KernelRows, KernelCols, - (OutputTileRows + KernelRows - 1), - (OutputTileCols + KernelCols - 1), - T - >; - - - /** Perform a convolution. - */ - template <typename TOut, typename TIn> - class Convolution - { - public: - // Information about the typed Winograd instance - typedef TOut OutputType; - 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); - - /** Get the memory required to store the kernel transformed into the - * Winograd domain. - */ - static size_t get_kernel_storage_size(const KernelShape &shape); - - /** 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 - ); - - /** 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 - ); - - /** 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 - ); - - /* 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 - ); - - static int get_input_matrix_stride( - const KernelShape &kernel_shape, - const Tensor4DShape &input_shape, - const PaddingType padding_type - ); - - /* 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 - ); - - static int get_output_matrix_stride( - const KernelShape &kernel_shape, - const Tensor4DShape &input_shape, - const PaddingType padding_type - ); - - /* 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 constexpr int M_BLOCK = 4; /** Size of block used by GEMM. */ - static constexpr int N_BLOCK = 16; /** Size of block used by GEMM. */ - }; -}; - -} // namespace winograd |