diff options
Diffstat (limited to 'src/core/NEON/kernels/winograd')
-rw-r--r-- | src/core/NEON/kernels/winograd/winograd_shim_nchw.hpp | 191 |
1 files changed, 0 insertions, 191 deletions
diff --git a/src/core/NEON/kernels/winograd/winograd_shim_nchw.hpp b/src/core/NEON/kernels/winograd/winograd_shim_nchw.hpp deleted file mode 100644 index c5bcffbaef..0000000000 --- a/src/core/NEON/kernels/winograd/winograd_shim_nchw.hpp +++ /dev/null @@ -1,191 +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 <cstdint> -#include <cstdlib> - -#include "gemm.hpp" -#include "profiler.hpp" -#include "utils.hpp" -#include "shims.hpp" -#include "winograd_gemm.hpp" - -#include "transforms.hpp" - -#ifndef ALLOC_ALIGN -#define ALLOC_ALIGN 64 -#endif // ALLOC_ALIGN - - -namespace winograd_shim_nchw { - /***************************************************************************/ - /* Implementation of the Winograd F(2x2, 3x3, 4x4) algorithm using GEMM - * internally. - */ - template <typename TOut, typename TIn> - class Winograd2x2_3x3GEMM : public winograd::Winograd2x2_3x3GEMM<TOut, TIn> { - public: - /* Instantiate a new Winograd operator. - */ - Winograd2x2_3x3GEMM(const KernelShape &kernel_shape, const Tensor4DShape input_shape, const PaddingType padding_type, void *kernel_storage); - - void nchw2nhwc( const Tensor4DShape& input_shape, const PaddingType padding_type, void *working_space, const TIn* const input); - void nhwc2nchw( const Tensor4DShape& input_shape, const PaddingType padding_type, void *working_space, TOut* const output); - - - std::pair<TOut*,TIn*> get_nhwc_ptrs(const Tensor4DShape& input_shape,const PaddingType padding_type,void *working_space); - - static size_t get_working_space_size(const Tensor4DShape &input_shape,const KernelShape &k_shape, const PaddingType padding); - protected: - /* Get the memory required to store an NHWC copy of the input tensor. */ - static size_t get_working_nhwc_input_size(const Tensor4DShape &input_shape); - - /* Get the memory required to store an NHWC copy of the input tensor. */ - static size_t get_working_nhwc_output_size(const Tensor4DShape &output_shape, const KernelShape &k_shape, const PaddingType padding) ; - }; -} // namespace winograd - -/*****************************************************************************/ -template <typename TOut, typename TIn> -winograd_shim_nchw::Winograd2x2_3x3GEMM<TOut, TIn>::Winograd2x2_3x3GEMM( - const KernelShape &kernel_shape, const Tensor4DShape input_shape, - const PaddingType padding_type, void *kernel_storage -) : winograd::Winograd2x2_3x3GEMM<TOut, TIn>(kernel_shape,input_shape,padding_type,kernel_storage) { -} - -/*****************************************************************************/ -template <typename TOut, typename TIn> -void winograd_shim_nchw::Winograd2x2_3x3GEMM<TOut, TIn>::nchw2nhwc(const Tensor4DShape& input_shape, const PaddingType padding_type, void *working_space, const TIn* const input) { - assert(working_space); - int8_t* const ws_bytes = reinterpret_cast<int8_t *>(working_space); - - // Extract the top chunk of the working space to store the input and output - // tensors in NHWC format. - const int in_matrix_stride_bytes = winograd::Winograd2x2_3x3GEMM<TOut, TIn>::get_input_matrix_size(input_shape, this->kernel_shape, padding_type); - const int out_matrix_stride_bytes = winograd::Winograd2x2_3x3GEMM<TOut, TIn>::get_output_matrix_size(input_shape, this->kernel_shape, padding_type); - - // Allocate working space for the input and output in NHWC format - TIn* const input_nhwc = reinterpret_cast<TIn *>( - ws_bytes + 16*(in_matrix_stride_bytes + out_matrix_stride_bytes) - ); - - // Re-order the input tensor - this->prof( - "NCHW -> NHWC", - [input, input_shape, input_nhwc] () { - nchw_to_nhwc( - input, input_nhwc, - input_shape.n_batches, - input_shape.n_channels, - input_shape.n_rows, - input_shape.n_cols - ); - }, - input_shape.size(), 0, input_shape.size() - ); -} - -/*****************************************************************************/ -template <typename TOut, typename TIn> -void winograd_shim_nchw::Winograd2x2_3x3GEMM<TOut, TIn>::nhwc2nchw(const Tensor4DShape& input_shape, const PaddingType padding_type, - void *working_space, TOut* const output) { - - assert(working_space); - int8_t* const ws_bytes = reinterpret_cast<int8_t *>(working_space); - - // Extract the top chunk of the working space to store the input and output - // tensors in NHWC format. - const int in_matrix_stride_bytes = winograd::Winograd2x2_3x3GEMM<TOut, TIn>::get_input_matrix_size(input_shape, this->kernel_shape, padding_type); - const int out_matrix_stride_bytes = winograd::Winograd2x2_3x3GEMM<TOut, TIn>::get_output_matrix_size(input_shape, this->kernel_shape, padding_type); - - TOut* const output_nhwc = reinterpret_cast<TOut *>(ws_bytes + 16*(in_matrix_stride_bytes + out_matrix_stride_bytes) + get_working_nhwc_input_size(input_shape)); - - // Re-order the output tensor into NCHW - const auto output_shape = winograd::Winograd2x2_3x3GEMM<TOut, TIn>::get_output_shape(input_shape, this->kernel_shape, padding_type); - this->prof( - "NHWC -> NCHW", - [output_nhwc, output_shape, output] () { - nhwc_to_nchw( - output_nhwc, output, - output_shape.n_batches, - output_shape.n_rows, - output_shape.n_cols, - output_shape.n_channels - ); - }, - output_shape.size(), 0, output_shape.size() - ); -} - - -/*****************************************************************************/ -template <typename TOut, typename TIn> -std::pair<TOut*,TIn*> winograd_shim_nchw::Winograd2x2_3x3GEMM<TOut, TIn>::get_nhwc_ptrs( - const Tensor4DShape& input_shape, - const PaddingType padding_type, - void *working_space -) { - assert(working_space); - int8_t* const ws_bytes = reinterpret_cast<int8_t *>(working_space); - - // Extract the top chunk of the working space to store the input and output - // tensors in NHWC format. - const int in_matrix_stride_bytes = winograd::Winograd2x2_3x3GEMM<TOut, TIn>::get_input_matrix_size(input_shape, this->kernel_shape, padding_type); - const int out_matrix_stride_bytes = winograd::Winograd2x2_3x3GEMM<TOut, TIn>::get_output_matrix_size(input_shape, this->kernel_shape, padding_type); - - // Allocate working space for the input and output in NHWC format - TIn* input_nhwc = reinterpret_cast<TIn *>(ws_bytes + 16*(in_matrix_stride_bytes + out_matrix_stride_bytes)); - TOut* output_nhwc = reinterpret_cast<TOut *>(ws_bytes + 16*(in_matrix_stride_bytes + out_matrix_stride_bytes) + get_working_nhwc_input_size(input_shape)); - return std::make_pair(output_nhwc,input_nhwc); -} - - - - -/*****************************************************************************/ -template <typename TOut, typename TIn> -size_t winograd_shim_nchw::Winograd2x2_3x3GEMM<TOut, TIn>::get_working_space_size( - const Tensor4DShape& input_shape, const KernelShape &k_shape, const PaddingType padding_type -) { - // TODO Add memory required for NHWC copies of input tensors - return winograd::Winograd2x2_3x3GEMM<TOut, TIn>::get_working_space_size( - input_shape, k_shape, padding_type) - + get_working_nhwc_input_size(input_shape) - + get_working_nhwc_output_size(input_shape, k_shape, padding_type); -} - -template <typename TOut, typename TIn> -size_t winograd_shim_nchw::Winograd2x2_3x3GEMM<TOut, TIn>::get_working_nhwc_input_size( - const Tensor4DShape& input_shape -) { - return roundup(input_shape.size() * sizeof(TIn), static_cast<size_t>(ALLOC_ALIGN)); -} - -template <typename TOut, typename TIn> -size_t winograd_shim_nchw::Winograd2x2_3x3GEMM<TOut, TIn>::get_working_nhwc_output_size( - const Tensor4DShape& input_shape, const KernelShape &k_shape, const PaddingType padding_type -) { - const auto output_shape = winograd::Winograd2x2_3x3GEMM<TOut, TIn>::get_output_shape(input_shape,k_shape, padding_type); - return roundup(output_shape.size() * sizeof(TIn), static_cast<size_t>(ALLOC_ALIGN)); -} |