| /* |
| * Copyright (c) 2017-2019 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_gemm_local.hpp" |
| #include "arm_gemm.hpp" |
| #include "winograd.hpp" |
| |
| namespace winograd |
| { |
| |
| |
| class IWinogradConvolutionLayer |
| { |
| public: |
| virtual ~IWinogradConvolutionLayer() = default; |
| |
| virtual unsigned int weight_transform_get_window(void) const = 0; |
| virtual void weight_transform_run(unsigned int start, unsigned int stop) = 0; |
| |
| virtual IInputTransform& input_transform(void) = 0; // Expose the input transform |
| virtual IOutputTransform& output_transform(void) = 0; // Expose the output transform |
| virtual arm_gemm::IGemmCommon *gemm(void) = 0; // Expose the underlying GEMM |
| }; |
| |
| /** Example of how to construct an ACL-like interface. |
| * |
| * Use `get_weight_storage_size`, `get_input_storage_size` and |
| * `get_output_storage_size` to allocate memory for the convolution engine. |
| * Then create a `WinogradConvolutionLayer`. |
| * |
| * Initialise the weights using `weights_transform.run(...)`. |
| * |
| * For each inference: |
| * 1. Transform the inputs to the Winograd domain using `input_transform.run(...)` |
| * 2. Perform a number of GEMMs using `gemms.run(...)` |
| * 3. Transform the output to the spatial domain using `output_transform.run(...)` |
| */ |
| template <int OutputTileRows, int OutputTileCols, int KernelRows, int KernelCols, |
| typename TIn, typename TInGEMM, typename TOutGEMM, typename TOut, |
| WinogradRoots Roots> |
| class WinogradConvolutionLayer : public IWinogradConvolutionLayer |
| { |
| public: |
| using WinogradBase = winograd::WinogradGEMM<OutputTileRows, OutputTileCols, KernelRows, KernelCols, Roots>; |
| using WeightsTransform = typename WinogradBase::template WeightsTransform<TIn, TInGEMM>; |
| using InputTransform = typename WinogradBase::template InputTransform<TIn, TInGEMM>; |
| using WinogradConv = typename WinogradBase::template Convolution<TOut, TIn, TInGEMM, TOutGEMM>; |
| using OutputTransform = typename WinogradBase::template OutputTransform<TOutGEMM, TOut>; |
| |
| private: |
| static constexpr int InnerTileRows = OutputTileRows + KernelRows - 1; |
| static constexpr int InnerTileCols = OutputTileCols + KernelCols - 1; |
| static constexpr int N_GEMMS = InnerTileRows * InnerTileCols; |
| |
| const int _n_output_rows, _n_output_cols; |
| const int _kernel_matrix_stride, _kernel_matrix_row_stride; |
| const int _input_matrix_stride, _input_matrix_row_stride; |
| const int _output_matrix_stride, _output_matrix_row_stride; |
| const int _tile_rows, _tile_cols; |
| const int _m, _k, _n; |
| |
| WeightsTransform weights_transform; /** Operator to transform weights to Winograd domain. */ |
| InputTransform _input_transform; /** Operator to transform input to Winograd domain. */ |
| const arm_gemm::GemmArgs gemm_args; |
| arm_gemm::UniqueGemmCommon<TInGEMM, TOutGEMM> gemms; /** Operator to perform multiple GEMMs. */ |
| OutputTransform _output_transform; /** Operator to transform output from Winograd domain. */ |
| |
| public: |
| |
| /** Determine how much memory (in units of TIn) to allocate for the |
| * transformed weights. |
| */ |
| static unsigned int get_weight_storage_size( |
| const int n_output_channels, /** Number of output feature maps. */ |
| const int n_input_channels /** Number of input feature maps. */ |
| ); |
| |
| static unsigned int get_weight_stride( |
| const int n_output_channels, /** Number of output feature maps. */ |
| const int n_input_channels /** Number of input feature maps. */ |
| ); |
| |
| static unsigned int get_weight_multi_stride( |
| const int n_output_channels, /** Number of output feature maps. */ |
| const int n_input_channels /** Number of input feature maps. */ |
| ); |
| |
| /** Determine how much memory (in units of TIn) to allocate for the |
| * transformed input. |
| */ |
| static unsigned int get_input_storage_size( |
| const int n_batches, /** Number of batches in the input tensor. */ |
| const int n_channels, /** Number of feature maps in the input tensor. */ |
| const int n_rows, /** Number of rows in each feature map. */ |
| const int n_cols, /** Number of columns in each feature map. */ |
| const bool same_padding /** Use "SAME" padding, otherwise use "VALID". */ |
| ); |
| |
| /** Get the row stride for the A matrix in the Winograd domain. */ |
| static unsigned int get_input_stride( |
| const int n_batches, /** Number of batches in the input tensor. */ |
| const int n_channels, /** Number of feature maps in the input tensor. */ |
| const int n_rows, /** Number of rows in each feature map. */ |
| const int n_cols, /** Number of columns in each feature map. */ |
| const bool same_padding /** Use "SAME" padding, otherwise use "VALID". */ |
| ); |
| |
| /** Get the stride between A matrices in the Winograd domain. */ |
| static unsigned int get_input_multi_stride( |
| const int n_batches, /** Number of batches in the input tensor. */ |
| const int n_channels, /** Number of feature maps in the input tensor. */ |
| const int n_rows, /** Number of rows in each feature map. */ |
| const int n_cols, /** Number of columns in each feature map. */ |
| const bool same_padding /** Use "SAME" padding, otherwise use "VALID". */ |
| ); |
| |
| /** Determine how much memory (in units of TOut) to allocate for the |
| * (Winograd domain) output. |
| */ |
| static unsigned int get_output_storage_size( |
| const int n_batches, /** Number of batches in the output tensor. */ |
| const int n_rows, /** Number of rows in each feature map of the input tensor. */ |
| const int n_cols, /** Number of columns in each feature map of the input tensor. */ |
| const int n_output_channels, /** Number of feature maps in the output tensor. */ |
| const bool same_padding /** Use "SAME" padding, otherwise use "VALID". */ |
| ); |
| |
| static unsigned int get_output_stride( |
| const int n_batches, /** Number of batches in the output tensor. */ |
| const int n_rows, /** Number of rows in each feature map of the input tensor. */ |
| const int n_cols, /** Number of columns in each feature map of the input tensor. */ |
| const int n_output_channels, /** Number of feature maps in the output tensor. */ |
| const bool same_padding /** Use "SAME" padding, otherwise use "VALID". */ |
| ); |
| |
| static unsigned int get_output_multi_stride( |
| const int n_batches, /** Number of batches in the output tensor. */ |
| const int n_rows, /** Number of rows in each feature map of the input tensor. */ |
| const int n_cols, /** Number of columns in each feature map of the input tensor. */ |
| const int n_output_channels, /** Number of feature maps in the output tensor. */ |
| const bool same_padding /** Use "SAME" padding, otherwise use "VALID". */ |
| ); |
| |
| /** Get the shape (rows, cols) of a feature map of the output tensor. */ |
| static std::pair<int, int> get_output_feature_map_shape( |
| const int n_input_rows, /** Number of rows in the input feature map. */ |
| const int n_input_cols, /** Number of columns in the input feature map. */ |
| const bool same_padding /** Use "SAME" padding, otherwise use "VALID". */ |
| ); |
| |
| /** Create a new Winograd convolution layer. |
| */ |
| WinogradConvolutionLayer( |
| const arm_gemm::CPUInfo &cpuinfo, /** Describes CPU properties. */ |
| const int n_threads, /** Maximum number of threads used to execute the convolution. */ |
| const int n_batches, /** Number of batches in the input and output tensors. */ |
| const int n_input_channels, /** Number of feature maps in a batch of the input tensor. */ |
| const int n_input_rows, /** Number of rows in a feature map of the input tensor. */ |
| const int n_input_cols, /** Number of columns in a feature map of the input tensor. */ |
| const int n_output_channels, /** Number of feature maps in the output tensor. */ |
| const bool same_padding, /** Use "SAME" padding, otherwise use "VALID". */ |
| const arm_gemm::Activation &activation, |
| const TIn* const weights, /** Pointer to weight tensor in spatial domain. Must be ordered as "Height x Rows x Input Feature Maps x Output Feature Maps. */ |
| TInGEMM* const weights_storage, /** Pointer to storage for weight tensor in the Winograd domain. Must be at least the size returned by `get_weight_storage_size`. */ |
| const TIn* const input, /** Pointer to NHWC ordered input tensor, in the spatial domain. */ |
| TInGEMM* const winograd_input, /** Pointer to working space for the input tensor in the Winograd domain. Must be at least the size returned by `get_input_storage_size`. */ |
| const TOut* const biases, /** Pointer to biases vector. Pass nullptr if no bias is provided. */ |
| TOut* const output, /** Pointer to NHWC ordered output tensor, in the spatial domain. */ |
| TOutGEMM* const winograd_output, /** Pointer to working space for the output tensor in the Winograd domain. Must be at least the size returned by `get_output_storage_size`. */ |
| const bool pretranspose_B=true, /** Hint that the B matrix can be pretransposed. */ |
| arm_gemm::GemmConfig *gemm_cfg=nullptr /** Pointer to GEMM configuration. */ |
| ); |
| |
| /* Utility methods for interacting with the layer. */ |
| unsigned int weight_transform_get_window(void) const; |
| void weight_transform_run(const unsigned int start, const unsigned int stop); |
| |
| IInputTransform& input_transform(void); |
| IOutputTransform& output_transform(void); |
| |
| /* Get a pointer to the GEMM underlying the Winograd transform. */ |
| arm_gemm::IGemmCommon *gemm(void); |
| }; |
| |
| } |