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Diffstat (limited to 'src/core/NEON/kernels/convolution/depthwise/depthwise.hpp')
| -rw-r--r-- | src/core/NEON/kernels/convolution/depthwise/depthwise.hpp | 551 |
1 files changed, 0 insertions, 551 deletions
diff --git a/src/core/NEON/kernels/convolution/depthwise/depthwise.hpp b/src/core/NEON/kernels/convolution/depthwise/depthwise.hpp deleted file mode 100644 index 70d6689731..0000000000 --- a/src/core/NEON/kernels/convolution/depthwise/depthwise.hpp +++ /dev/null @@ -1,551 +0,0 @@ -/* - * Copyright (c) 2018-2019 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_neon.h> -#include "activation.hpp" -#include "padding.hpp" - -namespace depthwise -{ - -namespace nck = neon_convolution_kernels; - -class IDepthwiseConvolution -{ - public: - virtual ~IDepthwiseConvolution() = default; - - virtual int output_size( - int dim_size, - unsigned int padding_before, - unsigned int padding_after - ) const = 0; - - /* Set input tensor and stride. */ - virtual void set_input(const void *inptr) = 0; - virtual void set_input(const void *inptr, int column_stride) = 0; - virtual void set_input(const void *inptr, int row_stride, int column_stride) = 0; - virtual void set_input(const void *inptr, int batch_stride, int row_stride, int column_stride) = 0; - - /* Set output tensor and stride. */ - virtual void set_output(void *outptr) = 0; - virtual void set_output(void *outptr, int column_stride) = 0; - virtual void set_output(void *outptr, int row_stride, int column_stride) = 0; - virtual void set_output(void *outptr, int batch_stride, int row_stride, int column_stride) = 0; - - /* Weights and biases are re-ordered to improve memory access patterns. Use - * these methods to determine the size of the re-pack buffer and to set the - * address (and implicitly reorder the weights and biases into) the buffer. - */ - virtual size_t get_packed_params_size(void) const = 0; - virtual void set_packed_params_buffer(void *) = 0; - - virtual void pack_params(const void *weights, const void *biases=nullptr) const = 0; - virtual void pack_params(void *buffer, const void *weights, const void *biases=nullptr) const = 0; - virtual void pack_params( - void *buffer, - const void* weights, - unsigned int weight_row_stride, - unsigned int weight_col_stride, - const void *biases=nullptr - ) const = 0; - - /* Working space is used to pad tensors on the fly. Before running any - * inference check the amount of space required, allocate and provide a - * pointer to the convolution engine. - */ - virtual size_t get_working_space_size(unsigned int nthreads=1) const = 0; - virtual void set_working_space(void *) = 0; - - virtual unsigned int get_window(void) const = 0; - virtual void run( - unsigned int start, - unsigned int stop, - unsigned int threadid=0 - ) = 0; -}; - -template < - unsigned int OutputTileRows, unsigned int OutputTileCols, - unsigned int KernelRows, unsigned int KernelCols, - unsigned int StrideRows, unsigned int StrideCols, - typename TIn, typename TBias, typename TOut, - typename Derived -> -class DepthwiseConvolutionBase : public IDepthwiseConvolution -{ - public: - // Information about the specific convolution instance - using InputType = TIn; - using BiasType = TBias; - using OutputType = TOut; - 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 stride_rows = StrideRows; - static constexpr int stride_cols = StrideCols; - static constexpr int inner_tile_rows = stride_rows * (output_tile_rows - 1) + kernel_rows; - static constexpr int inner_tile_cols = stride_cols * (output_tile_cols - 1) + kernel_cols; - - /** Create a new depthwise convolution engine. - * - * @param[in] n_batches Number of batches tensors. - * @param[in] n_input_rows Number of rows in input tensor. - * @param[in] n_input_cols Number of columns in input tensor. - * @param[in] n_channels Number of channels in input and output tensors. - */ - DepthwiseConvolutionBase( - int n_batches, int n_input_rows, int n_input_cols, int n_channels, - nck::ActivationFunction activation, - unsigned int padding_top, - unsigned int padding_left, - unsigned int padding_bottom, - unsigned int padding_right - ); - - /** Create a new depthwise convolution engine. - * - * @param[in] n_batches Number of batches tensors. - * @param[in] n_input_rows Number of rows in input tensor. - * @param[in] n_input_cols Number of columns in input tensor. - * @param[in] n_channels Number of channels in input and output tensors. - */ - DepthwiseConvolutionBase( - int n_batches, int n_input_rows, int n_input_cols, int n_channels, - int n_output_rows, int n_output_cols, - nck::ActivationFunction activation, - unsigned int padding_top, - unsigned int padding_left, - unsigned int padding_bottom, - unsigned int padding_right - ); - - // Cannot copy or move a DepthwiseConvolution. - DepthwiseConvolutionBase(DepthwiseConvolutionBase&) = delete; - DepthwiseConvolutionBase operator=(DepthwiseConvolutionBase&) = delete; - - /* Set input tensor and stride. */ - void set_input(const void *inptr) override; - void set_input(const void *inptr, int column_stride) override; - void set_input(const void *inptr, int row_stride, int column_stride) override; - void set_input(const void *inptr, int batch_stride, int row_stride, int column_stride) override; - - /* Set output tensor and stride. */ - void set_output(void *outptr) override; - void set_output(void *outptr, int column_stride) override; - void set_output(void *outptr, int row_stride, int column_stride) override; - void set_output(void *outptr, int batch_stride, int row_stride, int column_stride) override; - - /** Get the number of output rows/columns. - * - * @param[in] dim_size Number of elements in the dimension (rows/columns) - * @param[in] same_padding True if the padding is SAME, otherwise false. - */ - static int get_output_size( - int dim_size, unsigned int padding_before, unsigned int padding_after - ); - - int output_size( - int dim_size, unsigned int padding_before, unsigned int padding_after - ) const override; - - /* Determine how much memory is required to store the packed weights and - * biases. - */ - size_t get_packed_params_size(void) const override; - - /* Set the buffer for the packed weights and biases, and perform the - * packing. - */ - void set_packed_params_buffer(void *buffer) override; - - void pack_params(const void *weights, const void *biases=nullptr) const override; - - void pack_params( - void *buffer, - const void *weights, - const void *biases=nullptr - ) const override; - - void pack_params( - void *buffer, - const void *weights, - unsigned int weight_row_stride, - unsigned int weight_col_stride, - const void *biases=nullptr - ) const override; - - /** Query the amount of working space required. - * @param[in] The largest number of threads which will be used to execute - * the kernel. - */ - size_t get_working_space_size(unsigned int n_threads=1) const override; - - /** Set the working space buffer. - */ - void set_working_space(void *buffer) override; - - /** Get the window of work to be performed by an instance of the operator. - */ - unsigned int get_window(void) const override; - - /** Perform a portion of the work associated with the operator. - * - * Will perform the window of work described by $[start, stop)$. - * - * @param[in] start Start of the window of work to perform. - * @param[in] stop End of the work to perform. - * @param[in] ID of the thread performing the work. - */ - void run( - unsigned int start, - unsigned int stop, - unsigned int threadid=0 - ) override; - - protected: - /** Get the value to use to pad the tensor. - */ - TIn _input_padding_value(void) const; - - /** Implementation of the parameter packing. - */ - void _pack_params( - void *buffer, - const void *weights, - unsigned int weight_row_stride, - unsigned int weight_col_stride, - const void *biases=nullptr - ) const; - - /** Process a tile-row of the tensors. - */ - void process_tile_row( - unsigned int threadid, - int n_channels, - const void* packed_params, - const InputType* inptr, - OutputType* outptr, - int row_pad_in_top, - int row_pad_in_left, - int row_pad_in_bottom, - int row_pad_out_bottom, - int n_tiles, - int n_input_cols, - int n_output_cols - ); - - /** Process a single tile of the tensor. - * - * This method will apply input/output padding (if required) and call the - * depthwise tile implementation. - */ - void process_tile( - unsigned int threadid, - int n_channels, - const void* packed_params, - const InputType* inptr, - OutputType* outptr, - int pad_in_top, - int pad_in_left, - int pad_in_bottom, - int pad_in_right, - int pad_out_bottom, - int pad_out_right - ); - - /** Perform depthwise convolution on a single tile. - */ - template <nck::ActivationFunction Activation> - void execute_tile( - int n_channels, - const void* packed_params, - const InputType* inptr, - unsigned int in_row_stride, - unsigned int in_col_stride, - OutputType* outptr, - unsigned int out_row_stride, - unsigned int out_col_stride - ); - - template <nck::ActivationFunction Activation> - void execute_tile( - int n_channels, - const void* packed_params, - const InputType* inptrs[inner_tile_rows][inner_tile_cols], - OutputType* outptrs[output_tile_rows][output_tile_cols] - ); - - int n_channels(void) const; - - private: - // Member variables of instances of a convolution engine. - const InputType* _input; - OutputType* _output; - void* _packed_parameters; - void* _working_space; // Per-thread working space - const int _n_batches, _n_input_rows, _n_input_cols, _n_channels, - _n_output_rows, _n_output_cols, _n_tile_rows, _n_tile_cols; - const unsigned int _padding_top, _padding_left, _padding_bottom, _padding_right; - const nck::ActivationFunction _activation; - - // Stride information for a convolution instance - int _input_col_stride, _input_row_stride, _input_batch_stride; - int _output_col_stride, _output_row_stride, _output_batch_stride; - - // Methods for getting access to working space - size_t _get_input_working_space_size(void) const; - size_t _get_output_working_space_size(void) const; - - void *_get_input_working_space(unsigned int threadid) const; - void *_get_output_working_space(unsigned int threadid) const; -}; - - -template < - unsigned int OutputTileRows, unsigned int OutputTileCols, - unsigned int KernelRows, unsigned int KernelCols, - unsigned int StrideRows, unsigned int StrideCols, - typename TIn, typename TBias, typename TOut -> -class DepthwiseConvolution : public DepthwiseConvolutionBase< - OutputTileRows, OutputTileCols, - KernelRows, KernelCols, - StrideRows, StrideCols, - TIn, TBias, TOut, - DepthwiseConvolution< - OutputTileRows, OutputTileCols, - KernelRows, KernelCols, - StrideRows, StrideCols, - TIn, TBias, TOut - > -> -{ - using Base = DepthwiseConvolutionBase< - OutputTileRows, OutputTileCols, - KernelRows, KernelCols, - StrideRows, StrideCols, - TIn, TBias, TOut, - DepthwiseConvolution< - OutputTileRows, OutputTileCols, - KernelRows, KernelCols, - StrideRows, StrideCols, - TIn, TBias, TOut - > >; - friend Base; - using InputType = typename Base::InputType; - using OutputType = typename Base::OutputType; - - public: - using Base::DepthwiseConvolutionBase; - - protected: - template <nck::ActivationFunction Activation> - void execute_tile( - int n_channels, - const void* packed_params, - const TIn* inptr, - unsigned int in_row_stride, - unsigned int in_col_stride, - TOut* outptr, - unsigned int out_row_stride, - unsigned int out_col_stride - ); - - template <nck::ActivationFunction Activation> - void execute_tile( - int n_channels, - const void* packed_params, - const InputType* inptrs[Base::inner_tile_rows][Base::inner_tile_cols], - OutputType* outptrs[Base::output_tile_rows][Base::output_tile_cols] - ); -}; - - -template < - unsigned int OutputTileRows, unsigned int OutputTileCols, - unsigned int KernelRows, unsigned int KernelCols, - unsigned int StrideRows, unsigned int StrideCols -> -class DepthwiseConvolution< - OutputTileRows, OutputTileCols, - KernelRows, KernelCols, - StrideRows, StrideCols, - float, float, float -> : public DepthwiseConvolutionBase< - OutputTileRows, OutputTileCols, - KernelRows, KernelCols, - StrideRows, StrideCols, - float, float, float, - DepthwiseConvolution< - OutputTileRows, OutputTileCols, - KernelRows, KernelCols, - StrideRows, StrideCols, - float, float, float - > -> -{ - using Base = DepthwiseConvolutionBase< - OutputTileRows, OutputTileCols, - KernelRows, KernelCols, - StrideRows, StrideCols, - float, float, float, - DepthwiseConvolution< - OutputTileRows, OutputTileCols, - KernelRows, KernelCols, - StrideRows, StrideCols, - float, float, float - > >; - friend Base; - using InputType = typename Base::InputType; - using OutputType = typename Base::OutputType; - - public: - DepthwiseConvolution( - int n_batches, int n_input_rows, int n_input_cols, int n_channels, - nck::ActivationFunction activation, - unsigned int padding_top, - unsigned int padding_left, - unsigned int padding_bottom, - unsigned int padding_right - ); - - DepthwiseConvolution( - int n_batches, int n_input_rows, int n_input_cols, int n_channels, - int n_output_rows, int n_output_cols, - nck::ActivationFunction activation, - unsigned int padding_top, - unsigned int padding_left, - unsigned int padding_bottom, - unsigned int padding_right - ); - - protected: - template <nck::ActivationFunction Activation> - void execute_tile( - int n_channels, - const void* packed_params, - const float* inptr, - unsigned int in_row_stride, - unsigned int in_col_stride, - float* outptr, - unsigned int out_row_stride, - unsigned int out_col_stride - ); - - template <nck::ActivationFunction Activation> - void execute_tile( - int n_channels, - const void* packed_params, - const float* inptrs[Base::inner_tile_rows][Base::inner_tile_cols], - float* outptrs[Base::output_tile_rows][Base::output_tile_cols] - ); -}; - -#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC -template < - unsigned int OutputTileRows, unsigned int OutputTileCols, - unsigned int KernelRows, unsigned int KernelCols, - unsigned int StrideRows, unsigned int StrideCols -> -class DepthwiseConvolution< - OutputTileRows, OutputTileCols, - KernelRows, KernelCols, - StrideRows, StrideCols, - float16_t, float16_t, float16_t -> : public DepthwiseConvolutionBase< - OutputTileRows, OutputTileCols, - KernelRows, KernelCols, - StrideRows, StrideCols, - float16_t, float16_t, float16_t, - DepthwiseConvolution< - OutputTileRows, OutputTileCols, - KernelRows, KernelCols, - StrideRows, StrideCols, - float16_t, float16_t, float16_t - > -> -{ - using Base = DepthwiseConvolutionBase< - OutputTileRows, OutputTileCols, - KernelRows, KernelCols, - StrideRows, StrideCols, - float16_t, float16_t, float16_t, - DepthwiseConvolution< - OutputTileRows, OutputTileCols, - KernelRows, KernelCols, - StrideRows, StrideCols, - float16_t, float16_t, float16_t - > >; - friend Base; - using InputType = typename Base::InputType; - using OutputType = typename Base::OutputType; - - public: - DepthwiseConvolution( - int n_batches, int n_input_rows, int n_input_cols, int n_channels, - nck::ActivationFunction activation, - unsigned int padding_top, - unsigned int padding_left, - unsigned int padding_bottom, - unsigned int padding_right - ); - - DepthwiseConvolution( - int n_batches, int n_input_rows, int n_input_cols, int n_channels, - int n_output_rows, int n_output_cols, - nck::ActivationFunction activation, - unsigned int padding_top, - unsigned int padding_left, - unsigned int padding_bottom, - unsigned int padding_right - ); - - protected: - template <nck::ActivationFunction Activation> - void execute_tile( - int n_channels, - const void* packed_params, - const float16_t* inptr, - unsigned int in_row_stride, - unsigned int in_col_stride, - float16_t* outptr, - unsigned int out_row_stride, - unsigned int out_col_stride - ); - - template <nck::ActivationFunction Activation> - void execute_tile( - int n_channels, - const void* packed_params, - const float16_t* inptrs[Base::inner_tile_rows][Base::inner_tile_cols], - float16_t* outptrs[Base::output_tile_rows][Base::output_tile_cols] - ); -}; -#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC - -} // namespace depthwise |