arm_compute/runtime/CL/functions/CLConvolution.h - ml/ComputeLibrary - Gitiles

 /*
  * Copyright (c) 2016-2020 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.
  */
 #ifndef ARM_COMPUTE_CLCONVOLUTION_H
 #define ARM_COMPUTE_CLCONVOLUTION_H

 #include "arm_compute/core/CL/kernels/CLConvolutionKernel.h"
 #include "arm_compute/core/CL/kernels/CLFillBorderKernel.h"
 #include "arm_compute/core/Types.h"
 #include "arm_compute/runtime/CL/CLTensor.h"
 #include "arm_compute/runtime/CL/ICLSimpleFunction.h"
 #include "arm_compute/runtime/IFunction.h"
 #include "arm_compute/runtime/IMemoryManager.h"
 #include "arm_compute/runtime/MemoryGroup.h"

 #include <cstdint>
 #include <memory>

 namespace arm_compute
 {
 class ICLTensor;

 /** Basic function to execute convolution of size 3x3. This function calls the following OpenCL kernels:
  *
  * -# @ref CLFillBorderKernel (executed if border_mode == CONSTANT or border_mode == REPLICATE)
  * -# @ref CLConvolution3x3Kernel
  *
  */
 class CLConvolution3x3 : public ICLSimpleFunction
 {
 public:
     /** Initialize the function's source, destination, conv and border_mode.
      *
      * @param[in,out] input                 Source tensor. Data types supported: U8. (Written to only for @p border_mode != UNDEFINED)
      * @param[out]    output                Destination tensor, Data types supported: U8 or S16.
      * @param[in]     conv                  matrix_size x matrix_size S16 coefficients structured as a row-major 2D array in a linear buffer.
      * @param[in]     scale                 Scale of the convolution matrix. If 0 is passed, it will be set to the sum of the coefficients of the convolution or 1 if they add up to 0.
      * @param[in]     border_mode           Strategy to use for borders.
      * @param[in]     constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT.
      */
     void configure(ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value = 0);
     /** Initialize the function's source, destination, conv and border_mode.
      *
      * @param[in]     compile_context       The compile context to be used.
      * @param[in,out] input                 Source tensor. Data types supported: U8. (Written to only for @p border_mode != UNDEFINED)
      * @param[out]    output                Destination tensor, Data types supported: U8 or S16.
      * @param[in]     conv                  matrix_size x matrix_size S16 coefficients structured as a row-major 2D array in a linear buffer.
      * @param[in]     scale                 Scale of the convolution matrix. If 0 is passed, it will be set to the sum of the coefficients of the convolution or 1 if they add up to 0.
      * @param[in]     border_mode           Strategy to use for borders.
      * @param[in]     constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT.
      */
     void configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value = 0);
 };

 /** Basic function to execute square convolution.Currently it supports 5x5, 7x7, 9x9. This function calls the following OpenCL kernels:
  *
  * -# @ref CLFillBorderKernel (executed if border_mode == CONSTANT or border_mode == REPLICATE)
  * -# @ref CLConvolutionKernel or<br/>
  *    @ref CLSeparableConvolutionHorKernel and @ref CLSeparableConvolutionVertKernel (if convolution matrix is separable)
  *
  */
 template <unsigned int matrix_size>
 class CLConvolutionSquare : public IFunction
 {
 public:
     /** Default constructor */
     CLConvolutionSquare(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
     /** Initialize the function's source, destination, conv and border_mode.
      *
      * @param[in,out] input                 Source tensor. Data types supported: U8. (Written to only for @p border_mode != UNDEFINED)
      * @param[out]    output                Destination tensor, Data types supported: U8 or S16.
      * @param[in]     conv                  matrix_size x matrix_size S16 coefficients structured as a row-major 2D array in a linear buffer.
      * @param[in]     scale                 Scale of the convolution matrix. If 0 is passed, it will be set to the sum of the coefficients of the convolution or 1 if they add up to 0.
      * @param[in]     border_mode           Strategy to use for borders.
      * @param[in]     constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT.
      */
     void configure(ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value = 0);
     /** Initialize the function's source, destination, conv and border_mode.
      *
      * @param[in]     compile_context       The compile context to be used.
      * @param[in,out] input                 Source tensor. Data types supported: U8. (Written to only for @p border_mode != UNDEFINED)
      * @param[out]    output                Destination tensor, Data types supported: U8 or S16.
      * @param[in]     conv                  matrix_size x matrix_size S16 coefficients structured as a row-major 2D array in a linear buffer.
      * @param[in]     scale                 Scale of the convolution matrix. If 0 is passed, it will be set to the sum of the coefficients of the convolution or 1 if they add up to 0.
      * @param[in]     border_mode           Strategy to use for borders.
      * @param[in]     constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT.
      */
     void configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value = 0);

     // Inherited methods overriden:
     void run() override;

 private:
     MemoryGroup                                   _memory_group;   /**< Function's memory group */
     CLTensor                                      _tmp;            /**< temporary buffer for output of horizontal pass */
     bool                                          _is_separable;   /**< true if the convolution can be separated */
     CLSeparableConvolutionHorKernel<matrix_size>  _kernel_hor;     /**< kernel for horizontal pass of separated convolution */
     CLSeparableConvolutionVertKernel<matrix_size> _kernel_vert;    /**< kernel for vertical pass of separated convolution */
     CLConvolutionKernel<matrix_size>              _kernel;         /**< kernel for non-separated convolution **/
     CLFillBorderKernel                            _border_handler; /**< kernel for border handling */
 };

 /** Basic function to run 5x5 convolution. */
 using CLConvolution5x5 = CLConvolutionSquare<5>;
 /** Basic function to run 7x7 convolution. */
 using CLConvolution7x7 = CLConvolutionSquare<7>;
 /** Basic function to run 9x9 convolution. */
 using CLConvolution9x9 = CLConvolutionSquare<9>;

 /** Basic function to execute non-square convolution. This function calls the following CL kernels:
  *
  * -# @ref CLFillBorderKernel (executed if border_mode == CONSTANT or border_mode == REPLICATE)
  * -# @ref CLConvolutionRectangleKernel or<br/>
  *
  * @note Convolution rectangle should have dimensions of 3, 5, 7, 9
  */
 class CLConvolutionRectangle : public ICLSimpleFunction
 {
 public:
     /** Initialize the function's source, destination, conv and border_mode.
      *
      * @param[in,out] input                 Source tensor. Data types supported: U8. (Written to only for @p border_mode != UNDEFINED)
      * @param[out]    output                Destination tensor, Data types supported: U8 or S16.
      * @param[in]     conv                  Matrix_size x matrix_size S16 coefficients structured as a row-major 2D array in a linear buffer.
      * @param[in]     rows                  Rows of convolution kernel.
      * @param[in]     cols                  Columns of convolution kernel.
      * @param[in]     scale                 Scale of the convolution matrix. If 0 is passed, it will be set to the sum of the coefficients of the convolution or 1 if they add up to 0.
      * @param[in]     border_mode           Strategy to use for borders.
      * @param[in]     constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT.
      */
     void configure(ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t rows, uint32_t cols, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value = 0);
     /** Initialize the function's source, destination, conv and border_mode.
      *
      * @param[in]     compile_context       The compile context to be used.
      * @param[in,out] input                 Source tensor. Data types supported: U8. (Written to only for @p border_mode != UNDEFINED)
      * @param[out]    output                Destination tensor, Data types supported: U8 or S16.
      * @param[in]     conv                  Matrix_size x matrix_size S16 coefficients structured as a row-major 2D array in a linear buffer.
      * @param[in]     rows                  Rows of convolution kernel.
      * @param[in]     cols                  Columns of convolution kernel.
      * @param[in]     scale                 Scale of the convolution matrix. If 0 is passed, it will be set to the sum of the coefficients of the convolution or 1 if they add up to 0.
      * @param[in]     border_mode           Strategy to use for borders.
      * @param[in]     constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT.
      */
     void configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t rows, uint32_t cols, uint32_t scale, BorderMode border_mode,
                    uint8_t constant_border_value = 0);
 };
 }
 #endif /*ARM_COMPUTE_CLCONVOLUTION_H */
	/*
	* Copyright (c) 2016-2020 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.
	*/
	#ifndef ARM_COMPUTE_CLCONVOLUTION_H
	#define ARM_COMPUTE_CLCONVOLUTION_H

	#include "arm_compute/core/CL/kernels/CLConvolutionKernel.h"
	#include "arm_compute/core/CL/kernels/CLFillBorderKernel.h"
	#include "arm_compute/core/Types.h"
	#include "arm_compute/runtime/CL/CLTensor.h"
	#include "arm_compute/runtime/CL/ICLSimpleFunction.h"
	#include "arm_compute/runtime/IFunction.h"
	#include "arm_compute/runtime/IMemoryManager.h"
	#include "arm_compute/runtime/MemoryGroup.h"

	#include <cstdint>
	#include <memory>

	namespace arm_compute
	{
	class ICLTensor;

	/** Basic function to execute convolution of size 3x3. This function calls the following OpenCL kernels:
	*
	* -# @ref CLFillBorderKernel (executed if border_mode == CONSTANT or border_mode == REPLICATE)
	* -# @ref CLConvolution3x3Kernel
	*
	*/
	class CLConvolution3x3 : public ICLSimpleFunction
	{
	public:
	/** Initialize the function's source, destination, conv and border_mode.
	*
	* @param[in,out] input Source tensor. Data types supported: U8. (Written to only for @p border_mode != UNDEFINED)
	* @param[out] output Destination tensor, Data types supported: U8 or S16.
	* @param[in] conv matrix_size x matrix_size S16 coefficients structured as a row-major 2D array in a linear buffer.
	* @param[in] scale Scale of the convolution matrix. If 0 is passed, it will be set to the sum of the coefficients of the convolution or 1 if they add up to 0.
	* @param[in] border_mode Strategy to use for borders.
	* @param[in] constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT.
	*/
	void configure(ICLTensor input, ICLTensor output, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value = 0);
	/** Initialize the function's source, destination, conv and border_mode.
	*
	* @param[in] compile_context The compile context to be used.
	* @param[in,out] input Source tensor. Data types supported: U8. (Written to only for @p border_mode != UNDEFINED)
	* @param[out] output Destination tensor, Data types supported: U8 or S16.
	* @param[in] conv matrix_size x matrix_size S16 coefficients structured as a row-major 2D array in a linear buffer.
	* @param[in] scale Scale of the convolution matrix. If 0 is passed, it will be set to the sum of the coefficients of the convolution or 1 if they add up to 0.
	* @param[in] border_mode Strategy to use for borders.
	* @param[in] constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT.
	*/
	void configure(const CLCompileContext &compile_context, ICLTensor input, ICLTensor output, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value = 0);
	};

	/** Basic function to execute square convolution.Currently it supports 5x5, 7x7, 9x9. This function calls the following OpenCL kernels:
	*
	* -# @ref CLFillBorderKernel (executed if border_mode == CONSTANT or border_mode == REPLICATE)
	* -# @ref CLConvolutionKernel or<br/>
	* @ref CLSeparableConvolutionHorKernel and @ref CLSeparableConvolutionVertKernel (if convolution matrix is separable)
	*
	*/
	template <unsigned int matrix_size>
	class CLConvolutionSquare : public IFunction
	{
	public:
	/** Default constructor */
	CLConvolutionSquare(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
	/** Initialize the function's source, destination, conv and border_mode.
	*
	* @param[in,out] input Source tensor. Data types supported: U8. (Written to only for @p border_mode != UNDEFINED)
	* @param[out] output Destination tensor, Data types supported: U8 or S16.
	* @param[in] conv matrix_size x matrix_size S16 coefficients structured as a row-major 2D array in a linear buffer.
	* @param[in] scale Scale of the convolution matrix. If 0 is passed, it will be set to the sum of the coefficients of the convolution or 1 if they add up to 0.
	* @param[in] border_mode Strategy to use for borders.
	* @param[in] constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT.
	*/
	void configure(ICLTensor input, ICLTensor output, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value = 0);
	/** Initialize the function's source, destination, conv and border_mode.
	*
	* @param[in] compile_context The compile context to be used.
	* @param[in,out] input Source tensor. Data types supported: U8. (Written to only for @p border_mode != UNDEFINED)
	* @param[out] output Destination tensor, Data types supported: U8 or S16.
	* @param[in] conv matrix_size x matrix_size S16 coefficients structured as a row-major 2D array in a linear buffer.
	* @param[in] scale Scale of the convolution matrix. If 0 is passed, it will be set to the sum of the coefficients of the convolution or 1 if they add up to 0.
	* @param[in] border_mode Strategy to use for borders.
	* @param[in] constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT.
	*/
	void configure(const CLCompileContext &compile_context, ICLTensor input, ICLTensor output, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value = 0);

	// Inherited methods overriden:
	void run() override;

	private:
	MemoryGroup _memory_group; /*< Function's memory group /
	CLTensor _tmp; /*< temporary buffer for output of horizontal pass /
	bool _is_separable; /*< true if the convolution can be separated /
	CLSeparableConvolutionHorKernel<matrix_size> _kernel_hor; /*< kernel for horizontal pass of separated convolution /
	CLSeparableConvolutionVertKernel<matrix_size> _kernel_vert; /*< kernel for vertical pass of separated convolution /
	CLConvolutionKernel<matrix_size> _kernel; /< kernel for non-separated convolution /
	CLFillBorderKernel _border_handler; /*< kernel for border handling /
	};

	/** Basic function to run 5x5 convolution. */
	using CLConvolution5x5 = CLConvolutionSquare<5>;
	/** Basic function to run 7x7 convolution. */
	using CLConvolution7x7 = CLConvolutionSquare<7>;
	/** Basic function to run 9x9 convolution. */
	using CLConvolution9x9 = CLConvolutionSquare<9>;

	/** Basic function to execute non-square convolution. This function calls the following CL kernels:
	*
	* -# @ref CLFillBorderKernel (executed if border_mode == CONSTANT or border_mode == REPLICATE)
	* -# @ref CLConvolutionRectangleKernel or<br/>
	*
	* @note Convolution rectangle should have dimensions of 3, 5, 7, 9
	*/
	class CLConvolutionRectangle : public ICLSimpleFunction
	{
	public:
	/** Initialize the function's source, destination, conv and border_mode.
	*
	* @param[in,out] input Source tensor. Data types supported: U8. (Written to only for @p border_mode != UNDEFINED)
	* @param[out] output Destination tensor, Data types supported: U8 or S16.
	* @param[in] conv Matrix_size x matrix_size S16 coefficients structured as a row-major 2D array in a linear buffer.
	* @param[in] rows Rows of convolution kernel.
	* @param[in] cols Columns of convolution kernel.
	* @param[in] scale Scale of the convolution matrix. If 0 is passed, it will be set to the sum of the coefficients of the convolution or 1 if they add up to 0.
	* @param[in] border_mode Strategy to use for borders.
	* @param[in] constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT.
	*/
	void configure(ICLTensor input, ICLTensor output, const int16_t *conv, uint32_t rows, uint32_t cols, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value = 0);
	/** Initialize the function's source, destination, conv and border_mode.
	*
	* @param[in] compile_context The compile context to be used.
	* @param[in,out] input Source tensor. Data types supported: U8. (Written to only for @p border_mode != UNDEFINED)
	* @param[out] output Destination tensor, Data types supported: U8 or S16.
	* @param[in] conv Matrix_size x matrix_size S16 coefficients structured as a row-major 2D array in a linear buffer.
	* @param[in] rows Rows of convolution kernel.
	* @param[in] cols Columns of convolution kernel.
	* @param[in] scale Scale of the convolution matrix. If 0 is passed, it will be set to the sum of the coefficients of the convolution or 1 if they add up to 0.
	* @param[in] border_mode Strategy to use for borders.
	* @param[in] constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT.
	*/
	void configure(const CLCompileContext &compile_context, ICLTensor input, ICLTensor output, const int16_t *conv, uint32_t rows, uint32_t cols, uint32_t scale, BorderMode border_mode,
	uint8_t constant_border_value = 0);
	};
	}
	#endif /ARM_COMPUTE_CLCONVOLUTION_H /