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/*
* Copyright (c) 2016-2019 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.
*/
#ifndef ARM_COMPUTE_CLCONVOLUTIONKERNEL_H
#define ARM_COMPUTE_CLCONVOLUTIONKERNEL_H
#include "arm_compute/core/CL/ICLSimple2DKernel.h"
#include <cstdint>
namespace arm_compute
{
class ICLTensor;
/****************************************************************************************\
* Square Convolution *
\****************************************************************************************/
/** Interface for the kernel to run an arbitrary size convolution on a tensor. (Currently supports 3x3, 5x5, 7x7 and 9x9).
* The client can supply a convolution matrix \f$ C_{m,n} \f$.
* @f{eqnarray}{
* k_0 &=& \frac{m}{2} \\
* l_0 &=& \frac{n}{2} \\
* sum &=& \sum_{k=0,l=0}^{k=m-1,l=n-1} input(x+k-k_0, y+l-l_0) C_{k,l}
* @f}
*
* @note The above equation for this function is similar to the default OpenCV Filter2D function,
* which actually computes a correlation and not a convolution.
* In case of a real convolution the convolution matrix should be flipped both horizontally and vertically.
*/
template <unsigned int matrix_size>
class CLConvolutionKernel : public ICLSimple2DKernel
{
public:
/** Initialise the kernel's input, output and border mode.
*
* @param[in] input Source tensor. Data types supported: U8.
* @param[out] output Destination tensor, Data types supported: U8, S16.
* @param[in] conv Convolution matrix to apply to the input tensor.
* @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_undefined True if the border mode is undefined. False if it's replicate or constant.
*/
void configure(const ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t scale, bool border_undefined);
// Inherited methods overridden:
BorderSize border_size() const override;
};
/** Interface for the kernel which applies a 3x3 convolution to a tensor. */
using CLConvolution3x3Kernel = CLConvolutionKernel<3>;
/** Interface for the kernel which applies a 5x5 convolution to a tensor. */
using CLConvolution5x5Kernel = CLConvolutionKernel<5>;
/** Interface for the kernel which applies a 7x7 convolution to a tensor. */
using CLConvolution7x7Kernel = CLConvolutionKernel<7>;
/** Interface for the kernel which applies a 9x9 convolution to a tensor. */
using CLConvolution9x9Kernel = CLConvolutionKernel<9>;
/****************************************************************************************\
* Separable Square Convolution *
\****************************************************************************************/
/** Kernel for the Horizontal pass of a Separable Convolution. Currently support 5x5, 7x7, 9x9 */
template <unsigned int matrix_size>
class CLSeparableConvolutionHorKernel : public ICLSimple2DKernel
{
public:
/** Default Constructor */
CLSeparableConvolutionHorKernel();
/** Initialise the kernel's input, output and border mode.
*
* @param[in] input Source tensor. Data types supported: U8.
* @param[out] output Destination tensor, Data types supported: S16.
* @param[in] conv Convolution matrix to apply to the input tensor.
* @param[in] border_undefined True if the border mode is undefined. False if it's replicate or constant.
*/
void configure(const ICLTensor *input, ICLTensor *output, const int16_t *conv, bool border_undefined);
// Inherited methods overridden:
BorderSize border_size() const override;
private:
BorderSize _border_size; /**< Border size */
};
/** Interface for the kernel which applies a horizontal pass of 5x5 convolution to a tensor. */
using CLSeparableConvolution5x5HorKernel = CLSeparableConvolutionHorKernel<5>;
/** Interface for the kernel which applies a horizontal pass of 7x7 convolution to a tensor. */
using CLSeparableConvolution7x7HorKernel = CLSeparableConvolutionHorKernel<7>;
/** Interface for the kernel which applies a horizontal pass of 9x9 convolution to a tensor. */
using CLSeparableConvolution9x9HorKernel = CLSeparableConvolutionHorKernel<9>;
/** Kernel for the Vertical pass of a Separable Convolution. Currently supports 5x5, 7x7, 9x9 */
template <unsigned int matrix_size>
class CLSeparableConvolutionVertKernel : public ICLSimple2DKernel
{
public:
/** Initialise the kernel's input, output and border mode.
*
* @param[in] input Source tensor. Data types supported: S16.
* @param[out] output Destination tensor, Data types supported: U8, S16.
* @param[in] conv Convolution matrix to apply to the input tensor.
* @param[in] scale Scale of the convolution matrix.
* @param[in] border_undefined True if the border mode is undefined. False if it's replicate or constant.
* @param[in] data_type Data type to use for intermeidate result. @sa data_type_for_convolution
*/
void configure(const ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t scale, bool border_undefined, DataType data_type = DataType::S32);
// Inherited methods overridden:
BorderSize border_size() const override;
};
/** Interface for the kernel which applies a vertical pass of 5x5 convolution to a tensor. */
using CLSeparableConvolution5x5VertKernel = CLSeparableConvolutionVertKernel<5>;
/** Interface for the kernel which applies a vertical pass of 7x7 convolution to a tensor. */
using CLSeparableConvolution7x7VertKernel = CLSeparableConvolutionVertKernel<7>;
/** Interface for the kernel which applies a vertical pass of 9x9 convolution to a tensor. */
using CLSeparableConvolution9x9VertKernel = CLSeparableConvolutionVertKernel<9>;
/****************************************************************************************\
* Rectangle Convolution *
\****************************************************************************************/
/** Kernel for the running convolution on a rectangle matrix.
*
* @note Supports combinations of 3,5,7 and 9.
*/
class CLConvolutionRectangleKernel : public ICLKernel
{
public:
/** Default constructor */
CLConvolutionRectangleKernel();
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLConvolutionRectangleKernel(const CLConvolutionRectangleKernel &) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLConvolutionRectangleKernel &operator=(const CLConvolutionRectangleKernel &) = delete;
/** Allow instances of this class to be moved */
CLConvolutionRectangleKernel(CLConvolutionRectangleKernel &&) = default;
/** Allow instances of this class to be moved */
CLConvolutionRectangleKernel &operator=(CLConvolutionRectangleKernel &&) = default;
/** Initialise the kernel's input, output and border mode.
*
* @param[in] input Source tensor. Data types supported: U8.
* @param[out] output Destination tensor, Data types supported: U8, S16.
* @param[in] conv Convolution matrix to apply to the input tensor.
* @param[in] width Width of convolution matrix (Number of columns)
* @param[in] height Height of convolution matrix (Number of rows)
* @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_undefined True if the border mode is undefined. False if it's replicate or constant.
*/
void configure(const ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t width, uint32_t height, uint32_t scale, bool border_undefined);
// Inherited methods overridden:
void run(const Window &window, cl::CommandQueue &queue) override;
BorderSize border_size() const override;
private:
BorderSize _border_size;
const ICLTensor *_input;
ICLTensor *_output;
};
} // namespace arm_compute
#endif /*ARM_COMPUTE_CLCONVOLUTIONKERNEL_H */
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