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/*
* Copyright (c) 2018-2020 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_CLWINOGRADINPUTTRANSFORMKERNEL_H
#define ARM_COMPUTE_CLWINOGRADINPUTTRANSFORMKERNEL_H
#include "src/core/CL/ICLKernel.h"
namespace arm_compute
{
class ICLTensor;
/** OpenCL kernel to perform Winograd input transform.*/
class CLWinogradInputTransformKernel : public ICLKernel
{
public:
/** Default constructor */
CLWinogradInputTransformKernel();
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLWinogradInputTransformKernel(const CLWinogradInputTransformKernel &) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLWinogradInputTransformKernel &operator=(const CLWinogradInputTransformKernel &) = delete;
/** Allow instances of this class to be moved */
CLWinogradInputTransformKernel(CLWinogradInputTransformKernel &&) = default;
/** Allow instances of this class to be moved */
CLWinogradInputTransformKernel &operator=(CLWinogradInputTransformKernel &&) = default;
/** Set the input and output of the kernel.
*
* @note Winograd input transform supports the following configurations for NCWH data layout
* F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3),
* F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3),
* F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5)
*
* @note Winograd input transform supports the following configurations for NHWC data layout
* F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3),
* F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5)
*
* Strides: only unit strides
*
* @param[in] input The input tensor to transform. Data types supported: F16/F32
* @param[in] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_input_transform_shape. Data types supported: Same as @p input
* @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo.
*/
void configure(const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info);
/** Set the input and output of the kernel.
*
* @note Winograd input transform supports the following configurations for NCWH data layout
* F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3),
* F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3),
* F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5)
*
* @note Winograd input transform supports the following configurations for NHWC data layout
* F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3),
* F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5)
*
* Strides: only unit strides
*
* @param[in] compile_context The compile context to be used.
* @param[in] input The input tensor to transform. Data types supported: F16/F32
* @param[in] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_input_transform_shape. Data types supported: Same as @p input
* @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo.
*/
void configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info);
/** Static function to check if given info will lead to a valid configuration of @ref CLWinogradInputTransformKernel
*
* @note Winograd input transform supports the following configurations for NCWH data layout
* F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3),
* F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3),
* F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5)
*
* @note Winograd input transform supports the following configurations for NHWC data layout
* F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3),
* F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5)
*
* Strides: only unit strides
*
* @param[in] input The input tensor to transform. Data types supported: F16/F32
* @param[in] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_input_transform_shape. Data types supported: Same as @p input
* @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo.
*
* @return a status
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *output, const WinogradInfo &winograd_info);
// Inherited methods overridden:
void run(const Window &window, cl::CommandQueue &queue) override;
BorderSize border_size() const override;
private:
using WinogradKey = std::pair<std::pair<int, int>, std::pair<int, int>>;
BorderSize _border_size;
const ICLTensor *_input;
ICLTensor *_output;
DataLayout _data_layout;
int _num_tiles_x;
int _num_tiles_y;
unsigned int _step_z;
};
} // arm_compute
#endif /*ARM_COMPUTE_CLWINOGRADINPUTTRANSFORMKERNEL_H */