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/*
* Copyright (c) 2017 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_CLGEMMMATRIXMULTIPLYKERNEL_H__
#define __ARM_COMPUTE_CLGEMMMATRIXMULTIPLYKERNEL_H__
#include "arm_compute/core/CL/ICLKernel.h"
namespace arm_compute
{
class ICLTensor;
/** OpenCL kernel to multiply two input matrices "A" and "B" or to multiply a vector "A" by a matrix "B". All elements of the output matrix/vector will be multiplied by alpha
*
* @note If the output tensor is a matrix, the implementation assumes that the input tensors @p input0 and @p input1 are both matrices and reshaped respectively with @ref CLGEMMInterleave4x4Kernel" and @ref CLGEMMTranspose1xWKernel
* @note If the output tensor is a vector and the data type is F32, the implementation assumes that the first input tensor @p input0 is a vector and the second input tensor @p input1 a matrix. The implementation also assumes that both tensors have not been reshaped
*
* @attention The second input tensor must have at least 2 dimensions (matrix)
*
*/
class CLGEMMMatrixMultiplyKernel : public ICLKernel
{
public:
/** Default constructor */
CLGEMMMatrixMultiplyKernel();
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLGEMMMatrixMultiplyKernel(const CLGEMMMatrixMultiplyKernel &) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLGEMMMatrixMultiplyKernel &operator=(const CLGEMMMatrixMultiplyKernel &) = delete;
/** Allow instances of this class to be moved */
CLGEMMMatrixMultiplyKernel(CLGEMMMatrixMultiplyKernel &&) = default;
/** Allow instances of this class to be moved */
CLGEMMMatrixMultiplyKernel &operator=(CLGEMMMatrixMultiplyKernel &&) = default;
/** Initialise the kernel's input, output and alpha
*
* @param[in] input0 Input tensor containing the interleaved Matrix A or the vector A. Data types supported: F16/F32
* @param[in] input1 Input tensor containing the transposed Matrix B if the first input tensor A is not a vector.
* If the output tensor is a vector, input1 must contain the matrix B not reshaped. Data type supported: same as @p input0
* @param[out] output Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0
* @param[in] alpha Weight of the matrix product
*/
void configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, float alpha);
// Inherited methods overridden:
void run(const Window &window, cl::CommandQueue &queue) override;
private:
const ICLTensor *_input0;
const ICLTensor *_input1;
ICLTensor *_output;
};
}
#endif /* __ARM_COMPUTE_CLGEMMMATRIXMULTIPLYKERNEL_H__ */
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