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/*
* Copyright (c) 2017-2022 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_CPU_GEMM_MATRIX_MULTIPLY_KERNEL_H
#define ARM_COMPUTE_CPU_GEMM_MATRIX_MULTIPLY_KERNEL_H
#include "src/core/common/Macros.h"
#include "src/cpu/ICpuKernel.h"
namespace arm_compute
{
namespace cpu
{
namespace kernels
{
/** Kernel to multiply two input matrices "A" and "B". All elements of the output matrix/vector will be multiplied by alpha after the matrix multiplication
*
* @note If the output tensor is a matrix, the implementation assumes that the input tensors @p lhs and @p rhs are both matrices and reshaped respectively with @ref CpuGemmInterleave4x4Kernel" and @ref CpuGemmTranspose1xWKernel
* @note If the output tensor is a vector and the data type is F32, the implementation assumes that the first input tensor @p lhs is a vector and the second input tensor @p rhs a matrix. The implementation also assumes that both tensors have not been reshaped
*
*/
class CpuGemmMatrixMultiplyKernel : public ICpuKernel<CpuGemmMatrixMultiplyKernel>
{
private:
using GemmMatrixMulKernelPtr = std::add_pointer<void(
const ITensor *, const ITensor *, ITensor *, const Window &, const ThreadInfo &, float, const bool)>::type;
public:
struct GemmMatrixMulKernel
{
const char *name;
const DataTypeISASelectorPtr is_selected;
GemmMatrixMulKernelPtr ukernel;
};
CpuGemmMatrixMultiplyKernel() = default;
ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(CpuGemmMatrixMultiplyKernel);
/** Initialise the kernel's input and output.
*
* @note If the output tensor is a matrix, the input matrices @p lhs and @p rhs should be the output of the kernels: @ref CpuGemmInterleave4x4Kernel and @ref CpuGemmTranspose1xWKernel
* These two kernels change the layout of the original matrices to be more cache-friendly.
*
* @param[in] lhs Left-handside tensor info containing the interleaved Matrix A or the vector A. Data types supported: F16/F32
* @param[in] rhs Right-handside tensor info containing the transposed Matrix B if the first input tensor A is not a vector.
* If the output tensor is a vector, rhs must contain the matrix B not reshaped. Data type supported: same as @p lhs
* @param[out] dst Output tensor to store the result of matrix multiplication. Data type supported: same as @p lhs.
* @param[in] alpha Weight of the matrix product
* @param[in] is_interleaved (Optional) True if lhs and rhs have been reshaped respectively using @ref CpuGemmInterleave4x4Kernel and @ref CpuGemmTranspose1xWKernel
* @param[in] reshape_info (Optional) GEMM reshape info. If is_interleaved_transposed = true, this object must contain the information to understand how @p lhs and @p rhs have been reshaped
*/
void configure(const ITensorInfo *lhs,
const ITensorInfo *rhs,
ITensorInfo *dst,
float alpha,
bool is_interleaved,
const GEMMReshapeInfo &reshape_info = GEMMReshapeInfo());
/** Static function to check if given info will lead to a valid configuration of @ref CpuGemmMatrixMultiplyKernel
*
* Similar to @ref CpuGemmMatrixMultiplyKernel::configure()
*
* @return a status
*/
static Status validate(const ITensorInfo *lhs,
const ITensorInfo *rhs,
const ITensorInfo *dst,
float alpha,
bool is_interleaved,
const GEMMReshapeInfo &reshape_info);
// Inherited methods overridden:
void run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) override;
const char *name() const override;
static const std::vector<GemmMatrixMulKernel> &get_available_kernels();
private:
/** Common signature for all the matrix multiply functions
*
* @param[in] lhs Left-handside input tensor. Data types supported: F16/F32
* @param[in] rhs Right-handside input tensor. Data types supported: same as @p lhs
* @param[out] dst The output tensor. Data type supported: same as @p rhs
* @param[in] window Region on which to execute the kernel.
* @param[in] info Thread info metadata.
* @param[in] alpha Weight of the matrix product.
*/
/** Matrix multiply function to use for the particular tensor types passed to configure() */
GemmMatrixMulKernelPtr _func{nullptr};
float _alpha{1.f};
};
} // namespace kernels
} // namespace cpu
} // namespace arm_compute
#endif /* ARM_COMPUTE_CPU_GEMM_MATRIX_MULTIPLY_KERNEL_H */
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