1 /* 2 * Copyright (c) 2017-2022 Arm Limited. 3 * 4 * SPDX-License-Identifier: MIT 5 * 6 * Permission is hereby granted, free of charge, to any person obtaining a copy 7 * of this software and associated documentation files (the "Software"), to 8 * deal in the Software without restriction, including without limitation the 9 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or 10 * sell copies of the Software, and to permit persons to whom the Software is 11 * furnished to do so, subject to the following conditions: 12 * 13 * The above copyright notice and this permission notice shall be included in all 14 * copies or substantial portions of the Software. 15 * 16 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 17 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 18 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 19 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 20 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 21 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 22 * SOFTWARE. 23 */ 24 #ifndef ARM_COMPUTE_CPU_GEMM_MATRIX_MULTIPLY_KERNEL_H 25 #define ARM_COMPUTE_CPU_GEMM_MATRIX_MULTIPLY_KERNEL_H 26 27 #include "src/core/common/Macros.h" 28 #include "src/cpu/ICpuKernel.h" 29 30 namespace arm_compute 31 { 32 namespace cpu 33 { 34 namespace kernels 35 { 36 /** 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 37 * 38 * @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 39 * @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 40 * 41 */ 42 class CpuGemmMatrixMultiplyKernel : public ICpuKernel<CpuGemmMatrixMultiplyKernel> 43 { 44 private: 45 using GemmMatrixMulKernelPtr = std::add_pointer<void(const ITensor *, const ITensor *, ITensor *, const Window &, const ThreadInfo &, float, const bool)>::type; 46 47 public: 48 struct GemmMatrixMulKernel 49 { 50 const char *name; 51 const DataTypeISASelectorPtr is_selected; 52 GemmMatrixMulKernelPtr ukernel; 53 }; 54 55 CpuGemmMatrixMultiplyKernel() = default; 56 ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(CpuGemmMatrixMultiplyKernel); 57 /** Initialise the kernel's input and output. 58 * 59 * @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 60 * These two kernels change the layout of the original matrices to be more cache-friendly. 61 * 62 * @param[in] lhs Left-handside tensor info containing the interleaved Matrix A or the vector A. Data types supported: F16/F32 63 * @param[in] rhs Right-handside tensor info containing the transposed Matrix B if the first input tensor A is not a vector. 64 * If the output tensor is a vector, rhs must contain the matrix B not reshaped. Data type supported: same as @p lhs 65 * @param[out] dst Output tensor to store the result of matrix multiplication. Data type supported: same as @p lhs. 66 * @param[in] alpha Weight of the matrix product 67 * @param[in] is_interleaved (Optional) True if lhs and rhs have been reshaped respectively using @ref CpuGemmInterleave4x4Kernel and @ref CpuGemmTranspose1xWKernel 68 * @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 69 */ 70 void configure(const ITensorInfo *lhs, const ITensorInfo *rhs, ITensorInfo *dst, float alpha, bool is_interleaved, const GEMMReshapeInfo &reshape_info = GEMMReshapeInfo()); 71 /** Static function to check if given info will lead to a valid configuration of @ref CpuGemmMatrixMultiplyKernel 72 * 73 * Similar to @ref CpuGemmMatrixMultiplyKernel::configure() 74 * 75 * @return a status 76 */ 77 static Status validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *dst, float alpha, bool is_interleaved, const GEMMReshapeInfo &reshape_info); 78 79 // Inherited methods overridden: 80 void run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) override; 81 const char *name() const override; 82 83 static const std::vector<GemmMatrixMulKernel> &get_available_kernels(); 84 85 private: 86 /** Common signature for all the matrix multiply functions 87 * 88 * @param[in] lhs Left-handside input tensor. Data types supported: F16/F32 89 * @param[in] rhs Right-handside input tensor. Data types supported: same as @p lhs 90 * @param[out] dst The output tensor. Data type supported: same as @p rhs 91 * @param[in] window Region on which to execute the kernel. 92 * @param[in] info Thread info metadata. 93 * @param[in] alpha Weight of the matrix product. 94 */ 95 96 /** Matrix multiply function to use for the particular tensor types passed to configure() */ 97 GemmMatrixMulKernelPtr _func{ nullptr }; 98 float _alpha{ 1.f }; 99 }; 100 } // namespace kernels 101 } // namespace cpu 102 } // namespace arm_compute 103 #endif /* ARM_COMPUTE_CPU_GEMM_MATRIX_MULTIPLY_KERNEL_H */ 104