| /* |
| * Copyright (c) 2017-2018 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" . All elements of the output matrix will be multiplied by alpha |
| * |
| * @note If the input tensors @p input0 and @p input1 have been reshaped respectively with @ref CLGEMMInterleave4x4Kernel" and @ref CLGEMMTranspose1xWKernel, |
| * the flag @p is_interleaved_transposed must be set to true |
| * |
| * @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 Matrix A. Data types supported: F16/F32 |
| * @param[in] input1 Input tensor containing the Matrix B. 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 |
| * @param[in] is_interleaved_transposed (Optional) True if input0 and input1 have been reshaped respectively using @ref CLGEMMInterleave4x4Kernel and @ref CLGEMMTranspose1xWKernel |
| * @param[in] reshape_info (Optional) GEMM reshape info. If is_interleaved_transposed = true, this object must contain the information to understand how the matrix A and matrix B have been reshaped |
| * @param[in] fp_mixed_precision (Optional) Use wider accumulators (32 bit instead of 16 for FP16) to improve accuracy |
| * |
| */ |
| void configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, float alpha, bool is_interleaved_transposed = true, const GEMMReshapeInfo &reshape_info = GEMMReshapeInfo(), |
| bool fp_mixed_precision = false); |
| /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMMatrixMultiplyKernel |
| * |
| * @param[in] input0 Input tensor containing the Matrix A. Data types supported: F16/F32 |
| * @param[in] input1 Input tensor containing the Matrix B. Data type supported: same as @p input0 |
| * @param[in] 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 |
| * @param[in] is_interleaved_transposed True if input0 and input1 have been reshaped respectively using @ref CLGEMMInterleave4x4Kernel and @ref CLGEMMTranspose1xWKernel |
| * @param[in] reshape_info GEMM reshape info. If is_interleaved_transposed = true, this object must contain the information to understand how the matrix A and matrix B have been reshaped |
| * @param[in] gpu_target GPU Target |
| * @param[in] fp_mixed_precision (Optional) Use wider accumulators (32 bit instead of 16 for FP16) to improve accuracy |
| * |
| * @return a status |
| */ |
| static Status validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, float alpha, bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info, |
| GPUTarget gpu_target, bool fp_mixed_precision = false); |
| |
| // Inherited methods overridden: |
| void run(const Window &window, cl::CommandQueue &queue) override; |
| |
| public: |
| const ICLTensor *_input0; |
| const ICLTensor *_input1; |
| ICLTensor *_output; |
| bool _slide_matrix_b; |
| bool _reinterpret_input_as_3d; |
| bool _reinterpret_output_as_3d; |
| }; |
| } // namespace arm_compute |
| #endif /* __ARM_COMPUTE_CLGEMMMATRIXMULTIPLYKERNEL_H__ */ |