1 /* 2 * Copyright (c) 2017-2020 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_CLGEMMMATRIXMULTIPLYKERNEL_H 25 #define ARM_COMPUTE_CLGEMMMATRIXMULTIPLYKERNEL_H 26 27 #include "src/core/CL/ICLKernel.h" 28 29 namespace arm_compute 30 { 31 class ICLTensor; 32 33 /** OpenCL kernel to multiply two input matrices "A" and "B" and add a martix "C" if provided. All elements of the output matrix will be multiplied by alpha. In case matrix C is passed, it will be added to the previous result. 34 * For the matrix C, the broadcast addition is supported if the flag "broadcast_bias" is set in the GEMMReshapeInfo object 35 * 36 * @note If the input tensors @p input0 and @p input1 have been reshaped respectively with @ref CLGEMMReshapeLHSMatrixKernel" and @ref CLGEMMReshapeRHSMatrixKernel, 37 * the flag @p is_interleaved_transposed must be set to true 38 * 39 * @attention @p input1 tensor must have at least 2 dimensions (matrix) 40 * 41 */ 42 class CLGEMMMatrixMultiplyKernel : public ICLKernel 43 { 44 public: 45 /** Default constructor */ 46 CLGEMMMatrixMultiplyKernel(); 47 /** Prevent instances of this class from being copied (As this class contains pointers) */ 48 CLGEMMMatrixMultiplyKernel(const CLGEMMMatrixMultiplyKernel &) = delete; 49 /** Prevent instances of this class from being copied (As this class contains pointers) */ 50 CLGEMMMatrixMultiplyKernel &operator=(const CLGEMMMatrixMultiplyKernel &) = delete; 51 /** Allow instances of this class to be moved */ 52 CLGEMMMatrixMultiplyKernel(CLGEMMMatrixMultiplyKernel &&) = default; 53 /** Allow instances of this class to be moved */ 54 CLGEMMMatrixMultiplyKernel &operator=(CLGEMMMatrixMultiplyKernel &&) = default; 55 /** Initialise the kernel's input, output and alpha 56 * 57 * @param[in] input0 Input tensor containing the Matrix A. Data types supported: F16/F32 58 * @param[in] input1 Input tensor containing the Matrix B. Data type supported: same as @p input0 59 * @param[in] input2 Input tensor containing the Matrix C (bias). Can be nullptr. Data type supported: same as @p input0 60 * @param[out] output Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0 61 * @param[in] alpha Weight of the matrix product 62 * @param[in] beta (Optional) Weight of vector C. Default value is 0. Only beta = 1 is currently supported. 63 * @param[in] is_interleaved_transposed (Optional) True if input0 and input1 have been reshaped respectively using @ref CLGEMMReshapeLHSMatrixKernel and @ref CLGEMMReshapeRHSMatrixKernel 64 * @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 65 * @param[in] fp_mixed_precision (Optional) Use wider accumulators (32 bit instead of 16 for FP16) to improve accuracy 66 * @param[in] activation_info (Optional) Activation to apply after the matrix multiplication 67 * 68 */ 69 void configure(const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta = 0.f, 70 bool is_interleaved_transposed = true, const GEMMReshapeInfo &reshape_info = GEMMReshapeInfo(), bool fp_mixed_precision = false, const ActivationLayerInfo &activation_info = ActivationLayerInfo()); 71 /** Initialise the kernel's input, output and alpha 72 * 73 * @param[in] compile_context The compile context to be used. 74 * @param[in] input0 Input tensor containing the Matrix A. Data types supported: F16/F32 75 * @param[in] input1 Input tensor containing the Matrix B. Data type supported: same as @p input0 76 * @param[in] input2 Input tensor containing the Matrix C (bias). Can be nullptr. Data type supported: same as @p input0 77 * @param[out] output Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0 78 * @param[in] alpha Weight of the matrix product 79 * @param[in] beta (Optional) Weight of vector C. Default value is 0. Only beta = 1 is currently supported. 80 * @param[in] is_interleaved_transposed (Optional) True if input0 and input1 have been reshaped respectively using @ref CLGEMMReshapeLHSMatrixKernel and @ref CLGEMMReshapeRHSMatrixKernel 81 * @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 82 * @param[in] fp_mixed_precision (Optional) Use wider accumulators (32 bit instead of 16 for FP16) to improve accuracy 83 * @param[in] activation_info (Optional) Activation to apply after the matrix multiplication 84 * 85 */ 86 void configure(const CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta = 0.f, 87 bool is_interleaved_transposed = true, const GEMMReshapeInfo &reshape_info = GEMMReshapeInfo(), bool fp_mixed_precision = false, const ActivationLayerInfo &activation_info = ActivationLayerInfo()); 88 /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMMatrixMultiplyKernel 89 * 90 * @param[in] input0 Input tensor containing the Matrix A info. Data types supported: F16/F32 91 * @param[in] input1 Input tensor containing the Matrix B info. Data type supported: same as @p input0 92 * @param[in] input2 Input tensor containing the Matrix C (bias) info. Can be nullptr. Data type supported: same as @p input0 93 * @param[in] output Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0 94 * @param[in] alpha Weight of the matrix product 95 * @param[in] beta Weight of vector C. Default value is 0. Only beta = 1 is currently supported. 96 * @param[in] is_interleaved_transposed True if input0 and input1 have been reshaped respectively using @ref CLGEMMReshapeLHSMatrixKernel and @ref CLGEMMReshapeRHSMatrixKernel 97 * @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 98 * @param[in] gpu_target GPU Target 99 * @param[in] fp_mixed_precision (Optional) Use wider accumulators (32 bit instead of 16 for FP16) to improve accuracy 100 * @param[in] activation_info (Optional) Activation to apply after the matrix multiplication 101 * 102 * @return a status 103 */ 104 static Status validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float alpha, float beta, 105 bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info, GPUTarget gpu_target, bool fp_mixed_precision = false, const ActivationLayerInfo &activation_info = ActivationLayerInfo()); 106 107 // Inherited methods overridden: 108 void run(const Window &window, cl::CommandQueue &queue) override; 109 110 public: 111 const ICLTensor *_input0; 112 const ICLTensor *_input1; 113 const ICLTensor *_input2; 114 ICLTensor *_output; 115 bool _slide_matrix_b; 116 bool _reinterpret_input_as_3d; 117 bool _reinterpret_output_as_3d; 118 bool _add_bias; 119 bool _broadcast_bias; 120 }; 121 } // namespace arm_compute 122 #endif /* ARM_COMPUTE_CLGEMMMATRIXMULTIPLYKERNEL_H */ 123