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_NEGEMMLOWREDUCTIONKERNEL_H 25 #define ARM_COMPUTE_NEGEMMLOWREDUCTIONKERNEL_H 26 27 #include "src/core/NEON/INEKernel.h" 28 29 namespace arm_compute 30 { 31 // Forward declarations 32 class ITensor; 33 struct GEMMLowpReductionKernelInfo; 34 35 /** Common interface for all NEON reduction kernels */ 36 class INEGEMMLowpReductionKernel : public INEKernel 37 { 38 public: 39 /** Constructor */ 40 INEGEMMLowpReductionKernel(); 41 /** Prevent instances of this class from being copied (As this class contains pointers)*/ 42 INEGEMMLowpReductionKernel(const INEGEMMLowpReductionKernel &) = delete; 43 /** Prevent instances of this class from being copied (As this class contains pointers)*/ 44 INEGEMMLowpReductionKernel &operator=(const INEGEMMLowpReductionKernel &) = delete; 45 /** Allow instances of this class to be moved */ 46 INEGEMMLowpReductionKernel(INEGEMMLowpReductionKernel &&) = default; 47 /** Allow instances of this class to be moved */ 48 INEGEMMLowpReductionKernel &operator=(INEGEMMLowpReductionKernel &&) = default; 49 /** Default destructor */ 50 virtual ~INEGEMMLowpReductionKernel() = default; 51 52 /** Initialise the kernel's input and output. 53 * 54 * @param[in] input Input tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8/QSYMM8_PER_CHANNEL 55 * @param[out] output Output row-vector of sums of all the entries in each row/col of input tensor. Data type supported: S32 56 * @param[in] info Kernel metadata: 57 * - k Number of matrix columns/rows depending on the type of reduction. 58 * - is_reshaped True if the matrix has been reshaped. 59 * - scalar Scalar value to multiply each reduced column/row by. 60 * - mul_byscalar True if each reduced column/row must be multiplied by a scalar value. 61 */ 62 virtual void configure(const ITensor *input, ITensor *output, const GEMMLowpReductionKernelInfo &info) = 0; 63 64 protected: 65 const ITensor *_input; 66 ITensor *_output; 67 int32_t _k; 68 int32_t _scalar; 69 bool _mul_by_scalar; 70 }; 71 72 /** NEON kernel used to compute the row-vectors of sums of all the entries in each row of Matrix A. 73 * 74 * @note This stage is needed to handle the offset of matrix product 75 * https://github.com/google/gemmlowp/blob/master/doc/low-precision.md 76 */ 77 class NEGEMMLowpMatrixAReductionKernel : public INEGEMMLowpReductionKernel 78 { 79 public: name()80 const char *name() const override 81 { 82 return "NEGEMMLowpMatrixAReductionKernel"; 83 } 84 /** Default constructor */ 85 NEGEMMLowpMatrixAReductionKernel() = default; 86 /** Prevent instances of this class from being copied */ 87 NEGEMMLowpMatrixAReductionKernel(const NEGEMMLowpMatrixAReductionKernel &) = delete; 88 /** Prevent instances of this class from being copied */ 89 NEGEMMLowpMatrixAReductionKernel &operator=(const NEGEMMLowpMatrixAReductionKernel &) = delete; 90 /** Allow instances of this class to be moved */ 91 NEGEMMLowpMatrixAReductionKernel(NEGEMMLowpMatrixAReductionKernel &&) = default; 92 /** Allow instances of this class to be moved */ 93 NEGEMMLowpMatrixAReductionKernel &operator=(NEGEMMLowpMatrixAReductionKernel &&) = default; 94 /** Default destructor */ 95 ~NEGEMMLowpMatrixAReductionKernel() = default; 96 /** Initialise the kernel's input and output. 97 * 98 * @param[in] mtx_a Input tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8/QSYMM8_PER_CHANNEL 99 * @param[out] vector_sum_row Output row-vector of sums of all the entries in each row of mtx_a. Data type supported: S32 100 * @param[in] info Kernel metadata: 101 * - k (num_mtx_a_cols) Number of matrix A columns 102 * - is_reshaped (is_interleaved4x4) True if the matrix A has been interleaved4x4 103 * - scalar Scalar value to multiply each reduced row by. 104 * - mul_byscalar True if each reduced column must be multiplied by a scalar value. 105 */ 106 void configure(const ITensor *mtx_a, ITensor *vector_sum_row, const GEMMLowpReductionKernelInfo &info) override; 107 /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMLowpMatrixAReductionKernel 108 * 109 * @param[in] mtx_a Input tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8/QSYMM8_PER_CHANNEL 110 * @param[in] vector_sum_row Output row-vector of sums of all the entries in each row of mtx_a. Data type supported: S32 111 * @param[in] info Kernel metadata: 112 * - k (num_mtx_a_cols) Number of matrix A columns 113 * - is_reshaped (is_interleaved4x4) True if the matrix A has been interleaved4x4 114 * - scalar Scalar value to multiply each reduced row by. 115 * - mul_byscalar True if each reduced column must be multiplied by a scalar value. 116 * 117 * @return a status 118 */ 119 static Status validate(const ITensorInfo *mtx_a, const ITensorInfo *vector_sum_row, const GEMMLowpReductionKernelInfo &info); 120 121 // Inherited methods overridden: 122 void run(const Window &window, const ThreadInfo &info) override; 123 124 private: 125 /** Execution of the reduction kernel specialized on the input type 126 * 127 * @param[in] window Execution window 128 */ 129 template <typename T> 130 void run_internal(const Window &window); 131 }; 132 133 /** NEON kernel used to compute the row-vectors of sums of all the entries in each column of Matrix B. 134 * 135 * @note This stage is needed to handle the offset of matrix product 136 * https://github.com/google/gemmlowp/blob/master/doc/low-precision.md 137 */ 138 class NEGEMMLowpMatrixBReductionKernel : public INEGEMMLowpReductionKernel 139 { 140 public: name()141 const char *name() const override 142 { 143 return "NEGEMMLowpMatrixBReductionKernel"; 144 } 145 /** Default constructor */ 146 NEGEMMLowpMatrixBReductionKernel() = default; 147 /** Prevent instances of this class from being copied (As this class contains pointers) */ 148 NEGEMMLowpMatrixBReductionKernel(const NEGEMMLowpMatrixBReductionKernel &) = delete; 149 /** Prevent instances of this class from being copied (As this class contains pointers) */ 150 NEGEMMLowpMatrixBReductionKernel &operator=(const NEGEMMLowpMatrixBReductionKernel &) = delete; 151 /** Allow instances of this class to be moved */ 152 NEGEMMLowpMatrixBReductionKernel(NEGEMMLowpMatrixBReductionKernel &&) = default; 153 /** Allow instances of this class to be moved */ 154 NEGEMMLowpMatrixBReductionKernel &operator=(NEGEMMLowpMatrixBReductionKernel &&) = default; 155 /** Default destructor */ 156 ~NEGEMMLowpMatrixBReductionKernel() = default; 157 /** Initialise the kernel's input and output. 158 * 159 * @param[in] mtx_b Input tensor. Data type supported: Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8/QSYMM8_PER_CHANNEL 160 * @param[out] vector_sum_col Output row-vector of sums of all the entries in each column of mtx_b. Data type supported: S32 161 * @param[in] info Kernel metadata: 162 * - k (num_mtx_b_rows) Number of matrix B rows. 163 * - is_reshaped (is_transposed1xW) True if the input tensor is transposed 1xW. 164 * - scalar Scalar value to multiply each reduced row by. 165 * - mul_byscalar True if each reduced row must be multiplied by a scalar value. 166 */ 167 void configure(const ITensor *mtx_b, ITensor *vector_sum_col, const GEMMLowpReductionKernelInfo &info) override; 168 /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMLowpMatrixBReductionKernel 169 * 170 * @param[in] mtx_b Input tensor. Data type supported: Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8/QSYMM8_PER_CHANNEL 171 * @param[in] vector_sum_col Output row-vector of sums of all the entries in each column of mtx_b. Data type supported: S32 172 * @param[in] info Kernel metadata: 173 * - k (num_mtx_b_rows) Number of matrix B rows. 174 * - is_reshaped (is_transposed1xW) True if the input tensor is transposed 1xW. 175 * - scalar Scalar value to multiply each reduced row by. 176 * - mul_byscalar True if each reduced row must be multiplied by a scalar value. 177 * 178 * @return a status 179 */ 180 static Status validate(const ITensorInfo *mtx_b, const ITensorInfo *vector_sum_col, const GEMMLowpReductionKernelInfo &info); 181 182 // Inherited methods overridden: 183 void run(const Window &window, const ThreadInfo &info) override; 184 185 private: 186 /** Execution of the reduction kernel specialized on the input type 187 * 188 * @param[in] window Execution window 189 * @param[in] info Thread-related information 190 */ 191 template <typename T> 192 void run_internal(const Window &window, const ThreadInfo &info); 193 }; 194 } // namespace arm_compute 195 196 #endif /* ARM_COMPUTE_NEGEMMLOWREDUCTIONKERNEL_H */ 197