1 /* 2 * Copyright (c) 2019-2022 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_GEMMLOWP_QUANTIZEDOWN_INT32TOINT16_SCALEBYFIXEDPOINT_KERNEL_H 25 #define ARM_COMPUTE_CPU_GEMMLOWP_QUANTIZEDOWN_INT32TOINT16_SCALEBYFIXEDPOINT_KERNEL_H 26 27 #include "arm_compute/core/KernelDescriptors.h" 28 #include "src/core/common/Macros.h" 29 #include "src/cpu/ICpuKernel.h" 30 31 namespace arm_compute 32 { 33 // Forward declaration 34 class ITensor; 35 namespace cpu 36 { 37 namespace kernels 38 { 39 /** Kernel used to quantize down the int32 accumulator values of GEMMLowp to QSYMM16 40 * 41 * This kernel takes a final int32 accumulator value (the output of @ref CpuGemmLowpMatrixMultiplyKernel), and processes it to obtain the final QSYMM16 value. 42 * The following computations will be performed by the kernel: 43 * 44 * -# Compute fixed point multiplication between each entry of input by result_fixedpoint_multiplier 45 * -# Add bias to final result if bias tensor is not a nullptr 46 * -# Round to nearest division by a power-of-two using result_shift 47 * -# Clamp the value between the specified min and max bounds 48 * -# Clamp the resulting int32 values to the [-32768, 32767] range and cast to QSYMM16. 49 * 50 */ 51 class CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel : public ICpuKernel<CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel> 52 { 53 public: 54 CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel() = default; 55 ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel); 56 /** Initialise the kernel's input and output. 57 * 58 * @param[in] src Input tensor info. Data type supported: S32 59 * @param[in] bias Biases tensor info. Only shared biases supported and it can be a nullptr if the biases addition is not required. 60 * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. 61 * @param[out] dst Output tensor info. Data type supported: Data type supported: QSYMM16 62 * @param[in] result_fixedpoint_multiplier Fixed point value to be multiplied to each element of the input matrix when once the result_offset has been add 63 * @param[in] result_shift Integer value used to round to nearest division by a power-of-two the result after the fixed point multiplication 64 * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QSYMM16. Defaults to 0. 65 * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QSYMM16. 66 * Along with @p min, this value can be used to implement "rectified linear unit" activation functions. Defaults to 0. 67 */ 68 void configure(ITensorInfo *src, ITensorInfo *bias, ITensorInfo *dst, int result_fixedpoint_multiplier, int result_shift, int min = 0, int max = 0); 69 /** Static function to check if given info will lead to a valid configuration 70 * 71 * Similar to CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel::configure() 72 * 73 * @return a status 74 */ 75 static Status validate(const ITensorInfo *src, const ITensorInfo *bias, const ITensorInfo *dst, int min = 0, int max = 0); 76 77 // Inherited methods overridden: 78 void run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) override; 79 const char *name() const override; 80 81 private: 82 /** Template function to run the CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel 83 * 84 * @param[in] src Input tensor info 85 * @param[in] bias Bias tensor info 86 * @param[out] dst Output tensor info 87 * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()). 88 */ 89 template <bool is_bounded_relu> 90 void run_internal(const ITensor *src, const ITensor *bias, ITensor *dst, const Window &window); 91 92 /** Common signature for all the specialised CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel functions 93 * 94 * @param[in] src Input tensor info 95 * @param[in] bias Bias tensor info 96 * @param[out] dst Output tensor info 97 * @param[in] window Region on which to execute the kernel. 98 */ 99 using QuantizeDownFunctionPtr = void (CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel::*)( 100 const ITensor *src, const ITensor *bias, ITensor *dst, const Window &window); 101 102 QuantizeDownFunctionPtr _func{ nullptr }; 103 int _result_fixedpoint_multiplier{ 0 }; 104 int _result_shift{ 0 }; 105 int _min{ 0 }; 106 int _max{ 0 }; 107 }; 108 } // namespace kernels 109 } // namespace cpu 110 } // namespace arm_compute 111 #endif /* ARM_COMPUTE_CPU_GEMMLOWP_QUANTIZEDOWN_INT32TOINT16_SCALEBYFIXEDPOINT_KERNEL_H */ 112