/* * Copyright (c) 2017-2019 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_NEGEMMLOWPQUANTIZEDOWNINT32TOUINT8SCALEKERNEL_H #define ARM_COMPUTE_NEGEMMLOWPQUANTIZEDOWNINT32TOUINT8SCALEKERNEL_H #include "arm_compute/core/NEON/INEKernel.h" namespace arm_compute { class ITensor; /** NEON kernel used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8 * * This kernel takes a final int32 accumulator value (the output of @ref NEGEMMLowpMatrixMultiplyKernel), and processes it to obtain the final QASYMM8 value. * The following computations will be performed by the kernel: * * -# Add offset terms to final result * -# Multiply each entry of result by result_mult_int * -# Add bias to final result if bias tensor is not a nullptr * -# Shift the int32 accumulator by result_shift * -# Clamp the value between the specified min and max bounds * -# Clamp the resulting int32 values to the [0..255] range and cast to QASYMM8. * */ class NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel : public INEKernel { public: const char *name() const override { return "NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel"; } /** Constructor */ NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel(); /** Prevent instances of this class from being copied (As this class contains pointers)*/ NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel(const NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &) = delete; /** Prevent instances of this class from being copied (As this class contains pointers)*/ NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &operator=(const NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &) = delete; /** Allow instances of this class to be moved */ NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel(NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &&) = default; /** Allow instances of this class to be moved */ NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &operator=(NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &&) = default; /** Initialise the kernel's input and output. * * @param[in] input Input tensor. Data type supported: S32 * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required. * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. * @param[out] output Output tensor. Data type supported: Data type supported: QASYMM8 * @param[in] result_offset Offset to be added to each element of the input matrix * @param[in] result_mult_int Value to be multiplied to each element of the input matrix when once the result_offset has been add * @param[in] result_shift Number of bits to shift right the result before converting back to QASYMM8 * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8 * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8, * Along with @p min, this value can be used to implement "rectified linear unit" activation functions */ void configure(const ITensor *input, const ITensor *bias, ITensor *output, int result_offset, int result_mult_int, int result_shift, int min = 0, int max = 0); /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel * * @param[in] input Input tensor. Data type supported: S32 * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required. * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. * @param[in] output Output tensor. Data type supported: Data type supported: QASYMM8 * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8 * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8, * Along with @p min, this value can be used to implement "rectified linear unit" activation functions * * @return a status */ static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min = 0, int max = 0); // Inherited methods overridden: void run(const Window &window, const ThreadInfo &info) override; private: /** Template function to run the NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel * * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()). */ template void run(const Window &window); /** Common signature for all the specialised NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel functions * * @param[in] window Region on which to execute the kernel. */ using QuantizeDownFunctionPtr = void (NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::*)(const Window &window); QuantizeDownFunctionPtr _func; const ITensor *_input; const ITensor *_bias; ITensor *_output; int _result_offset; int _result_mult_int; int _result_shift; int _min; int _max; }; } // namespace arm_compute #endif /* ARM_COMPUTE_NEGEMMLOWPQUANTIZEDOWNINT32TOUINT8SCALEKERNEL_H */