| /* |
| * Copyright (c) 2017-2020 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_NEGEMMLOWPOUTPUTSTAGE_H |
| #define ARM_COMPUTE_NEGEMMLOWPOUTPUTSTAGE_H |
| |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/runtime/NEON/INESimpleFunctionNoBorder.h" |
| |
| /** This file contains all available output stages for GEMMLowp on NEON. |
| * |
| * In gemmlowp, the "output stage" is the process that takes a final int32 accumulator value (the output of @ref NEGEMMLowpMatrixMultiplyCore), |
| * and processes it to obtain the final ASYMM8 value. |
| * |
| * More information about the GEMMLowp output stage can be found at https://github.com/google/gemmlowp/blob/master/doc/output.md |
| */ |
| |
| namespace arm_compute |
| { |
| class ITensor; |
| class ITensorInfo; |
| |
| /** Basic function to execute NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint on NEON. |
| * |
| * NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint depends on 3 parameters: |
| * |
| * result_fixedpoint_multiplier, result_shift, result_offset_after_shift |
| * |
| * The final result is: |
| * |
| * (FixedPointMul(input[i][k], result_fixedpoint_multiplier) >> result_shift) + result_offset_after_shift |
| * |
| * where FixedPointMul(x, y) is the nearest integer to the following |
| * mathematical expression, evaluated without overflow or intermediate rounding: |
| * |
| * (x * y) / 2^31 |
| * |
| * For more information: https://github.com/google/gemmlowp/blob/master/public/output_stages.h#L68 |
| * |
| * In case the bias tensor is provided, the final result is: |
| * |
| * ((FixedPointMul(input[i][k] + bias[k], result_fixedpoint_multiplier)) >> result_shift) + result_offset_after_shift |
| * |
| * This function calls the following NEON kernels: |
| * |
| * -# @ref NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel |
| * |
| * @note The function accepts also 2 optional input arguments (min and max) which can be used to implement "rectified linear unit" activation functions |
| * after the result is shifted right by result_shift |
| */ |
| class NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint : public INESimpleFunctionNoBorder |
| { |
| public: |
| /** Constructor */ |
| NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint() = default; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint(const NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint &) = delete; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint &operator=(const NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint &) = delete; |
| /** Prevent instances of this class from being moved (As this class contains non movable objects) */ |
| NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint(NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint &&) = delete; |
| /** Prevent instances of this class from being moved (As this class contains non movable objects) */ |
| NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint &operator=(NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint &&) = delete; |
| /** Default destructor */ |
| ~NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint(); |
| /** Initialise the kernel's inputs, 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_fixedpoint_multiplier Fixed point 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 after the fixed point multiplication |
| * @param[in] result_offset_after_shift Offset to be applied to result before converting it back to QASYMM8 |
| * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8. Defaults to the minimum possible 32-bit signed integer. |
| * @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. Defaults to the maximum possible 32-bit signed integer. |
| */ |
| void configure(const ITensor *input, const ITensor *bias, ITensor *output, int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift, |
| int min = std::numeric_limits<int32_t>::lowest(), int max = std::numeric_limits<int32_t>::max()); |
| /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint |
| * |
| * @param[in] input Input tensor. It is the output of @ref NEGEMMLowpMatrixMultiplyCore function. Data type supported: S32 |
| * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases 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. Defaults to the minimum possible 32-bit signed integer. |
| * @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. Defaults to the maximum possible 32-bit signed integer. |
| * |
| * @return a status |
| */ |
| static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min = std::numeric_limits<int32_t>::lowest(), int max = std::numeric_limits<int32_t>::max()); |
| }; |
| /** Basic function to execute NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint on NEON. |
| * |
| * NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint depends on 3 parameters: |
| * |
| * result_fixedpoint_multiplier, result_shift, result_offset_after_shift |
| * |
| * The final result is: |
| * |
| * (FixedPointMul(input[i][k], result_fixedpoint_multiplier) >> result_shift) + result_offset_after_shift |
| * |
| * where FixedPointMul(x, y) is the nearest integer to the following |
| * mathematical expression, evaluated without overflow or intermediate rounding: |
| * |
| * (x * y) / 2^31 |
| * |
| * For more information: https://github.com/google/gemmlowp/blob/master/public/output_stages.h#L68 |
| * |
| * In case the bias tensor is provided, the final result is: |
| * |
| * ((FixedPointMul(input[i][k] + bias[k], result_fixedpoint_multiplier)) >> result_shift) + result_offset_after_shift |
| * |
| * This function calls the following NEON kernels: |
| * |
| * -# @ref NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel |
| * |
| * @note The function accepts also 2 optional input arguments (min and max) which can be used to implement "rectified linear unit" activation functions |
| * after the result is shifted right by result_shift |
| */ |
| class NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint : public INESimpleFunctionNoBorder |
| { |
| public: |
| /** Constructor */ |
| NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint() = default; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint(const NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint &) = delete; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint &operator=(const NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint &) = delete; |
| /** Prevent instances of this class from being moved (As this class contains non movable objects) */ |
| NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint(NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint &&) = delete; |
| /** Prevent instances of this class from being moved (As this class contains non movable objects) */ |
| NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint &operator=(NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint &&) = delete; |
| /** Default destructor */ |
| ~NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint(); |
| /** Initialise the kernel's inputs, 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_SIGNED |
| * @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 |
| * @param[in] result_shift Number of bits to shift right the result after the fixed point multiplication |
| * @param[in] result_offset_after_shift Offset to be applied to result before converting it back to QASYMM8_SIGNED |
| * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8_SIGNED. Defaults to the minimum possible 32-bit signed integer. |
| * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8_SIGNED, |
| * Along with @p min, this value can be used to implement "rectified linear unit" activation functions. Defaults to the maximum possible 32-bit signed integer. |
| */ |
| void configure(const ITensor *input, const ITensor *bias, ITensor *output, int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift, |
| int min = std::numeric_limits<int32_t>::lowest(), int max = std::numeric_limits<int32_t>::max()); |
| /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint |
| * |
| * @param[in] input Input tensor. It is the output of @ref NEGEMMLowpMatrixMultiplyCore function. Data type supported: S32 |
| * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases 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_SIGNED |
| * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8_SIGNED. Defaults to the minimum possible 32-bit signed integer. |
| * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8_SIGNED, |
| * Along with @p min, this value can be used to implement "rectified linear unit" activation functions. Defaults to the maximum possible 32-bit signed integer. |
| * |
| * @return a status |
| */ |
| static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min = std::numeric_limits<int32_t>::lowest(), int max = std::numeric_limits<int32_t>::max()); |
| }; |
| /** Basic function to execute NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint on NEON. |
| * |
| * NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint depends on 2 parameters: |
| * |
| * result_fixedpoint_multiplier, result_shift |
| * |
| * The final result is: |
| * |
| * (FixedPointMul(input[i][k], result_fixedpoint_multiplier) >> result_shift) |
| * |
| * where FixedPointMul(x, y) is the nearest integer to the following |
| * mathematical expression, evaluated without overflow or intermediate rounding: |
| * |
| * (x * y) / 2^31 |
| * |
| * For more information: https://github.com/google/gemmlowp/blob/master/public/output_stages.h#L68 |
| * |
| * In case the bias tensor is provided, the final result is: |
| * |
| * ((FixedPointMul(input[i][k] + bias[k], result_fixedpoint_multiplier)) >> result_shift) + result_offset_after_shift |
| * |
| * This function calls the following NEON kernels: |
| * |
| * -# @ref NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel |
| * |
| * @note The function accepts also 2 optional input arguments (min and max) which can be used to implement "rectified linear unit" activation functions |
| * after the result is shifted right by result_shift |
| */ |
| class NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint : public INESimpleFunctionNoBorder |
| { |
| public: |
| /** Constructor */ |
| NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint() = default; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint(const NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint &) = delete; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint &operator=(const NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint &) = delete; |
| /** Prevent instances of this class from being moved (As this class contains non movable objects) */ |
| NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint(NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint &&) = delete; |
| /** Prevent instances of this class from being moved (As this class contains non movable objects) */ |
| NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint &operator=(NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint &&) = delete; |
| /** Default destructor */ |
| ~NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint(); |
| /** Initialise the kernel's inputs, 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: QSYMM16 |
| * @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 |
| * @param[in] result_shift Number of bits to shift right the result after the fixed point multiplication |
| * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QSYMM16. Defaults to the minimum possible 32-bit signed integer. |
| * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QSYMM16. |
| * Along with @p min, this value can be used to implement "rectified linear unit" activation functions. Defaults to the maximum possible 32-bit signed integer. |
| */ |
| void configure(const ITensor *input, const ITensor *bias, ITensor *output, int result_fixedpoint_multiplier, int result_shift, int min = std::numeric_limits<int32_t>::lowest(), |
| int max = std::numeric_limits<int32_t>::max()); |
| /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint |
| * |
| * @param[in] input Input tensor info. It is the output of @ref NEGEMMLowpMatrixMultiplyCore function. Data type supported: S32 |
| * @param[in] bias Biases tensor info. Only shared biases supported and it can be a nullptr if the addition of biases is not required. |
| * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. |
| * @param[in] output Output tensor info. Data type supported: Data type supported: QSYMM16 |
| * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QSYMM16. Defaults to the minimum possible 32-bit signed integer. |
| * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QSYMM16, |
| * Along with @p min, this value can be used to implement "rectified linear unit" activation functions. Defaults to the maximum possible 32-bit signed integer. |
| * |
| * @return a status |
| */ |
| static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min = std::numeric_limits<int32_t>::lowest(), int max = std::numeric_limits<int32_t>::max()); |
| }; |
| |
| /** Basic function to execute GEMMLowpQuantizeDown kernels on NEON. |
| * |
| * This function calls the following NEON kernels: |
| * |
| * -# @ref NEGEMMLowpQuantizeDownInt32ScaleKernel |
| * -# @ref NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel |
| * -# @ref NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel |
| * -# @ref NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel |
| */ |
| class NEGEMMLowpOutputStage : public INESimpleFunctionNoBorder |
| { |
| public: |
| /** Constructor */ |
| NEGEMMLowpOutputStage() = default; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| NEGEMMLowpOutputStage(const NEGEMMLowpOutputStage &) = delete; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| NEGEMMLowpOutputStage &operator=(const NEGEMMLowpOutputStage &) = delete; |
| /** Prevent instances of this class from being moved (As this class contains non movable objects) */ |
| NEGEMMLowpOutputStage(NEGEMMLowpOutputStage &&) = delete; |
| /** Prevent instances of this class from being moved (As this class contains non movable objects) */ |
| NEGEMMLowpOutputStage &operator=(NEGEMMLowpOutputStage &&) = delete; |
| /** Default destructor */ |
| ~NEGEMMLowpOutputStage(); |
| /** Initialise the kernel's inputs, 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/QASYMM8_SIGNED/QSYMM16 |
| * @param[in] info GEMMLowp output stage metadata. |
| */ |
| void configure(const ITensor *input, const ITensor *bias, ITensor *output, const GEMMLowpOutputStageInfo &info); |
| /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMLowpOutputStage |
| * |
| * @param[in] input Input tensor info. It is the output of @ref NEGEMMLowpMatrixMultiplyCore function. Data type supported: S32 |
| * @param[in] bias Biases tensor info. Only shared biases supported and it can be a nullptr if the addition of biases is not required. |
| * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. |
| * @param[in] output Output tensor info. Data type supported: Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM16 |
| * @param[in] info GEMMLowp output stage metadata. |
| * |
| * @return a status |
| */ |
| static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo &info); |
| }; |
| } // namespace arm_compute |
| #endif /*ARM_COMPUTE_NEGEMMLOWPOUTPUTSTAGE_H */ |