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/*
* Copyright (c) 2017-2018 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 <bool is_bounded_relu>
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__ */