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/*
* Copyright (c) 2017-2021 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_NEGEMMLOWREDUCTIONKERNEL_H
#define ARM_COMPUTE_NEGEMMLOWREDUCTIONKERNEL_H
#include "src/core/NEON/INEKernel.h"
namespace arm_compute
{
// Forward declarations
class ITensor;
struct GEMMLowpReductionKernelInfo;
/** Common interface for all Neon reduction kernels */
class INEGEMMLowpReductionKernel : public INEKernel
{
public:
/** Constructor */
INEGEMMLowpReductionKernel();
/** Prevent instances of this class from being copied (As this class contains pointers)*/
INEGEMMLowpReductionKernel(const INEGEMMLowpReductionKernel &) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers)*/
INEGEMMLowpReductionKernel &operator=(const INEGEMMLowpReductionKernel &) = delete;
/** Allow instances of this class to be moved */
INEGEMMLowpReductionKernel(INEGEMMLowpReductionKernel &&) = default;
/** Allow instances of this class to be moved */
INEGEMMLowpReductionKernel &operator=(INEGEMMLowpReductionKernel &&) = default;
/** Default destructor */
virtual ~INEGEMMLowpReductionKernel() = default;
/** Initialise the kernel's input and output.
*
* @param[in] input Input tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8/QSYMM8_PER_CHANNEL
* @param[out] output Output row-vector of sums of all the entries in each row/col of input tensor. Data type supported: S32
* @param[in] info Kernel metadata:
* - k Number of matrix columns/rows depending on the type of reduction.
* - is_reshaped True if the matrix has been reshaped.
* - scalar Scalar value to multiply each reduced column/row by.
* - mul_byscalar True if each reduced column/row must be multiplied by a scalar value.
*/
virtual void configure(const ITensor *input, ITensor *output, const GEMMLowpReductionKernelInfo &info) = 0;
protected:
const ITensor *_input;
ITensor *_output;
int32_t _k;
int32_t _scalar;
bool _mul_by_scalar;
};
/** Neon kernel used to compute the row-vectors of sums of all the entries in each row of Matrix A.
*
* @note This stage is needed to handle the offset of matrix product
* https://github.com/google/gemmlowp/blob/master/doc/low-precision.md
*/
class NEGEMMLowpMatrixAReductionKernel : public INEGEMMLowpReductionKernel
{
public:
const char *name() const override
{
return "NEGEMMLowpMatrixAReductionKernel";
}
/** Default constructor */
NEGEMMLowpMatrixAReductionKernel() = default;
/** Prevent instances of this class from being copied */
NEGEMMLowpMatrixAReductionKernel(const NEGEMMLowpMatrixAReductionKernel &) = delete;
/** Prevent instances of this class from being copied */
NEGEMMLowpMatrixAReductionKernel &operator=(const NEGEMMLowpMatrixAReductionKernel &) = delete;
/** Allow instances of this class to be moved */
NEGEMMLowpMatrixAReductionKernel(NEGEMMLowpMatrixAReductionKernel &&) = default;
/** Allow instances of this class to be moved */
NEGEMMLowpMatrixAReductionKernel &operator=(NEGEMMLowpMatrixAReductionKernel &&) = default;
/** Default destructor */
~NEGEMMLowpMatrixAReductionKernel() = default;
/** Initialise the kernel's input and output.
*
* @param[in] mtx_a Input tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8/QSYMM8_PER_CHANNEL
* @param[out] vector_sum_row Output row-vector of sums of all the entries in each row of mtx_a. Data type supported: S32
* @param[in] info Kernel metadata:
* - k (num_mtx_a_cols) Number of matrix A columns
* - is_reshaped (is_interleaved4x4) True if the matrix A has been interleaved4x4
* - scalar Scalar value to multiply each reduced row by.
* - mul_byscalar True if each reduced column must be multiplied by a scalar value.
*/
void configure(const ITensor *mtx_a, ITensor *vector_sum_row, const GEMMLowpReductionKernelInfo &info) override;
/** Static function to check if given info will lead to a valid configuration of @ref NEGEMMLowpMatrixAReductionKernel
*
* @param[in] mtx_a Input tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8/QSYMM8_PER_CHANNEL
* @param[in] vector_sum_row Output row-vector of sums of all the entries in each row of mtx_a. Data type supported: S32
* @param[in] info Kernel metadata:
* - k (num_mtx_a_cols) Number of matrix A columns
* - is_reshaped (is_interleaved4x4) True if the matrix A has been interleaved4x4
* - scalar Scalar value to multiply each reduced row by.
* - mul_byscalar True if each reduced column must be multiplied by a scalar value.
*
* @return a status
*/
static Status validate(const ITensorInfo *mtx_a, const ITensorInfo *vector_sum_row, const GEMMLowpReductionKernelInfo &info);
// Inherited methods overridden:
void run(const Window &window, const ThreadInfo &info) override;
private:
/** Execution of the reduction kernel specialized on the input type
*
* @param[in] window Execution window
*/
template <typename T>
void run_internal(const Window &window);
};
/** Neon kernel used to compute the row-vectors of sums of all the entries in each column of Matrix B.
*
* @note This stage is needed to handle the offset of matrix product
* https://github.com/google/gemmlowp/blob/master/doc/low-precision.md
*/
class NEGEMMLowpMatrixBReductionKernel : public INEGEMMLowpReductionKernel
{
public:
const char *name() const override
{
return "NEGEMMLowpMatrixBReductionKernel";
}
/** Default constructor */
NEGEMMLowpMatrixBReductionKernel() = default;
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEGEMMLowpMatrixBReductionKernel(const NEGEMMLowpMatrixBReductionKernel &) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEGEMMLowpMatrixBReductionKernel &operator=(const NEGEMMLowpMatrixBReductionKernel &) = delete;
/** Allow instances of this class to be moved */
NEGEMMLowpMatrixBReductionKernel(NEGEMMLowpMatrixBReductionKernel &&) = default;
/** Allow instances of this class to be moved */
NEGEMMLowpMatrixBReductionKernel &operator=(NEGEMMLowpMatrixBReductionKernel &&) = default;
/** Default destructor */
~NEGEMMLowpMatrixBReductionKernel() = default;
/** Initialise the kernel's input and output.
*
* @param[in] mtx_b Input tensor. Data type supported: Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8/QSYMM8_PER_CHANNEL
* @param[out] vector_sum_col Output row-vector of sums of all the entries in each column of mtx_b. Data type supported: S32
* @param[in] info Kernel metadata:
* - k (num_mtx_b_rows) Number of matrix B rows.
* - is_reshaped (is_transposed1xW) True if the input tensor is transposed 1xW.
* - scalar Scalar value to multiply each reduced row by.
* - mul_byscalar True if each reduced row must be multiplied by a scalar value.
*/
void configure(const ITensor *mtx_b, ITensor *vector_sum_col, const GEMMLowpReductionKernelInfo &info) override;
/** Static function to check if given info will lead to a valid configuration of @ref NEGEMMLowpMatrixBReductionKernel
*
* @param[in] mtx_b Input tensor. Data type supported: Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8/QSYMM8_PER_CHANNEL
* @param[in] vector_sum_col Output row-vector of sums of all the entries in each column of mtx_b. Data type supported: S32
* @param[in] info Kernel metadata:
* - k (num_mtx_b_rows) Number of matrix B rows.
* - is_reshaped (is_transposed1xW) True if the input tensor is transposed 1xW.
* - scalar Scalar value to multiply each reduced row by.
* - mul_byscalar True if each reduced row must be multiplied by a scalar value.
*
* @return a status
*/
static Status validate(const ITensorInfo *mtx_b, const ITensorInfo *vector_sum_col, const GEMMLowpReductionKernelInfo &info);
// Inherited methods overridden:
void run(const Window &window, const ThreadInfo &info) override;
private:
/** Execution of the reduction kernel specialized on the input type
*
* @param[in] window Execution window
* @param[in] info Thread-related information
*/
template <typename T>
void run_internal(const Window &window, const ThreadInfo &info);
};
} // namespace arm_compute
#endif /* ARM_COMPUTE_NEGEMMLOWREDUCTIONKERNEL_H */
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