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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_CLGEMMLOWPMATRIXMULTIPLYCORE_H
#define ARM_COMPUTE_CLGEMMLOWPMATRIXMULTIPLYCORE_H
#include "arm_compute/runtime/CL/CLTensor.h"
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/runtime/MemoryGroup.h"
namespace arm_compute
{
class CLCompileContext;
class IMemoryManager;
class ICLTensor;
class ITensorInfo;
class CLGEMMLowpMatrixMultiplyNativeKernel;
class CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel;
class CLGEMMLowpOffsetContributionKernel;
class CLGEMMLowpOffsetContributionOutputStageKernel;
class CLGEMMLowpMatrixAReductionKernel;
class CLGEMMLowpMatrixBReductionKernel;
namespace opencl
{
namespace kernels
{
class ClGemmReshapeRhsMatrixKernel;
} // namespace kernels
} // namespace opencl
namespace opencl
{
namespace kernels
{
class ClCastKernel;
} // namespace kernels
} // namespace opencl
/** Basic function to execute GEMMLowpMatrixMultiplyCore on OpenCL. */
class CLGEMMLowpMatrixMultiplyCore : public IFunction
{
public:
/** Constructor */
CLGEMMLowpMatrixMultiplyCore(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLGEMMLowpMatrixMultiplyCore(const CLGEMMLowpMatrixMultiplyCore &) = delete;
/** Default move constructor */
CLGEMMLowpMatrixMultiplyCore(CLGEMMLowpMatrixMultiplyCore &&) = default;
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLGEMMLowpMatrixMultiplyCore &operator=(const CLGEMMLowpMatrixMultiplyCore &) = delete;
/** Default move assignment operator */
CLGEMMLowpMatrixMultiplyCore &operator=(CLGEMMLowpMatrixMultiplyCore &&) = default;
/** Default destructor */
~CLGEMMLowpMatrixMultiplyCore();
/** Initialise the kernel's inputs, output
*
* Valid data layouts:
* - NHWC
* - NCHW
*
* Valid data type configurations:
* |src0 |src1 |src2 |dst |
* |:--------------|:------------------|:--------|:--------------|
* |QASYMM8 |QASYMM8 |S32 |QASYMM8 |
* |QASYMM8 |QSYMM8_PER_CHANNEL |S32 |QASYMM8 |
* |QASYMM8 |QSYMM8 |S32 |QASYMM8 |
* |QASYMM8 |QASYMM8 |S32 |S32 |
* |QASYMM8 |QSYMM8_PER_CHANNEL |S32 |S32 |
* |QASYMM8 |QSYMM8 |S32 |S32 |
* |QASYMM8_SIGNED |QASYMM8_SIGNED |S32 |QASYMM8_SIGNED |
* |QASYMM8_SIGNED |QSYMM8_PER_CHANNEL |S32 |QASYMM8_SIGNED |
* |QASYMM8_SIGNED |QSYMM8 |S32 |QASYMM8_SIGNED |
* |QASYMM8_SIGNED |QASYMM8_SIGNED |S32 |S32 |
* |QASYMM8_SIGNED |QSYMM8_PER_CHANNEL |S32 |S32 |
* |QASYMM8_SIGNED |QSYMM8 |S32 |S32 |
*
* @note GEMMLowp: low precision GEMM kernel. [A * B + C]
* This kernel performs the following computations:
*
* -# Convert a values from 8-bit quantized to int32 and add a_offset to each of them.
* -# Convert b values from 8-bit quantized to int32 and add b_offset to each of them.
* -# Compute the matrix product of the resulting a * b in int32.
* -# Quantize to uint8 if gemm_info.gemmlowp_output_stage != NONE
*
* @param[in] a First input tensor (Matrix A). Data type supported: QASYMM8/QASYMM8_SIGNED.
* @param[in] b Second input tensor (Matrix B). Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8/QSYMM8_PER_CHANNEL
* @param[in] c Third input tensor (Matrix C). It can be a nullptr. Data type supported: S32
* @param[out] output Output tensor. Data type supported: S32 or QASYMM8/QASYMM8_SIGNED if gemm_info.gemmlowp_output_stage != NONE
* @param[in] gemm_info (Optional) Specifies if the matrix A and/or matrix B have been reshaped and
* if the reshape of matrix B should be executed only for the first run
*/
void configure(const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, const GEMMInfo &gemm_info = GEMMInfo());
/** Initialise the kernel's inputs, output
*
* @note GEMMLowp: low precision GEMM kernel. [A * B + C]
* This kernel performs the following computations:
*
* -# Convert a values from 8-bit quantized to int32 and add a_offset to each of them.
* -# Convert b values from 8-bit quantized to int32 and add b_offset to each of them.
* -# Compute the matrix product of the resulting a * b in int32.
* -# Quantize to uint8 if gemm_info.gemmlowp_output_stage != NONE
*
* @param[in] compile_context The compile context to be used.
* @param[in] a First input tensor (Matrix A). Data type supported: QASYMM8/QASYMM8_SIGNED.
* @param[in] b Second input tensor (Matrix B). Data type supported: same as @p a
* @param[in] c Third input tensor (Matrix C). It can be a nullptr. Data type supported: S32
* @param[out] output Output tensor. Data type supported: S32 or QASYMM8/QASYMM8_SIGNED if gemm_info.gemmlowp_output_stage != NONE
* @param[in] gemm_info (Optional) Specifies if the matrix A and/or matrix B have been reshaped and
* if the reshape of matrix B should be executed only for the first run
*/
void configure(const CLCompileContext &compile_context, const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, const GEMMInfo &gemm_info = GEMMInfo());
/** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpMatrixMultiplyCore
*
* @param[in] a First input tensor info (Matrix A). Data type supported: QASYMM8.
* @param[in] b Second input tensor info (Matrix B). Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8/QSYMM8_PER_CHANNEL
* @param[in] c Third input tensor info (Matrix C). It can be a nullptr. Data type supported: S32
* @param[in] output Output tensor info. Data type supported: S32 or QASYMM8/QASYMM8_SIGNED if gemm_info.gemmlowp_output_stage != NONE
* @param[in] gemm_info (Optional) Specifies if the matrix A and/or matrix B have been reshaped and
* if the reshape of matrix B should be executed only for the first run
*
* @return a status
*/
static Status validate(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *output, const GEMMInfo &gemm_info = GEMMInfo());
// Inherited methods overridden:
void run() override;
void prepare() override;
private:
MemoryGroup _memory_group;
// Kernels used
std::unique_ptr<opencl::kernels::ClCastKernel> _weights_to_qasymm8;
std::unique_ptr<CLGEMMLowpMatrixMultiplyNativeKernel> _mm_native_kernel;
std::unique_ptr<CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel> _mm_reshaped_only_rhs_kernel;
std::unique_ptr<opencl::kernels::ClGemmReshapeRhsMatrixKernel> _mtx_b_reshape_kernel;
std::unique_ptr<CLGEMMLowpMatrixAReductionKernel> _mtx_a_reduction_kernel;
std::unique_ptr<CLGEMMLowpMatrixBReductionKernel> _mtx_b_reduction_kernel;
std::unique_ptr<CLGEMMLowpOffsetContributionKernel> _offset_contribution_kernel;
std::unique_ptr<CLGEMMLowpOffsetContributionOutputStageKernel> _offset_contribution_output_stage_kernel;
// Temporary tensors
CLTensor _qasymm8_weights;
CLTensor _vector_sum_col;
CLTensor _vector_sum_row;
CLTensor _tmp_b;
CLTensor _mm_result_s32;
CLTensor _gemm_output_stage_multipliers;
CLTensor _gemm_output_stage_shifts;
// Tensor pointers
const ICLTensor *_matrix_a;
const ICLTensor *_original_b;
const ICLTensor *_output;
int32_t _a_offset;
int32_t _b_offset;
bool _is_gemm_reshaped;
bool _reshape_b_only_on_first_run;
bool _is_prepared;
bool _run_output_stage;
bool _convert_to_qasymm8;
bool _run_offset_contribution;
};
} // namespace arm_compute
#endif /*ARM_COMPUTE_CLGEMMLOWPMATRIXMULTIPLYCORE_H */