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/*
* Copyright (c) 2016-2019 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_CLGEMM_H__
#define __ARM_COMPUTE_CLGEMM_H__
#include "arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h"
#include "arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.h"
#include "arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.h"
#include "arm_compute/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.h"
#include "arm_compute/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.h"
#include "arm_compute/runtime/CL/CLTensor.h"
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/runtime/IMemoryManager.h"
#include "arm_compute/runtime/MemoryGroup.h"
namespace arm_compute
{
class ICLTensor;
/** Basic function to execute GEMM on OpenCL. This function calls the following OpenCL kernels:
*
* -# @ref CLGEMMReshapeLHSMatrixKernel (only if the RESHAPED_V1 is selected by the heuristic model)
* -# @ref CLGEMMReshapeRHSMatrixKernel (only if either the RESHAPED_V1 or RESHAPED_ONLY_RHS is selected by the select_gemm_type method())
* -# @ref CLGEMMMatrixMultiplyKernel (only if either the NATIVE or RESHAPED_V1 is selected by the select_gemm_type method())
* -# @ref CLGEMMMatrixMultiplyReshapedKernel (only if RESHAPED_V1 is selected by the select_gemm_type method())
* -# @ref CLGEMMMatrixMultiplyReshapedOnlyRHSKernel (only if RESHAPED_ONLY_RHS is selected by the select_gemm_type method())
*
*/
class CLGEMM : public IFunction
{
public:
/** Default constructor.
*
* @param[in] memory_manager (Optional) Memory manager.
*/
CLGEMM(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLGEMM(const CLGEMM &) = delete;
/** Default move constructor */
CLGEMM(CLGEMM &&) = default;
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLGEMM &operator=(const CLGEMM &) = delete;
/** Default move assignment operator */
CLGEMM &operator=(CLGEMM &&) = default;
/** Initialise the kernel's inputs and output
*
* @note GEMM: General Matrix Multiply - [alpha * A * B + beta * C].
*
* @note All tensors must have the same data type.
*
* @note Whilst the first input tensor can be a vector, the second input tensor must be at least a matrix
*
* @param[in] a First input tensor (Matrix or Vector A). Data types supported: F16/F32
* @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 if just the multiplication between @p a and @p b is needed. Data type supported: same as @p a.
* @param[out] output Output tensor. Data type supported: same as @p a
* @param[in] alpha Weight of the matrix product
* @param[in] beta Weight of matrix C
* @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 happen only for the first run. GEMMInfo also contains information about the reshaping
* in case matrix A and matrix B have been already transformed.
*/
void configure(const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, float alpha, float beta, const GEMMInfo &gemm_info = GEMMInfo());
/** Static function to check if given info will lead to a valid configuration of @ref CLGEMM.
*
* @param[in] a First input tensor info (Matrix or Vector A). Data types supported: F16/F32
* @param[in] b Second input tensor info (Matrix B). Data type supported: same as @p a.
* @param[in] c Third input tensor info (Matrix C). It can be a nullptr if just the multiplication between @p a and @p b is needed. Data type supported: same as @p a.
* @param[in] output Output tensor info. Data type supported: same as @p a
* @param[in] alpha Weight of the matrix product
* @param[in] beta Weight of matrix C
* @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 happen only for the first run
*
* @return a status
*/
static Status validate(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *output, float alpha, float beta, const GEMMInfo &gemm_info = GEMMInfo());
// Inherited methods overridden:
void run() override;
void prepare() override;
private:
enum class GEMMType
{
NATIVE,
RESHAPED_V1,
RESHAPED_V2,
RESHAPED_ONLY_RHS
};
// TODO (COMPMID-2095)
static GEMMType select_gemm_type(unsigned int m, unsigned int n, unsigned int k, DataType data_type, bool reshape_b_only_on_first_run, GPUTarget gpu_target);
void configure_native(const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, float alpha, float beta, const GEMMInfo &gemm_info);
void configure_reshaped_v1(const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, float alpha, float beta, const GEMMInfo &gemm_info);
void configure_reshaped_v2(const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, float alpha, float beta, const GEMMInfo &gemm_info);
void configure_reshaped_only_rhs(const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, float alpha, float beta, const GEMMInfo &gemm_info);
static Status validate_native(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *output, float alpha, float beta, const GEMMInfo &gemm_info);
static Status validate_reshaped_v1(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *output, float alpha, float beta, const GEMMInfo &gemm_info);
static Status validate_reshaped_v2(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *output, float alpha, float beta, const GEMMInfo &gemm_info);
static Status validate_reshaped_only_rhs(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *output, float alpha, float beta, const GEMMInfo &gemm_info);
MemoryGroup _memory_group;
CLGEMMMatrixMultiplyKernel _mm_kernel;
CLGEMMReshapeLHSMatrixKernel _reshape_lhs_kernel;
CLGEMMReshapeRHSMatrixKernel _reshape_rhs_kernel;
CLGEMMMatrixMultiplyReshapedKernel _mm_reshaped_kernel;
CLGEMMMatrixMultiplyReshapedOnlyRHSKernel _mm_reshaped_only_rhs_kernel;
CLTensor _tmp_a;
CLTensor _tmp_b;
const ICLTensor *_original_b;
bool _reshape_b_only_on_first_run;
bool _is_prepared;
GEMMType _gemm_type;
};
} // namespace arm_compute
#endif /* __ARM_COMPUTE_CLGEMM_H__ */
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