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-/*
- * 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_CLGEMMMATRIXMULTIPLYKERNEL_H
-#define ARM_COMPUTE_CLGEMMMATRIXMULTIPLYKERNEL_H
-
-#include "arm_compute/core/CL/ICLKernel.h"
-
-namespace arm_compute
-{
-class ICLTensor;
-
-/** OpenCL kernel to multiply two input matrices "A" and "B" and add a martix "C" if provided. All elements of the output matrix will be multiplied by alpha. In case matrix C is passed, it will be added to the previous result.
- * For the matrix C, the broadcast addition is supported if the flag "broadcast_bias" is set in the GEMMReshapeInfo object
- *
- * @note If the input tensors @p input0 and @p input1 have been reshaped respectively with @ref CLGEMMReshapeLHSMatrixKernel" and @ref CLGEMMReshapeRHSMatrixKernel,
- * the flag @p is_interleaved_transposed must be set to true
- *
- * @attention @p input1 tensor must have at least 2 dimensions (matrix)
- *
- */
-class CLGEMMMatrixMultiplyKernel : public ICLKernel
-{
-public:
- /** Default constructor */
- CLGEMMMatrixMultiplyKernel();
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- CLGEMMMatrixMultiplyKernel(const CLGEMMMatrixMultiplyKernel &) = delete;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- CLGEMMMatrixMultiplyKernel &operator=(const CLGEMMMatrixMultiplyKernel &) = delete;
- /** Allow instances of this class to be moved */
- CLGEMMMatrixMultiplyKernel(CLGEMMMatrixMultiplyKernel &&) = default;
- /** Allow instances of this class to be moved */
- CLGEMMMatrixMultiplyKernel &operator=(CLGEMMMatrixMultiplyKernel &&) = default;
- /** Initialise the kernel's input, output and alpha
- *
- * @param[in] input0 Input tensor containing the Matrix A. Data types supported: F16/F32
- * @param[in] input1 Input tensor containing the Matrix B. Data type supported: same as @p input0
- * @param[in] input2 Input tensor containing the Matrix C (bias). Can be nullptr. Data type supported: same as @p input0
- * @param[out] output Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0
- * @param[in] alpha Weight of the matrix product
- * @param[in] beta (Optional) Weight of vector C. Default value is 0. Only beta = 1 is currently supported.
- * @param[in] is_interleaved_transposed (Optional) True if input0 and input1 have been reshaped respectively using @ref CLGEMMReshapeLHSMatrixKernel and @ref CLGEMMReshapeRHSMatrixKernel
- * @param[in] reshape_info (Optional) GEMM reshape info. If is_interleaved_transposed = true, this object must contain the information to understand how the matrix A and matrix B have been reshaped
- * @param[in] fp_mixed_precision (Optional) Use wider accumulators (32 bit instead of 16 for FP16) to improve accuracy
- * @param[in] activation_info (Optional) Activation to apply after the matrix multiplication
- *
- */
- void configure(const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta = 0.f,
- bool is_interleaved_transposed = true, const GEMMReshapeInfo &reshape_info = GEMMReshapeInfo(), bool fp_mixed_precision = false, const ActivationLayerInfo &activation_info = ActivationLayerInfo());
- /** Initialise the kernel's input, output and alpha
- *
- * @param[in] compile_context The compile context to be used.
- * @param[in] input0 Input tensor containing the Matrix A. Data types supported: F16/F32
- * @param[in] input1 Input tensor containing the Matrix B. Data type supported: same as @p input0
- * @param[in] input2 Input tensor containing the Matrix C (bias). Can be nullptr. Data type supported: same as @p input0
- * @param[out] output Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0
- * @param[in] alpha Weight of the matrix product
- * @param[in] beta (Optional) Weight of vector C. Default value is 0. Only beta = 1 is currently supported.
- * @param[in] is_interleaved_transposed (Optional) True if input0 and input1 have been reshaped respectively using @ref CLGEMMReshapeLHSMatrixKernel and @ref CLGEMMReshapeRHSMatrixKernel
- * @param[in] reshape_info (Optional) GEMM reshape info. If is_interleaved_transposed = true, this object must contain the information to understand how the matrix A and matrix B have been reshaped
- * @param[in] fp_mixed_precision (Optional) Use wider accumulators (32 bit instead of 16 for FP16) to improve accuracy
- * @param[in] activation_info (Optional) Activation to apply after the matrix multiplication
- *
- */
- void configure(const CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta = 0.f,
- bool is_interleaved_transposed = true, const GEMMReshapeInfo &reshape_info = GEMMReshapeInfo(), bool fp_mixed_precision = false, const ActivationLayerInfo &activation_info = ActivationLayerInfo());
- /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMMatrixMultiplyKernel
- *
- * @param[in] input0 Input tensor containing the Matrix A info. Data types supported: F16/F32
- * @param[in] input1 Input tensor containing the Matrix B info. Data type supported: same as @p input0
- * @param[in] input2 Input tensor containing the Matrix C (bias) info. Can be nullptr. Data type supported: same as @p input0
- * @param[in] output Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0
- * @param[in] alpha Weight of the matrix product
- * @param[in] beta Weight of vector C. Default value is 0. Only beta = 1 is currently supported.
- * @param[in] is_interleaved_transposed True if input0 and input1 have been reshaped respectively using @ref CLGEMMReshapeLHSMatrixKernel and @ref CLGEMMReshapeRHSMatrixKernel
- * @param[in] reshape_info GEMM reshape info. If is_interleaved_transposed = true, this object must contain the information to understand how the matrix A and matrix B have been reshaped
- * @param[in] gpu_target GPU Target
- * @param[in] fp_mixed_precision (Optional) Use wider accumulators (32 bit instead of 16 for FP16) to improve accuracy
- * @param[in] activation_info (Optional) Activation to apply after the matrix multiplication
- *
- * @return a status
- */
- static Status validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float alpha, float beta,
- bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info, GPUTarget gpu_target, bool fp_mixed_precision = false, const ActivationLayerInfo &activation_info = ActivationLayerInfo());
-
- // Inherited methods overridden:
- void run(const Window &window, cl::CommandQueue &queue) override;
-
-public:
- const ICLTensor *_input0;
- const ICLTensor *_input1;
- const ICLTensor *_input2;
- ICLTensor *_output;
- bool _slide_matrix_b;
- bool _reinterpret_input_as_3d;
- bool _reinterpret_output_as_3d;
- bool _add_bias;
- bool _broadcast_bias;
-};
-} // namespace arm_compute
-#endif /* ARM_COMPUTE_CLGEMMMATRIXMULTIPLYKERNEL_H */