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Diffstat (limited to 'src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h')
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1 files changed, 122 insertions, 0 deletions
diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h new file mode 100644 index 0000000000..71d223b8ac --- /dev/null +++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h @@ -0,0 +1,122 @@ +/* + * 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 "src/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 */ |