From ebc3a90721fe4a41b8e141466894d4d7185c01b7 Mon Sep 17 00:00:00 2001 From: Michele Di Giorgio Date: Fri, 16 Nov 2018 16:04:25 +0000 Subject: COMPMID-1706: Fuse the bias addition within CLGEMM Change-Id: I378f2023f4fa010f195f76716ac07aa86279bfae Signed-off-by: Michele Di Giorgio Reviewed-on: https://review.mlplatform.org/280 Tested-by: Arm Jenkins Reviewed-by: Gian Marco Iodice --- .../core/CL/kernels/CLGEMMMatrixMultiplyKernel.h | 24 ++++++++++++++-------- .../runtime/CL/functions/CLFullyConnectedLayer.h | 4 ++-- .../runtime/CL/functions/CLGEMMConvolutionLayer.h | 12 ++++++----- 3 files changed, 25 insertions(+), 15 deletions(-) (limited to 'arm_compute') diff --git a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h index 797bda86cf..724a7d67e6 100644 --- a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h +++ b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h @@ -30,12 +30,14 @@ namespace arm_compute { class ICLTensor; -/** OpenCL kernel to multiply two input matrices "A" and "B" . All elements of the output matrix will be multiplied by alpha +/** OpenCL kernel to multiply two input matrices "A" and "B" and add a vector "C" if provided. All elements of the output matrix will be multiplied by alpha. In case vector C is passed, it will be added to the previous result (a broadcast addition will be performed). * * @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 The second input tensor must have at least 2 dimensions (matrix) + * @attention Vector C (@p input2) must be 1D. A broadcast addition is performed. + * + * @attention @p input1 tensor must have at least 2 dimensions (matrix) * */ class CLGEMMMatrixMultiplyKernel : public ICLKernel @@ -55,21 +57,25 @@ public: * * @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 Vector C. 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 * */ - void configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, float alpha, bool is_interleaved_transposed = true, const GEMMReshapeInfo &reshape_info = GEMMReshapeInfo(), - bool fp_mixed_precision = false); + 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); /** 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. Data types supported: F16/F32 - * @param[in] input1 Input tensor containing the Matrix B. Data type supported: same as @p input0 + * @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 Vector C 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 @@ -77,8 +83,8 @@ public: * * @return a status */ - static Status validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, float alpha, bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info, - GPUTarget gpu_target, bool fp_mixed_precision = false); + 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); // Inherited methods overridden: void run(const Window &window, cl::CommandQueue &queue) override; @@ -86,10 +92,12 @@ public: 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 _has_vec_c; }; } // namespace arm_compute #endif /* __ARM_COMPUTE_CLGEMMMATRIXMULTIPLYKERNEL_H__ */ diff --git a/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h b/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h index d6d88cec55..e800dd7cbb 100644 --- a/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h +++ b/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2018 ARM Limited. + * Copyright (c) 2017-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -136,7 +136,7 @@ private: CLGEMM _mm_gemm; CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp; CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint _gemmlowp_output_stage; - CLGEMMMatrixAccumulateBiasesKernel _accumulate_biases_kernel; + CLGEMMMatrixAccumulateBiasesKernel _accumulate_biases_kernel; // TODO(COMPMID-1889): Use CLGEMM to add bias in CLFullyConnectedLayer CLTensor _flatten_output; CLTensor _gemmlowp_output; CLTensor _converted_weights_output; diff --git a/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h index d7694a8328..b304576f33 100644 --- a/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h +++ b/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2018 ARM Limited. + * Copyright (c) 2017-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -163,7 +163,7 @@ private: * @param[in, out] output Output tensor. Data types supported: Same as @p input, * except for input of QASYMM8 type where output should be of S32 type. * @param[in] gemmlowp_output_stage GEMMLowp output stage info - * @param[in] gemm_3d_depth (Optional) Depth of GEMM 3D (Defaults to 1) + * @param[in] gemm_3d_depth Depth of GEMM 3D */ void configure_mm(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const GEMMLowpOutputStageInfo &gemmlowp_output_stage, int gemm_3d_depth = 1); /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMConvolutionLayer matrix multiply routines @@ -175,13 +175,14 @@ private: * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. * Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type. * @param[in] gemmlowp_output_stage GEMMLowp output stage info - * @param[in] gemm_3d_depth (Optional) Depth of GEMM 3D (Defaults to 1) - * @param[in] skip_im2col (Optional) Flag which specifies if im2col has to be skipped. i.e. 1x1 convolution with NHWC data layout. (Default to false) + * @param[in] gemm_3d_depth Depth of GEMM 3D + * @param[in] skip_im2col Flag which specifies if im2col has to be skipped. i.e. 1x1 convolution with NHWC data layout. + * @param[in] run_addition Flag which specifies if @ref CLGEMMMatrixMatrixMultiplyAddition to be run. * * @return a status */ static Status validate_mm(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const GEMMLowpOutputStageInfo &gemmlowp_output_stage, - int gemm_3d_depth = 1, bool skip_im2col = false); + int gemm_3d_depth, bool skip_im2col, bool run_addition); private: CLMemoryGroup _memory_group; @@ -207,6 +208,7 @@ private: bool _is_quantized; bool _is_activationlayer_enabled; bool _is_prepared; + bool _run_addition; }; } // namespace arm_compute #endif /* __ARM_COMPUTE_CLGEMMCONVOLUTIONLAYER_H__ */ -- cgit v1.2.1