/* * Copyright (c) 2017-2018 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_CLFULLYCONNECTEDLAYER_H__ #define __ARM_COMPUTE_CLFULLYCONNECTEDLAYER_H__ #include "arm_compute/runtime/CL/ICLSimpleFunction.h" #include "arm_compute/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.h" #include "arm_compute/core/CL/kernels/CLIm2ColKernel.h" #include "arm_compute/core/CL/kernels/CLTransposeKernel.h" #include "arm_compute/runtime/CL/CLMemoryGroup.h" #include "arm_compute/runtime/CL/CLTensor.h" #include "arm_compute/runtime/CL/functions/CLGEMM.h" #include "arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h" #include "arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h" namespace arm_compute { /** Basic function to reshape the weights of Fully Connected layer with OpenCL. This function calls the following kernels: * * -# @ref CLTransposeKernel * * @note The fully connected layer accepts "weights" tensors only with 2 dimensions. */ class CLFullyConnectedLayerReshapeWeights : public ICLSimpleFunction { public: /** Set the input and output tensors. * * @param[in] input Weights tensor. The weights must be 2 dimensional. Data types supported: QS8/QASYMM8/QS16/F16/F32. * @param[out] output Destination tensor which stores the transposed input tensor. Data type supported: Same as @p input. */ void configure(const ICLTensor *input, ICLTensor *output); /** Static function to check if given info will lead to a valid configuration of @ref CLFullyConnectedLayerReshapeWeights * * @param[in] input Weights tensor. The weights must be 2 dimensional. Data types supported: QS8/QASYMM8/QS16/F16/F32. * @param[in] output Destination tensor which stores the transposed input tensor. Data type supported: Same as @p input. * * @return a status */ static Status validate(const ITensorInfo *input, const ITensorInfo *output); }; /** Basic function to compute a Fully Connected layer on OpenCL. This function calls the following OpenCL kernels: * * -# @ref CLIm2ColKernel (called when the input comes from a convolutional layer) * -# @ref CLFullyConnectedLayerReshapeWeights (if @p are_weights_reshaped is set to false and transpose_weights is set to true ) (called once) * -# @ref CLGEMMMatrixMultiplyKernel or @ref CLGEMMLowpMatrixMultiplyCore (if quantized asymmetric) * -# @ref CLGEMMMatrixAccumulateBiasesKernel or @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint (if quantized asymmetric) (if @p biases is not equal to nullptr) * * @note The fully connected layer accepts "weights" tensors only with 2 dimensions. */ class CLFullyConnectedLayer : public IFunction { public: /** Constructor */ CLFullyConnectedLayer(std::shared_ptr memory_manager = nullptr); /** Prevent instances of this class from being copied (As this class contains pointers) */ CLFullyConnectedLayer(const CLFullyConnectedLayer &) = delete; /** Default move constructor */ CLFullyConnectedLayer(CLFullyConnectedLayer &&) = default; /** Prevent instances of this class from being copied (As this class contains pointers) */ CLFullyConnectedLayer &operator=(const CLFullyConnectedLayer &) = delete; /** Default move assignment operator */ CLFullyConnectedLayer &operator=(CLFullyConnectedLayer &&) = default; /** Set the input and output tensors. * * @param[in] input Source tensor. Data type supported: QS8/QASYMM8/QS16/F16/F32. * @param[in] weights Weights tensor. The weights must be 2 dimensional. Data type supported: Same as @p input * @param[in] biases Bias tensor. It can be nullptr. Data type supported:Same as @p input. * @param[out] output Destination tensor. Data type supported: Same as @p input. * @param[in] transpose_weights (Optional) Transpose weights if true. Defaults to true. * @param[in] are_weights_reshaped (Optional) Reshape the weights tensor if false. Defaults to false. * @param[in] retain_internal_weights (Optional) Retain internal reshaped weights. Defaults to false. * Used for reconfiguration purposes. */ void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, bool transpose_weights = true, bool are_weights_reshaped = false, bool retain_internal_weights = false); /** Static function to check if given info will lead to a valid configuration of @ref CLFullyConnectedLayer * * @param[in] input Source tensor. Data type supported: QS8/QASYMM8/QS16/F16/F32. * @param[in] weights Weights tensor. The weights must be 2 dimensional. Data type supported: Same as @p input * @param[in] biases Bias tensor. It can be nullptr. Data type supported:Same as @p input. * @param[in] output Destination tensor. Data type supported: Same as @p input. * @param[in] transpose_weights (Optional) Transpose weights if true. Defaults to true. * @param[in] are_weights_reshaped (Optional) Reshape the weights tensor if false. Defaults to false. * @param[in] retain_internal_weights (Optional) Retain internal reshaped weights. Defaults to false. * Used for reconfiguration purposes. * * @return a status */ static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, bool transpose_weights = true, bool are_weights_reshaped = false, bool retain_internal_weights = false); //Inherited methods override void run() override; void prepare() override; private: void configure_fc_fc(const ICLTensor *input, const ICLTensor *weights, ICLTensor *output); void configure_conv_fc(const ICLTensor *input, const ICLTensor *weights, ICLTensor *output); void configure_mm(const ICLTensor *input, const ICLTensor *weights, ICLTensor *output); CLMemoryGroup _memory_group; CLIm2ColKernel _im2col_kernel; CLFullyConnectedLayerReshapeWeights _reshape_weights_kernel; CLGEMM _mm_gemm; CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp; CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint _gemmlowp_output_stage; CLGEMMMatrixAccumulateBiasesKernel _accumulate_biases_kernel; CLTensor _im2col_output; CLTensor _gemmlowp_output; CLTensor _reshape_weights_output; bool _are_weights_reshaped; bool _is_fc_after_conv; bool _accumulate_biases; bool _is_quantized; const ICLTensor *_original_weights; }; } #endif /* __ARM_COMPUTE_CLFULLYCONNECTEDLAYER_H__ */