text: /*
   * 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_CLLOCALLYCONNECTEDLAYER_H__
  #define __ARM_COMPUTE_CLLOCALLYCONNECTEDLAYER_H__
  
  #include "arm_compute/runtime/IFunction.h"
  
  #include "arm_compute/core/CL/kernels/CLCol2ImKernel.h"
  #include "arm_compute/core/CL/kernels/CLIm2ColKernel.h"
  #include "arm_compute/core/CL/kernels/CLLocallyConnectedMatrixMultiplyKernel.h"
  #include "arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h"
  #include "arm_compute/core/Types.h"
  #include "arm_compute/runtime/CL/CLMemoryGroup.h"
  #include "arm_compute/runtime/CL/CLTensor.h"
  #include "arm_compute/runtime/IMemoryManager.h"
  
  #include <memory>
  
  namespace arm_compute
  {
  class ICLTensor;
  
  /** Basic function to compute the locally connected layer. This function calls the following OpenCL kernels:
   *
   * -# @ref CLWeightsReshapeKernel (executed only once for each configuration)
   * -# @ref CLIm2ColKernel
   * -# @ref CLLocallyConnectedMatrixMultiplyKernel
   * -# @ref CLCol2ImKernel
   */
  class CLLocallyConnectedLayer : public IFunction
  {
  public:
      /** Default constructor */
      CLLocallyConnectedLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
      /** Prevent instances of this class from being copied (As this class contains pointers) */
      CLLocallyConnectedLayer(const CLLocallyConnectedLayer &) = delete;
      /** Default move constructor */
      CLLocallyConnectedLayer(CLLocallyConnectedLayer &&) = default;
      /** Prevent instances of this class from being copied (As this class contains pointers) */
      CLLocallyConnectedLayer &operator=(const CLLocallyConnectedLayer &) = delete;
      /** Default move assignment operator */
      CLLocallyConnectedLayer &operator=(CLLocallyConnectedLayer &&) = default;
      /** Set the input and output tensors.
       *
       * @param[in]  input     Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
       *                       while every optional dimension from 4 and above represent a batch of inputs.
       *                       Data types supported: F32.
       * @param[in]  weights   Weights tensor. Weights are 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM, num_patches]. Data type supported:Same as @p input.
       * @param[in]  biases    Biases tensor. Shared biases supported. Biases are 2D tensor with dimensions [OFM, num_patches]. Data type supported:Same as @p input.
       * @param[out] output    Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
       *                       Data types supported: Same as @p input.
       * @param[in]  conv_info Contains padding and stride information described in @ref PadStrideInfo.
       */
      void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info);
      /** Static function to check if given info will lead to a valid configuration of @ref CLLocallyConnectedLayer
       *
       * @param[in] input     Input tensor info. 3 lower dimensions represent a single input [width, height, IFM],
       *                      while every optional dimension from 4 and above represent a batch of inputs.
       *                      Data types supported: F32.
       * @param[in] weights   Weights tensor info. Weights are 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM, num_patches]. Data type supported:Same as @p input.
       * @param[in] biases    Biases tensor info. Shared biases supported. Biases are 2D tensor with dimensions [OFM, num_patches]. Data type supported:Same as @p input.
       * @param[in] output    Output tensor info. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
       *                      Data types supported: Same as @p input.
       * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
       *
       * @return a status
       */
      static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info);
  
      // Inherited methods overridden:
      void run() override;
  
  private:
      CLMemoryGroup                          _memory_group;
      CLIm2ColKernel                         _input_im2col_kernel;
      CLWeightsReshapeKernel                 _weights_reshape_kernel;
      CLLocallyConnectedMatrixMultiplyKernel _mm_kernel;
      CLCol2ImKernel                         _output_col2im_kernel;
      CLTensor                               _input_im2col_reshaped;
      CLTensor                               _weights_reshaped;
      CLTensor                               _gemm_output;
      bool                                   _is_first_run;
      const ICLTensor                       *_original_weights;
  };
  }
  #endif /* __ARM_COMPUTE_CLLOCALLYCONNECTEDLAYER_H__ */
  