text: /*
   * Copyright (c) 2018-2020 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_CLCONVERTFULLYCONNECTEDWEIGHTSKERNEL_H
  #define ARM_COMPUTE_CLCONVERTFULLYCONNECTEDWEIGHTSKERNEL_H
  
  #include "src/core/CL/ICLKernel.h"
  
  namespace arm_compute
  {
  class ICLTensor;
  
  /** Interface to convert the 2D Fully Connected weights from NCHW to NHWC or vice versa.
   *
   * @note This function can be applied to the 2D weights used by a Fully Connected layer if:
   *       - It follows a Convolution layer
   *       - The data layout used by the network does not match the one the model has been trained in.
   *
   * @note This function assumes the weights are already reshaped (transposed)
   */
  class CLConvertFullyConnectedWeightsKernel : public ICLKernel
  {
  public:
      /** Default constructor */
      CLConvertFullyConnectedWeightsKernel();
      /** Prevent instances of this class from being copied (As this class contains pointers) */
      CLConvertFullyConnectedWeightsKernel(const CLConvertFullyConnectedWeightsKernel &) = delete;
      /** Prevent instances of this class from being copied (As this class contains pointers) */
      CLConvertFullyConnectedWeightsKernel &operator=(const CLConvertFullyConnectedWeightsKernel &) = delete;
      /** Allow instances of this class to be moved */
      CLConvertFullyConnectedWeightsKernel(CLConvertFullyConnectedWeightsKernel &&) = default;
      /** Allow instances of this class to be moved */
      CLConvertFullyConnectedWeightsKernel &operator=(CLConvertFullyConnectedWeightsKernel &&) = default;
      /** Default destructor */
      ~CLConvertFullyConnectedWeightsKernel() = default;
      /** Set the input and output tensor.
       *
       * @param[in]  input                Source weights tensor to convert. Must be 2 dimensional. Data types supported: All.
       * @param[out] output               The converted weights tensor. Shape and Data Type: Same as @p input.
       * @param[in]  original_input_shape Shape of the original input tensor (the one entering fully connected layer).
       * @param[in]  data_layout          The data layout the weights have been trained in.
       */
      void configure(const ICLTensor *input, ICLTensor *output, const TensorShape &original_input_shape, DataLayout data_layout);
      /** Set the input and output tensor.
       *
       * @param[in]  compile_context      The compile context to be used.
       * @param[in]  input                Source weights tensor to convert. Must be 2 dimensional. Data types supported: All.
       * @param[out] output               The converted weights tensor. Shape and Data Type: Same as @p input.
       * @param[in]  original_input_shape Shape of the original input tensor (the one entering fully connected layer).
       * @param[in]  data_layout          The data layout the weights have been trained in.
       */
      void configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const TensorShape &original_input_shape, DataLayout data_layout);
      /** Static function to check if given info will lead to a valid configuration of @ref CLConvertFullyConnectedWeightsKernel
       *
       * @param[in] input                Source weights tensor info to convert. Must be 2 dimensional. Data types supported: All.
       * @param[in] output               The converted weights tensor info. Shape and Data Type: Same as @p input.
       * @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer).
       * @param[in] data_layout          The data layout the weights have been trained in.
       */
      static Status validate(const ITensorInfo *input, const ITensorInfo *output, const TensorShape &original_input_shape, DataLayout data_layout);
  
      // Inherited methods overridden:
      void run(const Window &window, cl::CommandQueue &queue) override;
  
  private:
      const ICLTensor *_input;
      ICLTensor       *_output;
  };
  } // namespace arm_compute
  #endif /*ARM_COMPUTE_CLCONVERTFULLYCONNECTEDWEIGHTSKERNEL_H */
  