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_NEDECONVOLUTIONLAYER_H__
  #define __ARM_COMPUTE_NEDECONVOLUTIONLAYER_H__
  
  #include "arm_compute/runtime/CPP/functions/CPPUpsample.h"
  #include "arm_compute/runtime/NEON/functions/NEConvolutionLayer.h"
  #include "arm_compute/runtime/NEON/functions/NEDirectConvolutionLayer.h"
  
  #include "arm_compute/core/Types.h"
  #include "arm_compute/runtime/IFunction.h"
  #include "arm_compute/runtime/IMemoryManager.h"
  #include "arm_compute/runtime/MemoryGroup.h"
  #include "arm_compute/runtime/Tensor.h"
  
  #include <memory>
  
  namespace arm_compute
  {
  /** Function to run the deconvolution layer.
   *
   * Deconvolution Layer is the backward pass of Convolution Layer. First we transform the input depending on the stride and pad info and then perfrom a 1x1
   * convolution pass. Input stride defines how many zeroes we should put between each element of the input, pad is the amount of padding and finaly a is a user
   * specified value where a < stride - 1 that increases the padding top and right of the input image.
   *
   *  The relation between input to output is as follows:
   *       width_output = round((width_input − 1) ∗ (stride_x - 1) − 2 ∗ padding_x + kernel_x + inner_border_right )
   *       height_output = round((height_input − 1) ∗ (stride_y - 1) − 2 ∗ padding_y + kernel_y + inner_border_top )
   *
   *  where
   *      width is the size of the first input dimension.
   *      height is the size of the second input dimension.
   *      width_output is the size of the first output dimension.
   *      height_output is the size of the second output dimension.
   *      kernel_x and kernel_y are the convolution sizes in x and y.
   *      inner_border_right and inner_border_top the number of zeros added to the top and right edges of the input.
   *      stride_x and stride_y is the input stride of the first and second dimension.
   *
   *  This function calls the following NEON kernels:
   *
   * -# @ref NEDirectConvolutionLayer
   *
   */
  class NEDeconvolutionLayer : public IFunction
  {
  public:
      /** Default constructor */
      NEDeconvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
  
      /** Prevent instances of this class from being copied (As this class contains pointers) */
      NEDeconvolutionLayer(const NEDeconvolutionLayer &) = delete;
      /** Prevent instances of this class from being copied (As this class contains pointers) */
      NEDeconvolutionLayer &operator=(const NEDeconvolutionLayer &) = delete;
      /** Allow instances of this class to be moved */
      NEDeconvolutionLayer(NEDeconvolutionLayer &&) = default;
      /** Allow instances of this class to be moved */
      NEDeconvolutionLayer &operator=(NEDeconvolutionLayer &&) = default;
      /** Default destructor */
      virtual ~NEDeconvolutionLayer() = default;
      /** Set the input, weights, biases and output tensors.
       *
       * @param[in,out] input              Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: F32.
       * @param[in]     weights            The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input.
       * @param[in]     bias               Optional, ignored if NULL. The biases have one dimension. Data type supported: Same as @p input.
       * @param[out]    output             Output tensor. The output has the same number of dimensions as the @p input.
       * @param[in]     info               Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo.
       * @param[in]     inner_border_right The number of zeros added to right edge of the input.
       * @param[in]     inner_border_top   The number of zeros added to top edge of the input.
       *
       */
      void configure(ITensor *input, const ITensor *weights, const ITensor *bias, ITensor *output, const PadStrideInfo &info,
                     unsigned int inner_border_right, unsigned int inner_border_top);
      /** Static function to check if given info will lead to a valid configuration of @ref NEDeconvolutionLayer
       *
       * @param[in] input              Input tensor info. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: F32.
       * @param[in] weights            The 4d weights info with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input.
       * @param[in] bias               (Optional) The biases have one dimension. Data type supported: Same as @p input.
       * @param[in] output             Output tensor info. The output has the same number of dimensions as the @p input.
       * @param[in] info               Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo.
       * @param[in] inner_border_right The number of zeros added to right edge of the input.
       * @param[in] inner_border_top   The number of zeros added to top edge of the input.
       *
       * @return a status
       */
      static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *bias, const ITensorInfo *output, const PadStrideInfo &info,
                             unsigned int inner_border_right, unsigned int inner_border_top);
  
      // Inherited methods overridden:
      void run() override;
  
  private:
      MemoryGroup        _memory_group;
      NEConvolutionLayer _conv_f;
      CPPUpsample        _upsample_f;
      Tensor             _scaled_output;
      ITensor           *_input;
      PadStrideInfo      _info;
      std::pair<unsigned int, unsigned int> _inner_border;
  };
  } // arm_compute
  #endif /* __ARM_COMPUTE_NEDECONVOLUTIONLAYER_H__ */
  