text: /*
   * Copyright (c) 2016, 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_UTILS_H__
  #define __ARM_COMPUTE_UTILS_H__
  
  #include "arm_compute/core/Error.h"
  #include "arm_compute/core/Rounding.h"
  #include "arm_compute/core/Types.h"
  
  #include <algorithm>
  #include <cstdint>
  #include <cstdlib>
  #include <numeric>
  #include <sstream>
  #include <string>
  #include <type_traits>
  #include <utility>
  #include <vector>
  
  namespace arm_compute
  {
  /** Calculate the rounded up quotient of val / m.
   *
   * @param[in] val Value to divide and round up.
   * @param[in] m   Value to divide by.
   *
   * @return the result.
   */
  template <typename S, typename T>
  constexpr auto DIV_CEIL(S val, T m) -> decltype((val + m - 1) / m)
  {
      return (val + m - 1) / m;
  }
  
  /** Computes the smallest number larger or equal to value that is a multiple of divisor.
   *
   * @param[in] value   Lower bound value
   * @param[in] divisor Value to compute multiple of.
   *
   * @return the result.
   */
  template <typename S, typename T>
  inline auto ceil_to_multiple(S value, T divisor) -> decltype(((value + divisor - 1) / divisor) * divisor)
  {
      ARM_COMPUTE_ERROR_ON(value < 0 || divisor <= 0);
      return DIV_CEIL(value, divisor) * divisor;
  }
  
  /** Computes the largest number smaller or equal to value that is a multiple of divisor.
   *
   * @param[in] value   Upper bound value
   * @param[in] divisor Value to compute multiple of.
   *
   * @return the result.
   */
  template <typename S, typename T>
  inline auto floor_to_multiple(S value, T divisor) -> decltype((value / divisor) * divisor)
  {
      ARM_COMPUTE_ERROR_ON(value < 0 || divisor <= 0);
      return (value / divisor) * divisor;
  }
  
  /** Returns the arm_compute library build information
   *
   * Contains the version number and the build options used to build the library
   *
   * @return The arm_compute library build information
   */
  std::string build_information();
  
  /** Load an entire file in memory
   *
   * @param[in] filename Name of the file to read.
   * @param[in] binary   Is it a binary file ?
   *
   * @return The content of the file.
   */
  std::string read_file(const std::string &filename, bool binary);
  
  /** The size in bytes of the data type
   *
   * @param[in] data_type Input data type
   *
   * @return The size in bytes of the data type
   */
  inline size_t data_size_from_type(DataType data_type)
  {
      switch(data_type)
      {
          case DataType::U8:
          case DataType::S8:
          case DataType::QS8:
          case DataType::QASYMM8:
              return 1;
          case DataType::U16:
          case DataType::S16:
          case DataType::F16:
          case DataType::QS16:
              return 2;
          case DataType::F32:
          case DataType::U32:
          case DataType::S32:
          case DataType::QS32:
              return 4;
          case DataType::F64:
          case DataType::U64:
          case DataType::S64:
              return 8;
          case DataType::SIZET:
              return sizeof(size_t);
          default:
              ARM_COMPUTE_ERROR("Invalid data type");
              return 0;
      }
  }
  
  /** The size in bytes of the pixel format
   *
   * @param[in] format Input format
   *
   * @return The size in bytes of the pixel format
   */
  inline size_t pixel_size_from_format(Format format)
  {
      switch(format)
      {
          case Format::U8:
              return 1;
          case Format::U16:
          case Format::S16:
          case Format::F16:
          case Format::UV88:
          case Format::YUYV422:
          case Format::UYVY422:
              return 2;
          case Format::RGB888:
              return 3;
          case Format::RGBA8888:
              return 4;
          case Format::U32:
          case Format::S32:
          case Format::F32:
              return 4;
          //Doesn't make sense for planar formats:
          case Format::NV12:
          case Format::NV21:
          case Format::IYUV:
          case Format::YUV444:
          default:
              ARM_COMPUTE_ERROR("Undefined pixel size for given format");
              return 0;
      }
  }
  
  /** The size in bytes of the data type
   *
   * @param[in] dt Input data type
   *
   * @return The size in bytes of the data type
   */
  inline size_t element_size_from_data_type(DataType dt)
  {
      switch(dt)
      {
          case DataType::S8:
          case DataType::U8:
          case DataType::QS8:
          case DataType::QASYMM8:
              return 1;
          case DataType::U16:
          case DataType::S16:
          case DataType::QS16:
          case DataType::F16:
              return 2;
          case DataType::U32:
          case DataType::S32:
          case DataType::F32:
          case DataType::QS32:
              return 4;
          default:
              ARM_COMPUTE_ERROR("Undefined element size for given data type");
              return 0;
      }
  }
  
  /** Return the data type used by a given single-planar pixel format
   *
   * @param[in] format Input format
   *
   * @return The size in bytes of the pixel format
   */
  inline DataType data_type_from_format(Format format)
  {
      switch(format)
      {
          case Format::U8:
          case Format::UV88:
          case Format::RGB888:
          case Format::RGBA8888:
          case Format::YUYV422:
          case Format::UYVY422:
              return DataType::U8;
          case Format::U16:
              return DataType::U16;
          case Format::S16:
              return DataType::S16;
          case Format::U32:
              return DataType::U32;
          case Format::S32:
              return DataType::S32;
          case Format::F16:
              return DataType::F16;
          case Format::F32:
              return DataType::F32;
          //Doesn't make sense for planar formats:
          case Format::NV12:
          case Format::NV21:
          case Format::IYUV:
          case Format::YUV444:
          default:
              ARM_COMPUTE_ERROR("Not supported data_type for given format");
              return DataType::UNKNOWN;
      }
  }
  
  /** Return the plane index of a given channel given an input format.
   *
   * @param[in] format  Input format
   * @param[in] channel Input channel
   *
   * @return The plane index of the specific channel of the specific format
   */
  inline int plane_idx_from_channel(Format format, Channel channel)
  {
      switch(format)
      {
          // Single planar formats have a single plane
          case Format::U8:
          case Format::U16:
          case Format::S16:
          case Format::U32:
          case Format::S32:
          case Format::F16:
          case Format::F32:
          case Format::UV88:
          case Format::RGB888:
          case Format::RGBA8888:
          case Format::YUYV422:
          case Format::UYVY422:
              return 0;
          // Multi planar formats
          case Format::NV12:
          case Format::NV21:
          {
              // Channel U and V share the same plane of format UV88
              switch(channel)
              {
                  case Channel::Y:
                      return 0;
                  case Channel::U:
                  case Channel::V:
                      return 1;
                  default:
                      ARM_COMPUTE_ERROR("Not supported channel");
                      return 0;
              }
          }
          case Format::IYUV:
          case Format::YUV444:
          {
              switch(channel)
              {
                  case Channel::Y:
                      return 0;
                  case Channel::U:
                      return 1;
                  case Channel::V:
                      return 2;
                  default:
                      ARM_COMPUTE_ERROR("Not supported channel");
                      return 0;
              }
          }
          default:
              ARM_COMPUTE_ERROR("Not supported format");
              return 0;
      }
  }
  
  /** Return the channel index of a given channel given an input format.
   *
   * @param[in] format  Input format
   * @param[in] channel Input channel
   *
   * @return The channel index of the specific channel of the specific format
   */
  inline int channel_idx_from_format(Format format, Channel channel)
  {
      switch(format)
      {
          case Format::RGB888:
          {
              switch(channel)
              {
                  case Channel::R:
                      return 0;
                  case Channel::G:
                      return 1;
                  case Channel::B:
                      return 2;
                  default:
                      ARM_COMPUTE_ERROR("Not supported channel");
                      return 0;
              }
          }
          case Format::RGBA8888:
          {
              switch(channel)
              {
                  case Channel::R:
                      return 0;
                  case Channel::G:
                      return 1;
                  case Channel::B:
                      return 2;
                  case Channel::A:
                      return 3;
                  default:
                      ARM_COMPUTE_ERROR("Not supported channel");
                      return 0;
              }
          }
          case Format::YUYV422:
          {
              switch(channel)
              {
                  case Channel::Y:
                      return 0;
                  case Channel::U:
                      return 1;
                  case Channel::V:
                      return 3;
                  default:
                      ARM_COMPUTE_ERROR("Not supported channel");
                      return 0;
              }
          }
          case Format::UYVY422:
          {
              switch(channel)
              {
                  case Channel::Y:
                      return 1;
                  case Channel::U:
                      return 0;
                  case Channel::V:
                      return 2;
                  default:
                      ARM_COMPUTE_ERROR("Not supported channel");
                      return 0;
              }
          }
          case Format::NV12:
          {
              switch(channel)
              {
                  case Channel::Y:
                      return 0;
                  case Channel::U:
                      return 0;
                  case Channel::V:
                      return 1;
                  default:
                      ARM_COMPUTE_ERROR("Not supported channel");
                      return 0;
              }
          }
          case Format::NV21:
          {
              switch(channel)
              {
                  case Channel::Y:
                      return 0;
                  case Channel::U:
                      return 1;
                  case Channel::V:
                      return 0;
                  default:
                      ARM_COMPUTE_ERROR("Not supported channel");
                      return 0;
              }
          }
          case Format::YUV444:
          case Format::IYUV:
          {
              switch(channel)
              {
                  case Channel::Y:
                      return 0;
                  case Channel::U:
                      return 0;
                  case Channel::V:
                      return 0;
                  default:
                      ARM_COMPUTE_ERROR("Not supported channel");
                      return 0;
              }
          }
          default:
              ARM_COMPUTE_ERROR("Not supported format");
              return 0;
      }
  }
  
  /** Return the number of planes for a given format
   *
   * @param[in] format Input format
   *
   * @return The number of planes for a given image format.
   */
  inline size_t num_planes_from_format(Format format)
  {
      switch(format)
      {
          case Format::U8:
          case Format::S16:
          case Format::U16:
          case Format::S32:
          case Format::U32:
          case Format::F16:
          case Format::F32:
          case Format::RGB888:
          case Format::RGBA8888:
          case Format::YUYV422:
          case Format::UYVY422:
              return 1;
          case Format::NV12:
          case Format::NV21:
              return 2;
          case Format::IYUV:
          case Format::YUV444:
              return 3;
          default:
              ARM_COMPUTE_ERROR("Not supported format");
              return 0;
      }
  }
  
  /** Return the number of channels for a given single-planar pixel format
   *
   * @param[in] format Input format
   *
   * @return The number of channels for a given image format.
   */
  inline size_t num_channels_from_format(Format format)
  {
      switch(format)
      {
          case Format::U8:
          case Format::U16:
          case Format::S16:
          case Format::U32:
          case Format::S32:
          case Format::F16:
          case Format::F32:
              return 1;
          // Because the U and V channels are subsampled
          // these formats appear like having only 2 channels:
          case Format::YUYV422:
          case Format::UYVY422:
              return 2;
          case Format::UV88:
              return 2;
          case Format::RGB888:
              return 3;
          case Format::RGBA8888:
              return 4;
          //Doesn't make sense for planar formats:
          case Format::NV12:
          case Format::NV21:
          case Format::IYUV:
          case Format::YUV444:
          default:
              return 0;
      }
  }
  
  /** Return the promoted data type of a given data type.
   *
   * @note If promoted data type is not supported an error will be thrown
   *
   * @param[in] dt Data type to get the promoted type of.
   *
   * @return Promoted data type
   */
  inline DataType get_promoted_data_type(DataType dt)
  {
      switch(dt)
      {
          case DataType::U8:
              return DataType::U16;
          case DataType::S8:
              return DataType::S16;
          case DataType::QS8:
              return DataType::QS16;
          case DataType::U16:
              return DataType::U32;
          case DataType::S16:
              return DataType::S32;
          case DataType::QS16:
              return DataType::QS32;
          case DataType::QASYMM8:
          case DataType::F16:
          case DataType::U32:
          case DataType::S32:
          case DataType::F32:
          case DataType::QS32:
              ARM_COMPUTE_ERROR("Unsupported data type promotions!");
          default:
              ARM_COMPUTE_ERROR("Undefined data type!");
      }
      return DataType::UNKNOWN;
  }
  
  /** Return true if the given format has horizontal subsampling.
   *
   * @param[in] format Format to determine subsampling.
   *
   * @return True if the format can be subsampled horizontaly.
   */
  inline bool has_format_horizontal_subsampling(Format format)
  {
      return (format == Format::YUYV422 || format == Format::UYVY422 || format == Format::NV12 || format == Format::NV21 || format == Format::IYUV || format == Format::UV88) ? true : false;
  }
  
  /** Return true if the given format has vertical subsampling.
   *
   * @param[in] format Format to determine subsampling.
   *
   * @return True if the format can be subsampled verticaly.
   */
  inline bool has_format_vertical_subsampling(Format format)
  {
      return (format == Format::NV12 || format == Format::NV21 || format == Format::IYUV || format == Format::UV88) ? true : false;
  }
  
  /** Separate a 2D convolution into two 1D convolutions
   *
   * @param[in]  conv     2D convolution
   * @param[out] conv_col 1D vertical convolution
   * @param[out] conv_row 1D horizontal convolution
   * @param[in]  size     Size of the 2D convolution
   *
   * @return true if the separation was successful
   */
  inline bool separate_matrix(const int16_t *conv, int16_t *conv_col, int16_t *conv_row, uint8_t size)
  {
      int32_t min_col     = -1;
      int16_t min_col_val = -1;
  
      for(int32_t i = 0; i < size; ++i)
      {
          if(conv[i] != 0 && (min_col < 0 || abs(min_col_val) > abs(conv[i])))
          {
              min_col     = i;
              min_col_val = conv[i];
          }
      }
  
      if(min_col < 0)
      {
          return false;
      }
  
      for(uint32_t j = 0; j < size; ++j)
      {
          conv_col[j] = conv[min_col + j * size];
      }
  
      for(uint32_t i = 0; i < size; i++)
      {
          if(static_cast<int>(i) == min_col)
          {
              conv_row[i] = 1;
          }
          else
          {
              int16_t coeff = conv[i] / conv[min_col];
  
              for(uint32_t j = 1; j < size; ++j)
              {
                  if(conv[i + j * size] != (conv_col[j] * coeff))
                  {
                      return false;
                  }
              }
  
              conv_row[i] = coeff;
          }
      }
  
      return true;
  }
  
  /** Calculate the scale of the given square matrix
   *
   * The scale is the absolute value of the sum of all the coefficients in the matrix.
   *
   * @note If the coefficients add up to 0 then the scale is set to 1.
   *
   * @param[in] matrix      Matrix coefficients
   * @param[in] matrix_size Number of elements per side of the square matrix. (Number of coefficients = matrix_size * matrix_size).
   *
   * @return The absolute value of the sum of the coefficients if they don't add up to 0, otherwise 1.
   */
  inline uint32_t calculate_matrix_scale(const int16_t *matrix, unsigned int matrix_size)
  {
      const size_t size = matrix_size * matrix_size;
  
      return std::max(1, std::abs(std::accumulate(matrix, matrix + size, 0)));
  }
  
  /** Calculate the output shapes of the depth concatenate function.
   *
   * @param[in] inputs_vector The vector that stores all the pointers to input.
   *
   * @return the output shape
   */
  template <typename T>
  TensorShape calculate_depth_concatenate_shape(const std::vector<T *> &inputs_vector)
  {
      TensorShape out_shape = inputs_vector[0]->info()->tensor_shape();
  
      size_t max_x = 0;
      size_t max_y = 0;
      size_t depth = 0;
  
      for(const auto &tensor : inputs_vector)
      {
          ARM_COMPUTE_ERROR_ON(tensor == nullptr);
          const TensorShape shape = tensor->info()->tensor_shape();
          max_x                   = std::max(shape.x(), max_x);
          max_y                   = std::max(shape.y(), max_y);
          depth += shape.z();
      }
  
      out_shape.set(0, max_x);
      out_shape.set(1, max_y);
      out_shape.set(2, depth);
  
      return out_shape;
  }
  
  /** Adjust tensor shape size if width or height are odd for a given multi-planar format. No modification is done for other formats.
   *
   * @note Adding here a few links discussing the issue of odd size and sharing the same solution:
   *       Android Source: https://android.googlesource.com/platform/frameworks/base/+/refs/heads/master/graphics/java/android/graphics/YuvImage.java
   *       WebM: https://groups.google.com/a/webmproject.org/forum/#!topic/webm-discuss/LaCKpqiDTXM
   *       libYUV: https://bugs.chromium.org/p/libyuv/issues/detail?id=198&can=1&q=odd%20width
   *       YUVPlayer: https://sourceforge.net/p/raw-yuvplayer/bugs/1/
   *
   * @param[in, out] shape  Tensor shape of 2D size
   * @param[in]      format Format of the tensor
   *
   * @return The adjusted tensor shape.
   */
  inline TensorShape adjust_odd_shape(const TensorShape &shape, Format format)
  {
      TensorShape output{ shape };
  
      // Force width to be even for formats which require subsampling of the U and V channels
      if(has_format_horizontal_subsampling(format))
      {
          output.set(0, output.x() & ~1U);
      }
  
      // Force height to be even for formats which require subsampling of the U and V channels
      if(has_format_vertical_subsampling(format))
      {
          output.set(1, output.y() & ~1U);
      }
  
      return output;
  }
  
  /** Calculate subsampled shape for a given format and channel
   *
   * @param[in] shape   Shape of the tensor to calculate the extracted channel.
   * @param[in] format  Format of the tensor.
   * @param[in] channel Channel to create tensor shape to be extracted.
   *
   * @return The subsampled tensor shape.
   */
  inline TensorShape calculate_subsampled_shape(const TensorShape &shape, Format format, Channel channel = Channel::UNKNOWN)
  {
      TensorShape output{ shape };
  
      // Subsample shape only for U or V channel
      if(Channel::U == channel || Channel::V == channel || Channel::UNKNOWN == channel)
      {
          // Subsample width for the tensor shape when channel is U or V
          if(has_format_horizontal_subsampling(format))
          {
              output.set(0, output.x() / 2U);
          }
  
          // Subsample height for the tensor shape when channel is U or V
          if(has_format_vertical_subsampling(format))
          {
              output.set(1, output.y() / 2U);
          }
      }
  
      return output;
  }
  
  /** Calculate accurary required by the horizontal and vertical convolution computations
   *
   * @param[in] conv_col Pointer to the vertical vector of the separated convolution filter
   * @param[in] conv_row Pointer to the horizontal vector of the convolution filter
   * @param[in] size     Number of elements per vector of the separated matrix
   *
   * @return The return type is a pair. The first element of the pair is the biggest data type needed for the first stage. The second
   * element of the pair is the biggest data type needed for the second stage.
   */
  inline std::pair<DataType, DataType> data_type_for_convolution(const int16_t *conv_col, const int16_t *conv_row, size_t size)
  {
      DataType first_stage  = DataType::UNKNOWN;
      DataType second_stage = DataType::UNKNOWN;
  
      auto gez = [](const int16_t &v)
      {
          return v >= 0;
      };
  
      auto accu_neg = [](const int &first, const int &second)
      {
          return first + (second < 0 ? second : 0);
      };
  
      auto accu_pos = [](const int &first, const int &second)
      {
          return first + (second > 0 ? second : 0);
      };
  
      const bool only_positive_coefficients = std::all_of(conv_row, conv_row + size, gez) && std::all_of(conv_col, conv_col + size, gez);
  
      if(only_positive_coefficients)
      {
          const int max_row_value = std::accumulate(conv_row, conv_row + size, 0) * UINT8_MAX;
          const int max_value     = std::accumulate(conv_col, conv_col + size, 0) * max_row_value;
  
          first_stage = (max_row_value <= UINT16_MAX) ? DataType::U16 : DataType::S32;
  
          second_stage = (max_value <= UINT16_MAX) ? DataType::U16 : DataType::S32;
      }
      else
      {
          const int min_row_value  = std::accumulate(conv_row, conv_row + size, 0, accu_neg) * UINT8_MAX;
          const int max_row_value  = std::accumulate(conv_row, conv_row + size, 0, accu_pos) * UINT8_MAX;
          const int neg_coeffs_sum = std::accumulate(conv_col, conv_col + size, 0, accu_neg);
          const int pos_coeffs_sum = std::accumulate(conv_col, conv_col + size, 0, accu_pos);
          const int min_value      = neg_coeffs_sum * max_row_value + pos_coeffs_sum * min_row_value;
          const int max_value      = neg_coeffs_sum * min_row_value + pos_coeffs_sum * max_row_value;
  
          first_stage = ((INT16_MIN <= min_row_value) && (max_row_value <= INT16_MAX)) ? DataType::S16 : DataType::S32;
  
          second_stage = ((INT16_MIN <= min_value) && (max_value <= INT16_MAX)) ? DataType::S16 : DataType::S32;
      }
  
      return std::make_pair(first_stage, second_stage);
  }
  
  /** Calculate the accuracy required by the squared convolution calculation.
   *
   *
   * @param[in] conv Pointer to the squared convolution matrix
   * @param[in] size The total size of the convolution matrix
   *
   * @return The return is the biggest data type needed to do the convolution
   */
  inline DataType data_type_for_convolution_matrix(const int16_t *conv, size_t size)
  {
      auto gez = [](const int16_t v)
      {
          return v >= 0;
      };
  
      const bool only_positive_coefficients = std::all_of(conv, conv + size, gez);
  
      if(only_positive_coefficients)
      {
          const int max_conv_value = std::accumulate(conv, conv + size, 0) * UINT8_MAX;
          if(max_conv_value <= UINT16_MAX)
          {
              return DataType::U16;
          }
          else
          {
              return DataType::S32;
          }
      }
      else
      {
          const int min_value = std::accumulate(conv, conv + size, 0, [](int a, int b)
          {
              return b < 0 ? a + b : a;
          })
          * UINT8_MAX;
  
          const int max_value = std::accumulate(conv, conv + size, 0, [](int a, int b)
          {
              return b > 0 ? a + b : a;
          })
          * UINT8_MAX;
  
          if((INT16_MIN <= min_value) && (INT16_MAX >= max_value))
          {
              return DataType::S16;
          }
          else
          {
              return DataType::S32;
          }
      }
  }
  
  /** Calculate padding requirements in case of SAME padding
   *
   * @param[in] input_shape   Input shape
   * @param[in] weights_shape Weights shape
   * @param[in] conv_info     Convolution information (containing strides)
   *
   * @return PadStrideInfo for SAME padding
   */
  PadStrideInfo calculate_same_pad(TensorShape input_shape, TensorShape weights_shape, PadStrideInfo conv_info);
  
  /** Returns expected shape for the deconvolution output tensor.
   *
   * @param[in] out_dims widht and height of the output tensor, these values can be obtained with the function deconvolution_output_dimensions.
   * @param[in] input    Shape of the input tensor.
   * @param[in] weights  Shape of the weights tensor.
   *
   * @return Deconvolution output tensor shape.
   */
  TensorShape deconvolution_output_shape(const std::pair<unsigned int, unsigned int> &out_dims, TensorShape input, TensorShape weights);
  
  /** Returns expected width and height of the deconvolution's output tensor.
   *
   * @param[in] in_width           Width of input tensor (Number of columns)
   * @param[in] in_height          Height of input tensor (Number of rows)
   * @param[in] kernel_width       Kernel width.
   * @param[in] kernel_height      Kernel height.
   * @param[in] padx               X axis padding.
   * @param[in] pady               Y axis padding.
   * @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.
   * @param[in] stride_x           X axis input stride.
   * @param[in] stride_y           Y axis input stride.
   *
   * @return A pair with the new width in the first position and the new height in the second.
   */
  const std::pair<unsigned int, unsigned int> deconvolution_output_dimensions(unsigned int in_width, unsigned int in_height,
                                                                              unsigned int kernel_width, unsigned int kernel_height,
                                                                              unsigned int padx, unsigned int pady, unsigned int inner_border_right, unsigned int inner_border_top,
                                                                              unsigned int stride_x, unsigned int stride_y);
  
  /** Returns expected width and height of output scaled tensor depending on dimensions rounding mode.
   *
   * @param[in] width           Width of input tensor (Number of columns)
   * @param[in] height          Height of input tensor (Number of rows)
   * @param[in] kernel_width    Kernel width.
   * @param[in] kernel_height   Kernel height.
   * @param[in] pad_stride_info Pad and stride information.
   * @param[in] dilation        (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
   *
   * @return A pair with the new width in the first position and the new height in the second.
   */
  const std::pair<unsigned int, unsigned int> scaled_dimensions(unsigned int width, unsigned int height,
                                                                unsigned int kernel_width, unsigned int kernel_height,
                                                                const PadStrideInfo &pad_stride_info,
                                                                const Size2D        &dilation = Size2D(1U, 1U));
  
  /** Convert a tensor format into a string.
   *
   * @param[in] format @ref Format to be translated to string.
   *
   * @return The string describing the format.
   */
  const std::string &string_from_format(Format format);
  
  /** Convert a channel identity into a string.
   *
   * @param[in] channel @ref Channel to be translated to string.
   *
   * @return The string describing the channel.
   */
  const std::string &string_from_channel(Channel channel);
  /** Convert a data layout identity into a string.
   *
   * @param[in] dl @ref DataLayout to be translated to string.
   *
   * @return The string describing the data layout.
   */
  const std::string &string_from_data_layout(DataLayout dl);
  /** Convert a data type identity into a string.
   *
   * @param[in] dt @ref DataType to be translated to string.
   *
   * @return The string describing the data type.
   */
  const std::string &string_from_data_type(DataType dt);
  /** Convert a matrix pattern into a string.
   *
   * @param[in] pattern @ref MatrixPattern to be translated to string.
   *
   * @return The string describing the matrix pattern.
   */
  const std::string &string_from_matrix_pattern(MatrixPattern pattern);
  /** Translates a given activation function to a string.
   *
   * @param[in] act @ref ActivationLayerInfo::ActivationFunction to be translated to string.
   *
   * @return The string describing the activation function.
   */
  const std::string &string_from_activation_func(ActivationLayerInfo::ActivationFunction act);
  /** Translates a given non linear function to a string.
   *
   * @param[in] function @ref NonLinearFilterFunction to be translated to string.
   *
   * @return The string describing the non linear function.
   */
  const std::string &string_from_non_linear_filter_function(NonLinearFilterFunction function);
  /** Translates a given interpolation policy to a string.
   *
   * @param[in] policy @ref InterpolationPolicy to be translated to string.
   *
   * @return The string describing the interpolation policy.
   */
  const std::string &string_from_interpolation_policy(InterpolationPolicy policy);
  /** Translates a given border mode policy to a string.
   *
   * @param[in] border_mode @ref BorderMode to be translated to string.
   *
   * @return The string describing the border mode.
   */
  const std::string &string_from_border_mode(BorderMode border_mode);
  /** Translates a given normalization type to a string.
   *
   * @param[in] type @ref NormType to be translated to string.
   *
   * @return The string describing the normalization type.
   */
  const std::string &string_from_norm_type(NormType type);
  /** Translates a given pooling type to a string.
   *
   * @param[in] type @ref PoolingType to be translated to string.
   *
   * @return The string describing the pooling type.
   */
  const std::string &string_from_pooling_type(PoolingType type);
  /** Lower a given string.
   *
   * @param[in] val Given string to lower.
   *
   * @return The lowered string
   */
  std::string lower_string(const std::string &val);
  
  /** Check if a given data type is of floating point type
   *
   * @param[in] dt Input data type.
   *
   * @return True if data type is of floating point type, else false.
   */
  inline bool is_data_type_float(DataType dt)
  {
      switch(dt)
      {
          case DataType::F16:
          case DataType::F32:
              return true;
          default:
              return false;
      }
  }
  
  /** Check if a given data type is of quantized type
   *
   * @note Quantized is considered a super-set of fixed-point and asymmetric data types.
   *
   * @param[in] dt Input data type.
   *
   * @return True if data type is of quantized type, else false.
   */
  inline bool is_data_type_quantized(DataType dt)
  {
      switch(dt)
      {
          case DataType::QS8:
          case DataType::QASYMM8:
          case DataType::QS16:
          case DataType::QS32:
              return true;
          default:
              return false;
      }
  }
  
  /** Check if a given data type is of fixed point type
   *
   * @param[in] dt Input data type.
   *
   * @return True if data type is of fixed point type, else false.
   */
  inline bool is_data_type_fixed_point(DataType dt)
  {
      switch(dt)
      {
          case DataType::QS8:
          case DataType::QS16:
          case DataType::QS32:
              return true;
          default:
              return false;
      }
  }
  
  /** Check if a given data type is of asymmetric quantized type
   *
   * @param[in] dt Input data type.
   *
   * @return True if data type is of symmetric quantized type, else false.
   */
  inline bool is_data_type_quantized_asymmetric(DataType dt)
  {
      switch(dt)
      {
          case DataType::QASYMM8:
              return true;
          default:
              return false;
      }
  }
  
  /** Create a string with the float in full precision.
   *
   * @param val Floating point value
   *
   * @return String with the floating point value.
   */
  inline std::string float_to_string_with_full_precision(float val)
  {
      std::stringstream ss;
      ss.precision(std::numeric_limits<float>::digits10 + 1);
      ss << val;
      return ss.str();
  }
  
  /** Print consecutive elements to an output stream.
   *
   * @param[out] s             Output stream to print the elements to.
   * @param[in]  ptr           Pointer to print the elements from.
   * @param[in]  n             Number of elements to print.
   * @param[in]  stream_width  (Optional) Width of the stream. If set to 0 the element's width is used. Defaults to 0.
   * @param[in]  element_delim (Optional) Delimeter among the consecutive elements. Defaults to space delimeter
   */
  template <typename T>
  void print_consecutive_elements_impl(std::ostream &s, const T *ptr, unsigned int n, int stream_width = 0, const std::string &element_delim = " ")
  {
      using print_type = typename std::conditional<std::is_floating_point<T>::value, T, int>::type;
  
      for(unsigned int i = 0; i < n; ++i)
      {
          // Set stream width as it is not a "sticky" stream manipulator
          if(stream_width != 0)
          {
              s.width(stream_width);
          }
  
          if(std::is_same<typename std::decay<T>::type, half>::value)
          {
              // We use T instead of print_type here is because the std::is_floating_point<half> returns false and then the print_type becomes int.
              s << std::right << static_cast<T>(ptr[i]) << element_delim;
          }
          else
          {
              s << std::right << static_cast<print_type>(ptr[i]) << element_delim;
          }
      }
  }
  
  /** Identify the maximum width of n consecutive elements.
   *
   * @param[in] s   The output stream which will be used to print the elements. Used to extract the stream format.
   * @param[in] ptr Pointer to the elements.
   * @param[in] n   Number of elements.
   *
   * @return The maximum width of the elements.
   */
  template <typename T>
  int max_consecutive_elements_display_width_impl(std::ostream &s, const T *ptr, unsigned int n)
  {
      using print_type = typename std::conditional<std::is_floating_point<T>::value, T, int>::type;
  
      int max_width = -1;
      for(unsigned int i = 0; i < n; ++i)
      {
          std::stringstream ss;
          ss.copyfmt(s);
  
          if(std::is_same<typename std::decay<T>::type, half>::value)
          {
              // We use T instead of print_type here is because the std::is_floating_point<half> returns false and then the print_type becomes int.
              ss << static_cast<T>(ptr[i]);
          }
          else
          {
              ss << static_cast<print_type>(ptr[i]);
          }
  
          max_width = std::max<int>(max_width, ss.str().size());
      }
      return max_width;
  }
  
  /** Print consecutive elements to an output stream.
   *
   * @param[out] s             Output stream to print the elements to.
   * @param[in]  dt            Data type of the elements
   * @param[in]  ptr           Pointer to print the elements from.
   * @param[in]  n             Number of elements to print.
   * @param[in]  stream_width  (Optional) Width of the stream. If set to 0 the element's width is used. Defaults to 0.
   * @param[in]  element_delim (Optional) Delimeter among the consecutive elements. Defaults to space delimeter
   */
  void print_consecutive_elements(std::ostream &s, DataType dt, const uint8_t *ptr, unsigned int n, int stream_width, const std::string &element_delim = " ");
  
  /** Identify the maximum width of n consecutive elements.
   *
   * @param[in] s   Output stream to print the elements to.
   * @param[in] dt  Data type of the elements
   * @param[in] ptr Pointer to print the elements from.
   * @param[in] n   Number of elements to print.
   *
   * @return The maximum width of the elements.
   */
  int max_consecutive_elements_display_width(std::ostream &s, DataType dt, const uint8_t *ptr, unsigned int n);
  }
  #endif /*__ARM_COMPUTE_UTILS_H__ */
  