text: /*
   * Copyright (c) 2016, 2017 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_TENSORINFO_H__
  #define __ARM_COMPUTE_TENSORINFO_H__
  
  #include "arm_compute/core/ITensorInfo.h"
  
  #include "arm_compute/core/Coordinates.h"
  #include "arm_compute/core/Strides.h"
  #include "arm_compute/core/TensorShape.h"
  #include "arm_compute/core/Types.h"
  #include "arm_compute/core/Utils.h"
  
  #include <cstddef>
  
  namespace arm_compute
  {
  class HOGInfo;
  
  /** Store the tensor's metadata */
  class TensorInfo final : public ITensorInfo
  {
  public:
      /** Default constructor */
      TensorInfo();
      /** Default destructor */
      ~TensorInfo() = default;
      /** Allow instances of this class to be copy constructed */
      TensorInfo(const ITensorInfo &info);
      /** Allow instances of this class to be copy constructed */
      TensorInfo(const TensorInfo &) = default;
      /** Allow instances of this class to be copied */
      TensorInfo &operator=(const TensorInfo &) = default;
      /** Allow instances of this class to be move constructed */
      TensorInfo(TensorInfo &&) = default;
      /** Allow instances of this class to be moved */
      TensorInfo &operator=(TensorInfo &&) = default;
  
      /** Construct a tensor info with a format.
       *
       * Can be used for automatic derivation of the shape by the function.
       *
       * @param[in] format Format of the tensor.
       */
      TensorInfo(Format format);
  
      /** 2D tensor constructor
       *
       * @param[in] width  Width of the 2D tensor
       * @param[in] height Height of the 2D tensor
       * @param[in] format Single plane format of the tensor.
       */
      TensorInfo(unsigned int width, unsigned int height, Format format);
      /** Constructor
       *
       * @param[in] tensor_shape It specifies the size for each dimension of the tensor in number of elements.
       * @param[in] format       Single plane format of the tensor.
       */
      TensorInfo(const TensorShape &tensor_shape, Format format);
  
      /** Construct a tensor info with a data type and number of channels.
       *
       * Can be used for automatic derivation of the shape by the function.
       *
       * @param[in] num_channels         It indicates the number of channels for each tensor element
       * @param[in] data_type            Data type to use for each tensor element
       * @param[in] fixed_point_position (Optional) It specifies the fixed point position when the tensor data type is QS8, QS16 or QS32.
       */
      TensorInfo(size_t num_channels, DataType data_type, size_t fixed_point_position = 0);
  
      /** Constructor
       *
       * @param[in] tensor_shape         It specifies the size for each dimension of the tensor in number of elements.
       * @param[in] num_channels         It indicates the number of channels for each tensor element
       * @param[in] data_type            Data type to use for each tensor element
       * @param[in] fixed_point_position (Optional) Fixed point position that expresses the number of bits for the fractional part of the number when the tensor's data type is QS8 or QS16.
       */
      TensorInfo(const TensorShape &tensor_shape, size_t num_channels, DataType data_type, int fixed_point_position = 0);
      /** Constructor
       *
       * @param[in] hog_info HOG's metadata used to allocate normalized HOG space
       * @param[in] width    Width of the 2D tensor where the HOG descriptor will be computed on
       * @param[in] height   Height of the 2D tensor where the HOG descriptor will be computed on
       */
      TensorInfo(const HOGInfo &hog_info, unsigned int width, unsigned int height);
  
      /** Initialize the tensor info with just a format.
       *
       * Can be used for automatic derivation of the shape by the function.
       *
       * @param[in] format Single plane format of the tensor.
       */
      void init(Format format);
  
      /** Initialize the metadata structure with the given parameters
       *
       * @param[in] tensor_shape Size for each dimension of the tensor in number of elements.
       * @param[in] format       Single plane format of the tensor.
       */
      void init(const TensorShape &tensor_shape, Format format);
      /** Initialize the metadata structure with the given parameters
       *
       * @param[in] tensor_shape                  Size for each dimension of the tensor in number of elements.
       * @param[in] format                        Single plane format of the tensor.
       * @param[in] strides_in_bytes              Stride in bytes for accessing each dimension of the tensor.
       * @param[in] offset_first_element_in_bytes Offset in bytes from the beginning of memory allocation to access the first element.
       * @param[in] total_size_in_bytes           Size in bytes of the memory allocation (including the offset to the first element).
       */
      void init(const TensorShape &tensor_shape, Format format, const Strides &strides_in_bytes, size_t offset_first_element_in_bytes, size_t total_size_in_bytes);
  
      /** Initialize the tensor info with just a format.
       *
       * Can be used for automatic derivation of the shape by the function.
       *
       * @param[in] num_channels         Desired number of channels for each tensor element.
       * @param[in] data_type            Data type to use for each tensor element.
       * @param[in] fixed_point_position (Optional) Fixed point position when the tensor data type is QS8, QS16 or QS32.
       */
      void init(size_t num_channels, DataType data_type, size_t fixed_point_position = 0);
  
      /** Initialize the metadata structure with the given parameters
       *
       * @param[in] tensor_shape         Size for each dimension of the tensor in number of elements.
       * @param[in] num_channels         Desired number of channels for each tensor element.
       * @param[in] data_type            Data type to use for each tensor element.
       * @param[in] fixed_point_position (Optional) Fixed point position that expresses the number of bits for the fractional part of the number when the tensor's data type is QS8 or QS16.
       */
      void init(const TensorShape &tensor_shape, size_t num_channels, DataType data_type, int fixed_point_position = 0);
      /** Initialize the metadata structure with the given parameters
       *
       * @param[in] tensor_shape                  Size for each dimension of the tensor in number of elements.
       * @param[in] num_channels                  Desired number of channels for each tensor element.
       * @param[in] data_type                     Data type to use for each tensor element.
       * @param[in] strides_in_bytes              Stride in bytes for accessing each dimension of the tensor.
       * @param[in] offset_first_element_in_bytes Offset in bytes from the beginning of memory allocation to access the first element.
       * @param[in] total_size_in_bytes           Size in bytes of the memory allocation (including the offset to the first element).
       * @param[in] fixed_point_position          (Optional) Fixed point position that expresses the number of bits for the fractional part of the number when the tensor's data type is QS8 or QS16.
       */
      void init(const TensorShape &tensor_shape, size_t num_channels, DataType data_type, const Strides &strides_in_bytes, size_t offset_first_element_in_bytes,
                size_t total_size_in_bytes, int fixed_point_position = 0);
      /** Initialize the metadata structure for the given HOG's metadata
       *
       * @param[in] hog_info HOG's metadata used to allocate normalized HOG space
       * @param[in] width    Width of the 2D tensor where the HOG descriptor will be computed on
       * @param[in] height   Height of the 2D tensor where the HOG descriptor will be computed on
       */
      void init(const HOGInfo &hog_info, unsigned int width, unsigned int height);
      /** Initialize the metadata structure for the given tensor shape and single-plane format, (Padding is automatically calculated)
       *
       * @note The padding used by this method is really conservative so that the tensor can be used for most functions.
       *
       * @param[in] tensor_shape It specifies the size for each dimension of the tensor in number of elements
       * @param[in] format       Single plane format of the image.
       *
       * @return Total allocation size including padding in bytes.
       */
      size_t init_auto_padding(const TensorShape &tensor_shape, Format format);
      /** Initialize the metadata structure for the given tensor shape, number of channels,
       *  data type and fixed point position. (Padding is automatically calculated)
       *
       * @note The padding used by this method is really conservative so that the tensor can be used for most functions.
       *
       * @param[in] tensor_shape         It specifies the size for each dimension of the tensor in number of elements
       * @param[in] num_channels         It indicates the number of channels for each tensor element
       * @param[in] data_type            Data type to use for each tensor element
       * @param[in] fixed_point_position (Optional) Fixed point position that expresses the number of bits for the fractional part of the number when the tensor's data type is QS8 or QS16.
       *
       * @return Total allocation size including padding in bytes.
       */
      size_t init_auto_padding(const TensorShape &tensor_shape, size_t num_channels, DataType data_type, int fixed_point_position = 0);
      /** Initialize the metadata structure for the given HOG's metadata
       *
       * @note init_auto_padding will be used for the tensor initialization.
       *
       * @param[in] hog_info HOG's metadata used to allocate normalized HOG space
       * @param[in] width    Width of the 2D tensor where the HOG descriptor will be computed on
       * @param[in] height   Height of the 2D tensor where the HOG descriptor will be computed on
       */
      size_t init_auto_padding(const HOGInfo &hog_info, unsigned int width, unsigned int height);
  
      // Inherited methods overridden:
      void set_data_type(DataType data_type) override;
      void set_num_channels(int num_channels) override;
      void set_format(Format format) override;
      void set_tensor_shape(TensorShape shape) override;
      void set_fixed_point_position(int fixed_point_position) override;
      bool auto_padding() override;
      bool extend_padding(const PaddingSize &padding) override;
      size_t dimension(size_t index) const override
      {
          return _tensor_shape[index];
      }
      const Strides &strides_in_bytes() const override
      {
          return _strides_in_bytes;
      }
      size_t offset_first_element_in_bytes() const override
      {
          return _offset_first_element_in_bytes;
      }
      size_t offset_element_in_bytes(const Coordinates &pos) const override;
      int fixed_point_position() const override
      {
          return _fixed_point_position;
      }
      size_t element_size() const override
      {
          return data_size_from_type(_data_type) * _num_channels;
      }
      size_t num_dimensions() const override
      {
          return _tensor_shape.num_dimensions();
      }
      size_t num_channels() const override
      {
          return _num_channels;
      }
      const TensorShape &tensor_shape() const override
      {
          return _tensor_shape;
      }
      DataType data_type() const override
      {
          return _data_type;
      }
      Format format() const override
      {
          return _format;
      }
      size_t total_size() const override
      {
          return _total_size;
      }
      PaddingSize padding() const override
      {
          return _padding;
      }
      bool has_padding() const override
      {
          return !_padding.empty();
      }
      bool is_resizable() const override
      {
          return _is_resizable;
      }
      void set_is_resizable(bool is_resizable) override
      {
          _is_resizable = is_resizable;
      }
      ValidRegion valid_region() const override
      {
          return _valid_region;
      }
      void set_valid_region(ValidRegion valid_region) override
      {
          _valid_region = std::move(valid_region);
      }
  
  private:
      /** Calculates strides, offset and total size resulting from the specified padding around the XY plane.
       *
       * @param[in] padding Padding around the XY plane in elements.
       */
      std::tuple<Strides, size_t, size_t> calculate_padding_requirements(const PaddingSize &padding);
  
      size_t      _total_size;
      int         _fixed_point_position;
      size_t      _offset_first_element_in_bytes;
      Strides     _strides_in_bytes;
      size_t      _num_channels;
      TensorShape _tensor_shape;
      DataType    _data_type;
      Format      _format;
      bool        _is_resizable;
      ValidRegion _valid_region;
      PaddingSize _padding;
  };
  }
  #endif /*__ARM_COMPUTE_TENSORINFO_H__ */
  