



'''simple docstring'''





from __future__ import annotations

__a          =		list[list[int]]

# assigning initial values to the grid
__a          =		[
    [3, 0, 6, 5, 0, 8, 4, 0, 0],
    [5, 2, 0, 0, 0, 0, 0, 0, 0],
    [0, 8, 7, 0, 0, 0, 0, 3, 1],
    [0, 0, 3, 0, 1, 0, 0, 8, 0],
    [9, 0, 0, 8, 6, 3, 0, 0, 5],
    [0, 5, 0, 0, 9, 0, 6, 0, 0],
    [1, 3, 0, 0, 0, 0, 2, 5, 0],
    [0, 0, 0, 0, 0, 0, 0, 7, 4],
    [0, 0, 5, 2, 0, 6, 3, 0, 0],
]

# a grid with no solution
__a          =		[
    [5, 0, 6, 5, 0, 8, 4, 0, 3],
    [5, 2, 0, 0, 0, 0, 0, 0, 2],
    [1, 8, 7, 0, 0, 0, 0, 3, 1],
    [0, 0, 3, 0, 1, 0, 0, 8, 0],
    [9, 0, 0, 8, 6, 3, 0, 0, 5],
    [0, 5, 0, 0, 9, 0, 6, 0, 0],
    [1, 3, 0, 0, 0, 0, 2, 5, 0],
    [0, 0, 0, 0, 0, 0, 0, 7, 4],
    [0, 0, 5, 2, 0, 6, 3, 0, 0],
]





def 						__snake_case(				_lowerCAmelCase     ,   _lowerCAmelCase     ,   _lowerCAmelCase     ,   _lowerCAmelCase		)		-> bool:
      for i in range(9		):
            if grid[row][i] == n or grid[i][column] == n:
                  return False

      for i in range(3		):
            for j in range(3		):
                  if grid[(row - row % 3) + i][(column - column % 3) + j] == n:
                        return False

      return True





def 						__snake_case(				_lowerCAmelCase		)		-> tuple[int, int] | None:
      for i in range(9		):
            for j in range(9		):
                  if grid[i][j] == 0:
                        return i, j
      return None





def 						__snake_case(				_lowerCAmelCase		)		-> Matrix | None:
      if location := find_empty_location(_lowerCAmelCase		):
            snake_case__						,				snake_case__  :    str    						=      location
      else:
            # If the location is ``None``, then the grid is solved.
            return grid

      for digit in range(1     ,   10		):
            if is_safe(_lowerCAmelCase     ,   _lowerCAmelCase     ,   _lowerCAmelCase     ,   _lowerCAmelCase		):
                  snake_case__  :    Optional[Any]    						=      digit

                  if sudoku(_lowerCAmelCase		) is not None:
                        return grid

                  snake_case__  :    Any    						=      0

      return None





def 						__snake_case(				_lowerCAmelCase		)		-> None:
      for row in grid:
            for cell in row:
                  print(_lowerCAmelCase     ,   end=""" """		)
            print()


if __name__ == "__main__":
       # make a copy of grid so that you can compare with the unmodified grid
       for example_grid in (initial_grid, no_solution):
              print("\nExample grid:\n" + "=" * 20)
              print_solution(example_grid)
              print("\nExample grid solution:")
              __a          =		sudoku(example_grid)
              if solution is not None:
                     print_solution(solution)
              else:
                     print("Cannot find a solution.")





'''simple docstring'''





from ...configuration_utils import PretrainedConfig
from ...utils import logging


__a          =		logging.get_logger(__name__)

__a          =		{
    "vinvino02/glpn-kitti": "https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json",
    # See all GLPN models at https://huggingface.co/models?filter=glpn
}







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







    lowercase					=		"glpn"




    def __init__(    self					:     Optional[Any] ,     snake_case_					:     List[str]=3 ,     snake_case_					:     Dict=4 ,     snake_case_					:     List[Any]=[2, 2, 2, 2] ,     snake_case_					:     int=[8, 4, 2, 1] ,     snake_case_					:     List[str]=[32, 64, 160, 256] ,     snake_case_					:     Tuple=[7, 3, 3, 3] ,     snake_case_					:     List[Any]=[4, 2, 2, 2] ,     snake_case_					:     Tuple=[1, 2, 5, 8] ,     snake_case_					:     List[str]=[4, 4, 4, 4] ,     snake_case_					:     Optional[int]="gelu" ,     snake_case_					:     Dict=0.0 ,     snake_case_					:     Union[str, Any]=0.0 ,     snake_case_					:     List[Any]=0.02 ,     snake_case_					:     Tuple=0.1 ,     snake_case_					:     Any=1E-6 ,     snake_case_					:     Dict=64 ,     snake_case_					:     Tuple=10 ,     snake_case_					:     List[Any]=-1 ,     **snake_case_					:     Optional[Any] ,     ):
          super().__init__(**snake_case_						)

          snake_case__  :    Optional[Any]    						=      num_channels
          snake_case__  :    Dict    						=      num_encoder_blocks
          snake_case__  :    Tuple    						=      depths
          snake_case__  :    Union[str, Any]    						=      sr_ratios
          snake_case__  :    Tuple    						=      hidden_sizes
          snake_case__  :    Optional[Any]    						=      patch_sizes
          snake_case__  :    int    						=      strides
          snake_case__  :    List[Any]    						=      mlp_ratios
          snake_case__  :    Optional[int]    						=      num_attention_heads
          snake_case__  :    Dict    						=      hidden_act
          snake_case__  :    int    						=      hidden_dropout_prob
          snake_case__  :    Optional[Any]    						=      attention_probs_dropout_prob
          snake_case__  :    str    						=      initializer_range
          snake_case__  :    List[str]    						=      drop_path_rate
          snake_case__  :    int    						=      layer_norm_eps
          snake_case__  :    Tuple    						=      decoder_hidden_size
          snake_case__  :    List[Any]    						=      max_depth
          snake_case__  :    Dict    						=      head_in_index
