





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


__lowercase	: Tuple       =logging.get_logger(__name__)

__lowercase	: str       ={
    """microsoft/swinv2-tiny-patch4-window8-256""": (
        """https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json"""
    ),
}

class   A							(						__lowercase    ):
      _snake_case				  ='''swinv2'''

      _snake_case				  ={
          '''num_attention_heads''': '''num_heads''',
          '''num_hidden_layers''': '''num_layers''',
      }



      def __init__(						self:    Any		,	_lowerCAmelCase:    List[str]=224		,	_lowerCAmelCase:    Union[str, Any]=4		,	_lowerCAmelCase:    Tuple=3		,	_lowerCAmelCase:    Optional[int]=96		,	_lowerCAmelCase:    str=[2, 2, 6, 2]		,	_lowerCAmelCase:    List[str]=[3, 6, 12, 24]		,	_lowerCAmelCase:    Optional[int]=7		,	_lowerCAmelCase:    Dict=4.0		,	_lowerCAmelCase:    str=True		,	_lowerCAmelCase:    int=0.0		,	_lowerCAmelCase:    Dict=0.0		,	_lowerCAmelCase:    Optional[Any]=0.1		,	_lowerCAmelCase:    int="gelu"		,	_lowerCAmelCase:    int=False		,	_lowerCAmelCase:    Optional[Any]=0.02		,	_lowerCAmelCase:    Union[str, Any]=1e-5		,	_lowerCAmelCase:    str=32		,	**_lowerCAmelCase:    int		,	)    ->     int:
         '''simple docstring'''

         super().__init__(**_lowerCAmelCase							)

         UpperCAmelCase_           =image_size
         UpperCAmelCase_           =patch_size
         UpperCAmelCase_           =num_channels
         UpperCAmelCase_           =embed_dim
         UpperCAmelCase_           =depths
         UpperCAmelCase_           =len(_lowerCAmelCase							)
         UpperCAmelCase_           =num_heads
         UpperCAmelCase_           =window_size
         UpperCAmelCase_           =mlp_ratio
         UpperCAmelCase_           =qkv_bias
         UpperCAmelCase_           =hidden_dropout_prob
         UpperCAmelCase_           =attention_probs_dropout_prob
         UpperCAmelCase_           =drop_path_rate
         UpperCAmelCase_           =hidden_act
         UpperCAmelCase_           =use_absolute_embeddings
         UpperCAmelCase_           =layer_norm_eps
         UpperCAmelCase_           =initializer_range
         UpperCAmelCase_           =encoder_stride
         # we set the hidden_size attribute in order to make Swinv2 work with VisionEncoderDecoderModel
         # this indicates the channel dimension after the last stage of the model
         UpperCAmelCase_           =int(embed_dim * 2 ** (len(_lowerCAmelCase							) - 1)							)
         UpperCAmelCase_           =(0, 0, 0, 0)










"""simple docstring"""






from __future__ import annotations







def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     int       =       len(lowercase__						)
				# We need to create solution object to save path.
				_lowerCamelCase	:     Tuple       =       [[0 for _ in range(lowercase__						)] for _ in range(lowercase__						)]
				_lowerCamelCase	:     Optional[Any]       =       run_maze(lowercase__				,       0				,       0				,       lowercase__						)
				if solved:
								print('\n'.join(str(lowercase__						) for row in solutions						)						)
				else:
								print('No solution exists!'						)
				return solved







def 	_snake_case     (							lowercase__				,       lowercase__				,       lowercase__				,       lowercase__						):
				_lowerCamelCase	:     Optional[int]       =       len(lowercase__						)
				# Final check point.
				if i == j == (size - 1):
								_lowerCamelCase	:     Optional[Any]       =       1
								return True

				_lowerCamelCase	:     List[str]       =       (not i < 0) and (not j < 0)  # Check lower bounds
				_lowerCamelCase	:     List[str]       =       (i < size) and (j < size)  # Check upper bounds

				if lower_flag and upper_flag:
								# check for already visited and block points.
								_lowerCamelCase	:     List[Any]       =       (not solutions[i][j]) and (not maze[i][j])
								if block_flag:
												# check visited
												_lowerCamelCase	:     Union[str, Any]       =       1

												# check for directions
												if (
												    run_maze(lowercase__				,       i + 1				,       lowercase__				,       lowercase__						)
												    or run_maze(lowercase__				,       lowercase__				,       j + 1				,       lowercase__						)
												    or run_maze(lowercase__				,       i - 1				,       lowercase__				,       lowercase__						)
												    or run_maze(lowercase__				,       lowercase__				,       j - 1				,       lowercase__						)
												):
																return True

												_lowerCamelCase	:     Dict       =       0
												return False
				return False


if __name__ == "__main__":
			import doctest

			doctest.testmod()