


'''simple docstring'''



from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


A__						:   Union[str, Any]				=    logging.get_logger(__name__)

A__						:   int				=    {
    """shi-labs/dinat-mini-in1k-224""": """https://huggingface.co/shi-labs/dinat-mini-in1k-224/resolve/main/config.json""",
    # See all Dinat models at https://huggingface.co/models?filter=dinat
}





class   UpperCAmelCase_    (__a   ,						__a    ):





    """simple docstring"""






    lowerCamelCase    :   Dict					=     '''dinat'''

    lowerCamelCase    :   int					=     {
        '''num_attention_heads''': '''num_heads''',
        '''num_hidden_layers''': '''num_layers''',
    }







    def __init__(				self     ,	SCREAMING_SNAKE_CASE_=4     ,	SCREAMING_SNAKE_CASE_=3     ,	SCREAMING_SNAKE_CASE_=64     ,	SCREAMING_SNAKE_CASE_=[3, 4, 6, 5]     ,	SCREAMING_SNAKE_CASE_=[2, 4, 8, 16]     ,	SCREAMING_SNAKE_CASE_=7     ,	SCREAMING_SNAKE_CASE_=[[1, 8, 1], [1, 4, 1, 4], [1, 2, 1, 2, 1, 2], [1, 1, 1, 1, 1]]     ,	SCREAMING_SNAKE_CASE_=3.0     ,	SCREAMING_SNAKE_CASE_=True     ,	SCREAMING_SNAKE_CASE_=0.0     ,	SCREAMING_SNAKE_CASE_=0.0     ,	SCREAMING_SNAKE_CASE_=0.1     ,	SCREAMING_SNAKE_CASE_="gelu"     ,	SCREAMING_SNAKE_CASE_=0.0_2     ,	SCREAMING_SNAKE_CASE_=1E-5     ,	SCREAMING_SNAKE_CASE_=0.0     ,	SCREAMING_SNAKE_CASE_=None     ,	SCREAMING_SNAKE_CASE_=None     ,	**SCREAMING_SNAKE_CASE_     ,	)							->	Optional[Any]:
         super().__init__(**_lowercase      )

         __lowerCamelCase  :      List[str]														=						patch_size
         __lowerCamelCase  :      Union[str, Any]														=						num_channels
         __lowerCamelCase  :      Tuple														=						embed_dim
         __lowerCamelCase  :      int														=						depths
         __lowerCamelCase  :      Dict														=						len(_lowercase      )
         __lowerCamelCase  :      str														=						num_heads
         __lowerCamelCase  :      Dict														=						kernel_size
         __lowerCamelCase  :      Dict														=						dilations
         __lowerCamelCase  :      List[str]														=						mlp_ratio
         __lowerCamelCase  :      Tuple														=						qkv_bias
         __lowerCamelCase  :      Optional[Any]														=						hidden_dropout_prob
         __lowerCamelCase  :      List[str]														=						attention_probs_dropout_prob
         __lowerCamelCase  :      Optional[Any]														=						drop_path_rate
         __lowerCamelCase  :      Union[str, Any]														=						hidden_act
         __lowerCamelCase  :      Any														=						layer_norm_eps
         __lowerCamelCase  :      Any														=						initializer_range
         # we set the hidden_size attribute in order to make Dinat work with VisionEncoderDecoderModel
         # this indicates the channel dimension after the last stage of the model
         __lowerCamelCase  :      Optional[Any]														=						int(embed_dim * 2 ** (len(_lowercase      ) - 1)      )
         __lowerCamelCase  :      str														=						layer_scale_init_value
         __lowerCamelCase  :      Union[str, Any]														=						['''stem'''] + [f'stage{idx}' for idx in range(1     ,	len(_lowercase      ) + 1      )]
         __lowerCamelCase  :      Optional[int]														=						get_aligned_output_features_output_indices(
             out_features=_lowercase     ,	out_indices=_lowercase     ,	stage_names=self.stage_names      )







def    lowerCAmelCase_  (		lowercase:				Dict		)     ->					Any:







 '''simple docstring'''
 _UpperCamelCase:  int    						=			[]
 _UpperCamelCase:  Dict    						=			set({'''(''', '''[''', '''{'''}		)
 _UpperCamelCase:  int    						=			set({''')''', ''']''', '''}'''}		)
 _UpperCamelCase:  Dict    						=			{'''{''': '''}''', '''[''': ''']''', '''(''': ''')'''}

 for i in range(len(lowercase		)		):
  if s[i] in open_brackets:
   stack.append(s[i]		)

  elif s[i] in closed_brackets and (
      len(lowercase		) == 0 or (len(lowercase		) > 0 and open_to_closed[stack.pop()] != s[i])
  ):
   return False

 return len(lowercase		) == 0




def    lowerCAmelCase_  (		)     ->					int:







 '''simple docstring'''
 _UpperCamelCase:  List[str]    						=			input('''Enter sequence of brackets: '''		)
 if is_balanced(lowercase		):
  print(lowercase	,       '''is balanced'''		)
 else:
  print(lowercase	,       '''is not balanced'''		)


if __name__ == "__main__":
  main()