





'''simple docstring'''




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


lowercase__    :      Dict						=    logging.get_logger(__name__)

lowercase__    :      Any						=    {
    '''google/bit-50''': '''https://huggingface.co/google/bit-50/resolve/main/config.json''',
}


class  SCREAMING_SNAKE_CASE    (a__					,		a__							):
     lowerCAmelCase					=       '''bit'''
     lowerCAmelCase					=       ['''preactivation''', '''bottleneck''']
     lowerCAmelCase					=       ['''SAME''', '''VALID''']


     def __init__(						self						,	_UpperCAmelCase=3						,	_UpperCAmelCase=64						,	_UpperCAmelCase=[256, 512, 1024, 2048]						,	_UpperCAmelCase=[3, 4, 6, 3]						,	_UpperCAmelCase="preactivation"						,	_UpperCAmelCase="relu"						,	_UpperCAmelCase=None						,	_UpperCAmelCase=32						,	_UpperCAmelCase=0.0						,	_UpperCAmelCase=False						,	_UpperCAmelCase=32						,	_UpperCAmelCase=1						,	_UpperCAmelCase=None						,	_UpperCAmelCase=None						,	**_UpperCAmelCase						,	):

          '''simple docstring'''






          super().__init__(**_UpperCAmelCase)
          if layer_type not in self.layer_types:
               raise ValueError(F'layer_type={layer_type} is not one of {",".join(self.layer_types)}')
          if global_padding is not None:
               if global_padding.upper() in self.supported_padding:
                    __A						: Dict      =       global_padding.upper()
               else:
                    raise ValueError(F'Padding strategy {global_padding} not supported')
          __A						: Optional[int]      =       num_channels
          __A						: str      =       embedding_size
          __A						: List[Any]      =       hidden_sizes
          __A						: List[Any]      =       depths
          __A						: int      =       layer_type
          __A						: Dict      =       hidden_act
          __A						: Dict      =       global_padding
          __A						: List[Any]      =       num_groups
          __A						: List[Any]      =       drop_path_rate
          __A						: Dict      =       embedding_dynamic_padding
          __A						: int      =       output_stride
          __A						: Union[str, Any]      =       width_factor

          __A						: Dict      =       ['stem'] + [F'stage{idx}' for idx in range(1						,	len(_UpperCAmelCase) + 1)]
          __A ,__A						: str      =       get_aligned_output_features_output_indices(
              out_features=_UpperCAmelCase						,	out_indices=_UpperCAmelCase						,	stage_names=self.stage_names)






'''simple docstring'''




import random






def        _lowerCAmelCase			(  __snake_case  : int ,							__snake_case  : float ,							__snake_case  : bool = False			)     ->     dict:
     __A						: dict      =       {i: [] for i in range(__snake_case			)}

     # if probability is greater or equal than 1, then generate a complete graph
     if probability >= 1:
          return complete_graph(__snake_case			)
     # if probability is lower or equal than 0, then return a graph without edges
     if probability <= 0:
          return graph

     # for each couple of nodes, add an edge from u to v
     # if the number randomly generated is greater than probability probability
     for i in range(__snake_case			):
          for j in range(i + 1 ,							__snake_case			):
               if random.random() < probability:
                    graph[i].append(__snake_case			)
                    if not directed:
                         # if the graph is undirected, add an edge in from j to i, either
                         graph[j].append(__snake_case			)
     return graph






def        _lowerCAmelCase			(  __snake_case  : int			)     ->     dict:
     return {
         i: [j for j in range(__snake_case			) if i != j] for i in range(__snake_case			)
     }


if __name__ == "__main__":
  import doctest

  doctest.testmod()