"""simple docstring"""


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


UpperCAmelCase__     						=  logging.get_logger(__name__)


class 				a (						lowerCAmelCase_		,							lowerCAmelCase_      ):
    _snake_case   :     Union[str, Any]   							=							'maskformer-swin'

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


    def __init__(    self		:     Dict      , __lowerCAmelCase		:     Tuple=224      , __lowerCAmelCase		:     Any=4      , __lowerCAmelCase		:     List[str]=3      , __lowerCAmelCase		:     str=96      , __lowerCAmelCase		:     List[str]=[2, 2, 6, 2]      , __lowerCAmelCase		:     Tuple=[3, 6, 12, 24]      , __lowerCAmelCase		:     Any=7      , __lowerCAmelCase		:     Optional[Any]=4.0      , __lowerCAmelCase		:     Tuple=True      , __lowerCAmelCase		:     Optional[int]=0.0      , __lowerCAmelCase		:     Any=0.0      , __lowerCAmelCase		:     Union[str, Any]=0.1      , __lowerCAmelCase		:     Optional[Any]="gelu"      , __lowerCAmelCase		:     Optional[int]=False      , __lowerCAmelCase		:     Dict=0.02      , __lowerCAmelCase		:     Tuple=1e-5      , __lowerCAmelCase		:     Tuple=None      , __lowerCAmelCase		:     Union[str, Any]=None      , **__lowerCAmelCase		:     Optional[int]      , ):
      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
      # we set the hidden_size attribute in order to make Swin work with VisionEncoderDecoderModel
      # this indicates the channel dimension after the last stage of the model
      _UpperCAmelCase         =					int(embed_dim * 2 ** (len(__lowerCAmelCase    ) - 1)    )
      _UpperCAmelCase         =					["""stem"""] + [f'''stage{idx}''' for idx in range(1      , len(__lowerCAmelCase    ) + 1    )]
      _UpperCAmelCase       , _UpperCAmelCase         =					get_aligned_output_features_output_indices(
          out_features=__lowerCAmelCase      , out_indices=__lowerCAmelCase      , stage_names=self.stage_names    )

"""simple docstring"""


from __future__ import annotations

from collections import Counter
from random import random


class 				a :


    def __init__(    self		:     Union[str, Any]    ):
      _UpperCAmelCase         =					{}


    def    lowerCAmelCase_     (    self		:     Optional[int]      , __lowerCAmelCase		:     str    ):
      _UpperCAmelCase         =					{}


    def    lowerCAmelCase_     (    self		:     str      , __lowerCAmelCase		:     str      , __lowerCAmelCase		:     str      , __lowerCAmelCase		:     float    ):
      if nodea not in self.connections:
        self.add_node(__lowerCAmelCase    )
      if nodea not in self.connections:
        self.add_node(__lowerCAmelCase    )
      _UpperCAmelCase         =					probability


    def    lowerCAmelCase_     (    self		:     Optional[Any]    ):
      return list(self.connections    )


    def    lowerCAmelCase_     (    self		:     List[Any]      , __lowerCAmelCase		:     str    ):
      _UpperCAmelCase         =					0
      _UpperCAmelCase         =					random()

      for dest in self.connections[node]:
        current_probability += self.connections[node][dest]
        if current_probability > random_value:
          return dest
      return ""






def 			__UpperCAmelCase    (	lowercase      ,lowercase      ,lowercase						):







  """simple docstring"""
  _UpperCAmelCase         =					MarkovChainGraphUndirectedUnweighted()

  for nodea, nodea, probability in transitions:
    graph.add_transition_probability(lowercase      ,lowercase      ,lowercase						)

  _UpperCAmelCase         =					Counter(graph.get_nodes()						)
  _UpperCAmelCase         =					start

  for _ in range(lowercase						):
    _UpperCAmelCase         =					graph.transition(lowercase						)
    visited[node] += 1

  return visited


if __name__ == "__main__":
    import doctest

    doctest.testmod()
