






import importlib
import inspect
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
A_		:		Any		     =			'src/transformers'


# This is to make sure the transformers module imported is the one in the repo.
A_		:		Tuple		     =			importlib.util.spec_from_file_location(
    'transformers',
    os.path.join(PATH_TO_TRANSFORMERS, '__init__.py'),
    submodule_search_locations=[PATH_TO_TRANSFORMERS],
)
A_		:		List[str]		     =			spec.loader.load_module()

A_		:		Union[str, Any]		     =			transformers.models.auto.configuration_auto.CONFIG_MAPPING

# Regex pattern used to find the checkpoint mentioned in the docstring of `config_class`.
# For example, `[bert-base-uncased](https://huggingface.co/bert-base-uncased)`
A_		:		Dict		     =			re.compile('\[(.+?)\]\((https://huggingface\.co/.+?)\)')


A_		:		Dict		     =			{
    'CLIPConfigMixin',
    'DecisionTransformerConfigMixin',
    'EncoderDecoderConfigMixin',
    'RagConfigMixin',
    'SpeechEncoderDecoderConfigMixin',
    'VisionEncoderDecoderConfigMixin',
    'VisionTextDualEncoderConfigMixin',
}

def   snake_case ()	->    Union[str, Any]:
  UpperCamelCase_: Dict   				=    []

  for config_class in list(CONFIG_MAPPING.values()  ):
    UpperCamelCase_: Tuple   				=    False

    # source code of `config_class`
    UpperCamelCase_: List[str]   				=    inspect.getsource(UpperCAmelCase__  )
    UpperCamelCase_: str   				=    _re_checkpoint.findall(UpperCAmelCase__  )

    for checkpoint in checkpoints:
      # Each `checkpoint` is a tuple of a checkpoint name and a checkpoint link.
      # For example, `('bert-base-uncased', 'https://huggingface.co/bert-base-uncased')`
      UpperCamelCase_: Any   				=    checkpoint

      # verify the checkpoint name corresponds to the checkpoint link
      UpperCamelCase_: str   				=    F'''https://huggingface.co/{ckpt_name}'''
      if ckpt_link == ckpt_link_from_name:
        UpperCamelCase_: Union[str, Any]   				=    True
        break

    UpperCamelCase_: List[Any]   				=    config_class.__name__
    if not checkpoint_found and name not in CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK:
      configs_without_checkpoint.append(UpperCAmelCase__  )

  if len(UpperCAmelCase__  ) > 0:
    UpperCamelCase_: List[Any]   				=    '\n'.join(sorted(UpperCAmelCase__  )  )
    raise ValueError(F'''The following configurations don\'t contain any valid checkpoint:\n{message}'''  )


if __name__ == "__main__":
   check_config_docstrings_have_checkpoints()







# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also say that there is no edge that connects
# vertices of same set.

def   snake_case (UpperCAmelCase__  )	->    List[str]:
  UpperCamelCase_: int   				=    [False] * len(UpperCAmelCase__  )
  UpperCamelCase_: Any   				=    [-1] * len(UpperCAmelCase__  )

  def dfs(UpperCAmelCase__     ,   UpperCAmelCase__  ):
    UpperCamelCase_: Tuple   				=    True
    UpperCamelCase_: Optional[int]   				=    c
    for u in graph[v]:
      if not visited[u]:
        dfs(UpperCAmelCase__     ,   1 - c  )

  for i in range(len(UpperCAmelCase__  )  ):
    if not visited[i]:
      dfs(UpperCAmelCase__     ,   0  )

  for i in range(len(UpperCAmelCase__  )  ):
    for j in graph[i]:
      if color[i] == color[j]:
        return False

  return True


# Adjacency list of graph
A_		:		Dict		     =			{0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 4: []}
print(check_bipartite_dfs(graph))