



# Author: OMKAR PATHAK, Nwachukwu Chidiebere

# Use a Python dictionary to construct the graph.
from __future__ import annotations

from pprint import pformat
from typing import Generic, TypeVar

_lowerCAmelCase    : Any							=							TypeVar("T")






class      UpperCAmelCase_  (    Generic[T]						):



      def __init__(					self					:     List[Any]					,     A					:     List[str] = True						):
           _UpperCAmelCase      :     Any        =   {}  # dictionary of lists
           _UpperCAmelCase      :     str        =   directed



      def 						snake_case_ (					self					:     Optional[Any]					,     A					:     Tuple					,     A					:     Dict						):

           if not self.directed:  # For undirected graphs
                # if both source vertex and destination vertex are both present in the
                # adjacency list, add destination vertex to source vertex list of adjacent
                # vertices and add source vertex to destination vertex list of adjacent
                # vertices.
                if source_vertex in self.adj_list and destination_vertex in self.adj_list:
                     self.adj_list[source_vertex].append(A						)
                     self.adj_list[destination_vertex].append(A						)
                # if only source vertex is present in adjacency list, add destination vertex
                # to source vertex list of adjacent vertices, then create a new vertex with
                # destination vertex as key and assign a list containing the source vertex
                # as it's first adjacent vertex.
                elif source_vertex in self.adj_list:
                     self.adj_list[source_vertex].append(A						)
                     _UpperCAmelCase      :     List[Any]        =   [source_vertex]
                # if only destination vertex is present in adjacency list, add source vertex
                # to destination vertex list of adjacent vertices, then create a new vertex
                # with source vertex as key and assign a list containing the source vertex
                # as it's first adjacent vertex.
                elif destination_vertex in self.adj_list:
                     self.adj_list[destination_vertex].append(A						)
                     _UpperCAmelCase      :     int        =   [destination_vertex]
                # if both source vertex and destination vertex are not present in adjacency
                # list, create a new vertex with source vertex as key and assign a list
                # containing the destination vertex as it's first adjacent vertex also
                # create a new vertex with destination vertex as key and assign a list
                # containing the source vertex as it's first adjacent vertex.
                else:
                     _UpperCAmelCase      :     Optional[int]        =   [destination_vertex]
                     _UpperCAmelCase      :     str        =   [source_vertex]
           else:  # For directed graphs
                # if both source vertex and destination vertex are present in adjacency
                # list, add destination vertex to source vertex list of adjacent vertices.
                if source_vertex in self.adj_list and destination_vertex in self.adj_list:
                     self.adj_list[source_vertex].append(A						)
                # if only source vertex is present in adjacency list, add destination
                # vertex to source vertex list of adjacent vertices and create a new vertex
                # with destination vertex as key, which has no adjacent vertex
                elif source_vertex in self.adj_list:
                     self.adj_list[source_vertex].append(A						)
                     _UpperCAmelCase      :     List[Any]        =   []
                # if only destination vertex is present in adjacency list, create a new
                # vertex with source vertex as key and assign a list containing destination
                # vertex as first adjacent vertex
                elif destination_vertex in self.adj_list:
                     _UpperCAmelCase      :     Optional[int]        =   [destination_vertex]
                # if both source vertex and destination vertex are not present in adjacency
                # list, create a new vertex with source vertex as key and a list containing
                # destination vertex as it's first adjacent vertex. Then create a new vertex
                # with destination vertex as key, which has no adjacent vertex
                else:
                     _UpperCAmelCase      :     Dict        =   [destination_vertex]
                     _UpperCAmelCase      :     int        =   []

           return self



      def __repr__(					self					:     Union[str, Any]						):
           return pformat(self.adj_list						)





"""simple docstring"""




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
_lowerCAmelCase    : Dict							=							"src/transformers"


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

_lowerCAmelCase    : Tuple							=							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)`
_lowerCAmelCase    : Optional[int]							=							re.compile("\[(.+?)\]\((https://huggingface\.co/.+?)\)")


_lowerCAmelCase    : Optional[int]							=							{
    "CLIPConfigMixin",
    "DecisionTransformerConfigMixin",
    "EncoderDecoderConfigMixin",
    "RagConfigMixin",
    "SpeechEncoderDecoderConfigMixin",
    "VisionEncoderDecoderConfigMixin",
    "VisionTextDualEncoderConfigMixin",
}

def 						__snake_case						(				)  ->       Dict:





     '''simple docstring'''

     _UpperCAmelCase      :     List[str]        =   []

     for config_class in list(CONFIG_MAPPING.values()    ):
          _UpperCAmelCase      :     Union[str, Any]        =   False

          # source code of `config_class`
          _UpperCAmelCase      :     Optional[int]        =   inspect.getsource(SCREAMING_SNAKE_CASE__    )
          _UpperCAmelCase      :     List[Any]        =   _re_checkpoint.findall(SCREAMING_SNAKE_CASE__    )

          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    ,	_UpperCAmelCase      :     List[Any]        =   checkpoint

               # verify the checkpoint name corresponds to the checkpoint link
               _UpperCAmelCase      :     Optional[Any]        =   f'https://huggingface.co/{ckpt_name}'
               if ckpt_link == ckpt_link_from_name:
                    _UpperCAmelCase      :     Optional[Any]        =   True
                    break

          _UpperCAmelCase      :     int        =   config_class.__name__
          if not checkpoint_found and name not in CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK:
               configs_without_checkpoint.append(SCREAMING_SNAKE_CASE__    )

     if len(SCREAMING_SNAKE_CASE__    ) > 0:
          _UpperCAmelCase      :     List[str]        =   "\n".join(sorted(SCREAMING_SNAKE_CASE__    )    )
          raise ValueError(f'The following configurations don\'t contain any valid checkpoint:\n{message}'    )


if __name__ == "__main__":
 check_config_docstrings_have_checkpoints()
