






'''simple docstring'''





import os
import warnings
from pathlib import Path
from typing import Optional, Union

from .dynamic_module_utils import custom_object_save
from .tokenization_utils_base import PreTrainedTokenizerBase
from .utils import PushToHubMixin, copy_func, direct_transformers_import, logging


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

# Dynamically import the Transformers module to grab the attribute classes of the processor form their names.
__A				:				List[str]					=		direct_transformers_import(Path(__file__).parent)


__A				:				Any					=		{
    """AutoTokenizer""": """PreTrainedTokenizerBase""",
    """AutoFeatureExtractor""": """FeatureExtractionMixin""",
    """AutoImageProcessor""": """ImageProcessingMixin""",
}
class 					lowercase							(				_lowerCamelCase   ):


    '''simple docstring'''

    lowerCAmelCase__   					=				["feature_extractor", "tokenizer"]
    # Names need to be attr_class for attr in attributes
    lowerCAmelCase__   					=				None
    lowerCAmelCase__   					=				None
    lowerCAmelCase__   					=				None

    def __init__(       self  :  Dict					,  *__lowerCamelCase  :  List[Any]					,  **__lowerCamelCase  :  Tuple  )				->				Optional[int]:

     '''simple docstring'''




     for key in kwargs:
      if key not in self.attributes:
       raise TypeError(f'''Unexpected keyword argument {key}.'''  )
     for arg, attribute_name in zip(__lowerCamelCase					,  self.attributes  ):
      if attribute_name in kwargs:
       raise TypeError(f'''Got multiple values for argument {attribute_name}.'''  )
      else:
       lowerCamelCase__	=  arg

     if len(__lowerCamelCase  ) != len(self.attributes  ):
      raise ValueError(
          f'''This processor requires {len(self.attributes  )} arguments: {", ".join(self.attributes  )}. Got '''
          f'''{len(__lowerCamelCase  )} arguments instead.'''  )

     # Check each arg is of the proper class (this will also catch a user initializing in the wrong order)
     for attribute_name, arg in kwargs.items():
      lowerCamelCase__	=  getattr(self					,  f'''{attribute_name}_class'''  )
      # Nothing is ever going to be an instance of "AutoXxx", in that case we check the base class.
      lowerCamelCase__	=  AUTO_TO_BASE_CLASS_MAPPING.get(__lowerCamelCase					,  __lowerCamelCase  )
      if isinstance(__lowerCamelCase					,  __lowerCamelCase  ):
       lowerCamelCase__	=  tuple(getattr(__lowerCamelCase					,  __lowerCamelCase  ) for n in class_name if n is not None  )
      else:
       lowerCamelCase__	=  getattr(__lowerCamelCase					,  __lowerCamelCase  )

      if not isinstance(__lowerCamelCase					,  __lowerCamelCase  ):
       raise ValueError(
           f'''Received a {type(__lowerCamelCase  ).__name__} for argument {attribute_name}, but a {class_name} was expected.'''  )

      setattr(self					,  __lowerCamelCase					,  __lowerCamelCase  )

    def __repr__(       self  :  Any  )				->				List[str]:

     '''simple docstring'''




     lowerCamelCase__	=  [f'''- {name}: {repr(getattr(self					,  __lowerCamelCase  )  )}''' for name in self.attributes]
     lowerCamelCase__	=  "\n".join(__lowerCamelCase  )
     return f'''{self.__class__.__name__}:\n{attributes_repr}'''

    def  a__					(       self  :  List[Any]					,  __lowerCamelCase  :  List[Any]					,  __lowerCamelCase  :  bool = False					,  **__lowerCamelCase  :  Tuple  )				->				Tuple:

     '''simple docstring'''




     os.makedirs(__lowerCamelCase					,  exist_ok=__lowerCamelCase  )

     if push_to_hub:
      lowerCamelCase__	=  kwargs.pop("commit_message"					,  __lowerCamelCase  )
      lowerCamelCase__	=  kwargs.pop("repo_id"					,  save_directory.split(os.path.sep  )[-1]  )
      lowerCamelCase__	=  self._create_repo(__lowerCamelCase					,  **__lowerCamelCase  )
      lowerCamelCase__	=  self._get_files_timestamps(__lowerCamelCase  )
     # If we have a custom config, we copy the file defining it in the folder and set the attributes so it can be
     # loaded from the Hub.
     if self._auto_class is not None:
      lowerCamelCase__	=  [getattr(self					,  __lowerCamelCase  ) for attribute_name in self.attributes]
      lowerCamelCase__	=  [(a.init_kwargs if isinstance(__lowerCamelCase					,  __lowerCamelCase  ) else a) for a in attrs]
      custom_object_save(self					,  __lowerCamelCase					,  config=__lowerCamelCase  )

     for attribute_name in self.attributes:
      lowerCamelCase__	=  getattr(self					,  __lowerCamelCase  )
      # Include the processor class in the attribute config so this processor can then be reloaded with the
      # `AutoProcessor` API.
      if hasattr(__lowerCamelCase					,  "_set_processor_class"  ):
       attribute._set_processor_class(self.__class__.__name__  )
      attribute.save_pretrained(__lowerCamelCase  )

     if self._auto_class is not None:
      # We added an attribute to the init_kwargs of the tokenizers, which needs to be cleaned up.
      for attribute_name in self.attributes:
       lowerCamelCase__	=  getattr(self					,  __lowerCamelCase  )
       if isinstance(__lowerCamelCase					,  __lowerCamelCase  ):
        del attribute.init_kwargs["auto_map"]

     if push_to_hub:
      self._upload_modified_files(
          __lowerCamelCase					,  __lowerCamelCase					,  __lowerCamelCase					,  commit_message=__lowerCamelCase					,  token=kwargs.get("use_auth_token"  )					,  )

    @classmethod
    def  a__					(       cls  :  Any					,  __lowerCamelCase  :  Union[str, os.PathLike]					,  __lowerCamelCase  :  Optional[Union[str, os.PathLike]] = None					,  __lowerCamelCase  :  bool = False					,  __lowerCamelCase  :  bool = False					,  __lowerCamelCase  :  Optional[Union[str, bool]] = None					,  __lowerCamelCase  :  str = "main"					,  **__lowerCamelCase  :  Union[str, Any]					,  )				->				Dict:

     '''simple docstring'''




     lowerCamelCase__	=  cache_dir
     lowerCamelCase__	=  force_download
     lowerCamelCase__	=  local_files_only
     lowerCamelCase__	=  revision

     lowerCamelCase__	=  kwargs.pop("use_auth_token"					,  __lowerCamelCase  )
     if use_auth_token is not None:
      warnings.warn(
          "The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers."					,  __lowerCamelCase  )
      if token is not None:
       raise ValueError(
           "`token` and `use_auth_token` are both specified. Please set only the argument `token`."  )
      lowerCamelCase__	=  use_auth_token

     if token is not None:
      # change to `token` in a follow-up PR
      lowerCamelCase__	=  token

     lowerCamelCase__	=  cls._get_arguments_from_pretrained(__lowerCamelCase					,  **__lowerCamelCase  )
     return cls(*__lowerCamelCase  )

    @classmethod
    def  a__					(       cls  :  Optional[Any]					,  __lowerCamelCase  :  Tuple="AutoProcessor"  )				->				str:

     '''simple docstring'''




     if not isinstance(__lowerCamelCase					,  __lowerCamelCase  ):
      lowerCamelCase__	=  auto_class.__name__

     import transformers.models.auto as auto_module

     if not hasattr(__lowerCamelCase					,  __lowerCamelCase  ):
      raise ValueError(f'''{auto_class} is not a valid auto class.'''  )

     lowerCamelCase__	=  auto_class

    @classmethod
    def  a__					(       cls  :  int					,  __lowerCamelCase  :  List[str]					,  **__lowerCamelCase  :  List[str]  )				->				int:

     '''simple docstring'''




     lowerCamelCase__	=  []
     for attribute_name in cls.attributes:
      lowerCamelCase__	=  getattr(cls					,  f'''{attribute_name}_class'''  )
      if isinstance(__lowerCamelCase					,  __lowerCamelCase  ):
       lowerCamelCase__	=  tuple(getattr(__lowerCamelCase					,  __lowerCamelCase  ) if n is not None else None for n in class_name  )
       lowerCamelCase__	=  kwargs.get("use_fast"					,  __lowerCamelCase  )
       if use_fast and classes[1] is not None:
        lowerCamelCase__	=  classes[1]
       else:
        lowerCamelCase__	=  classes[0]
      else:
       lowerCamelCase__	=  getattr(__lowerCamelCase					,  __lowerCamelCase  )

      args.append(attribute_class.from_pretrained(__lowerCamelCase					,  **__lowerCamelCase  )  )
     return args




    @property
    def  a__					(       self  :  Optional[Any]  )				->				List[str]:

     '''simple docstring'''




     lowerCamelCase__	=  getattr(self					,  self.attributes[0]  )
     return getattr(__lowerCamelCase					,  "model_input_names"					,  __lowerCamelCase  )
__A				:				Optional[int]					=		copy_func(ProcessorMixin.push_to_hub)
if ProcessorMixin.push_to_hub.__doc__ is not None:
 __A				:				Any					=		ProcessorMixin.push_to_hub.__doc__.format(
     object="""processor""", object_class="""AutoProcessor""", object_files="""processor files"""
 )









'''simple docstring'''





from __future__ import annotations

from queue import Queue
class 					lowercase							:


    '''simple docstring'''

    def __init__(       self  :  Optional[int]  )				->				None:

     '''simple docstring'''




     lowerCamelCase__	=  {}

    def  a__					(       self  :  Optional[int]  )				->				None:

     '''simple docstring'''




     for i in self.vertices:
      print(__lowerCamelCase					,  " : "					,  " -> ".join([str(__lowerCamelCase  ) for j in self.vertices[i]]  )  )

    def  a__					(       self  :  Optional[Any]					,  __lowerCamelCase  :  int					,  __lowerCamelCase  :  int  )				->				None:

     '''simple docstring'''




     if from_vertex in self.vertices:
      self.vertices[from_vertex].append(__lowerCamelCase  )
     else:
      lowerCamelCase__	=  [to_vertex]




    def  a__					(       self  :  Optional[int]					,  __lowerCamelCase  :  int  )				->				set[int]:

     '''simple docstring'''




     lowerCamelCase__	=  set()

     # create a first in first out queue to store all the vertices for BFS
     lowerCamelCase__	=  Queue()

     # mark the source node as visited and enqueue it
     visited.add(__lowerCamelCase  )
     queue.put(__lowerCamelCase  )

     while not queue.empty():
      lowerCamelCase__	=  queue.get()

      # loop through all adjacent vertex and enqueue it if not yet visited
      for adjacent_vertex in self.vertices[vertex]:
       if adjacent_vertex not in visited:
        queue.put(__lowerCamelCase  )
        visited.add(__lowerCamelCase  )
     return visited


if __name__ == "__main__":
 from doctest import testmod

 testmod(verbose=True)

 __A				:				Optional[Any]					=		Graph()
 g.add_edge(0, 1)
 g.add_edge(0, 2)
 g.add_edge(1, 2)
 g.add_edge(2, 0)
 g.add_edge(2, 3)
 g.add_edge(3, 3)

 g.print_graph()
 # 0  :  1 -> 2
 # 1  :  2
 # 2  :  0 -> 3
 # 3  :  3

 assert sorted(g.bfs(2)) == [0, 1, 2, 3]

