code: 
  
  
  
  '''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
  
  
  lowerCAmelCase__	:  str 		=logging.get_logger(__name__)
  
  # Dynamically import the Transformers module to grab the attribute classes of the processor form their names.
  lowerCAmelCase__	:  List[Any] 		=direct_transformers_import(Path(__file__).parent)
  
  
  lowerCAmelCase__	:  Union[str, Any] 		={
      '''AutoTokenizer''': '''PreTrainedTokenizerBase''',
      '''AutoFeatureExtractor''': '''FeatureExtractionMixin''',
      '''AutoImageProcessor''': '''ImageProcessingMixin''',
  }
  
  class      UpperCAmelCase_						(     __UpperCAmelCase ):
  
  						'''simple docstring'''
  
  
  
  
  						UpperCamelCase__    :				Optional[int]       						=						["""feature_extractor""", """tokenizer"""]
  						# Names need to be attr_class for attr in attributes
  						UpperCamelCase__    :				Optional[Any]       						=						None
  						UpperCamelCase__    :				str       						=						None
  						UpperCamelCase__    :				Dict       						=						None
  
  
  
  
  
  
  						def __init__(					self   ,							*_A   ,							**_A	):
  
  
  
  
  
  
  
  													'''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:
  																											__SCREAMING_SNAKE_CASE								=      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():
  																				__SCREAMING_SNAKE_CASE								=      getattr(self   ,							f"""{attribute_name}_class"""	)
  																				# Nothing is ever going to be an instance of "AutoXxx", in that case we check the base class.
  																				__SCREAMING_SNAKE_CASE								=      AUTO_TO_BASE_CLASS_MAPPING.get(lowerCamelCase__   ,							lowerCamelCase__	)
  																				if isinstance(lowerCamelCase__   ,							lowerCamelCase__	):
  																											__SCREAMING_SNAKE_CASE								=      tuple(getattr(lowerCamelCase__   ,							lowerCamelCase__	) for n in class_name if n is not None	)
  																				else:
  																											__SCREAMING_SNAKE_CASE								=      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	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													__SCREAMING_SNAKE_CASE								=      [f"""- {name}: {repr(getattr(self   ,							lowerCamelCase__	)	)}""" for name in self.attributes]
  													__SCREAMING_SNAKE_CASE								=      '\n'.join(lowerCamelCase__	)
  													return f"""{self.__class__.__name__}:\n{attributes_repr}"""
  
  
  
  
  
  
  						def  _A			(					self   ,							_A   ,							_A = False   ,							**_A	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													os.makedirs(lowerCamelCase__   ,							exist_ok=lowerCamelCase__	)
  
  													if push_to_hub:
  																				__SCREAMING_SNAKE_CASE								=      kwargs.pop('commit_message'   ,							lowerCamelCase__	)
  																				__SCREAMING_SNAKE_CASE								=      kwargs.pop('repo_id'   ,							save_directory.split(os.path.sep	)[-1]	)
  																				__SCREAMING_SNAKE_CASE								=      self._create_repo(lowerCamelCase__   ,							**lowerCamelCase__	)
  																				__SCREAMING_SNAKE_CASE								=      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:
  																				__SCREAMING_SNAKE_CASE								=      [getattr(self   ,							lowerCamelCase__	) for attribute_name in self.attributes]
  																				__SCREAMING_SNAKE_CASE								=      [(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:
  																				__SCREAMING_SNAKE_CASE								=      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:
  																											__SCREAMING_SNAKE_CASE								=      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   ,							_A   ,							_A = None   ,							_A = False   ,							_A = False   ,							_A = None   ,							_A = "main"   ,							**_A   ,							):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													__SCREAMING_SNAKE_CASE								=      cache_dir
  													__SCREAMING_SNAKE_CASE								=      force_download
  													__SCREAMING_SNAKE_CASE								=      local_files_only
  													__SCREAMING_SNAKE_CASE								=      revision
  
  													__SCREAMING_SNAKE_CASE								=      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`.'	)
  																				__SCREAMING_SNAKE_CASE								=      use_auth_token
  
  													if token is not None:
  																				# change to `token` in a follow-up PR
  																				__SCREAMING_SNAKE_CASE								=      token
  
  													__SCREAMING_SNAKE_CASE								=      cls._get_arguments_from_pretrained(lowerCamelCase__   ,							**lowerCamelCase__	)
  													return cls(*lowerCamelCase__	)
  
  
  
  
  
  
  						@classmethod
  						def  _A			(					cls   ,							_A="AutoProcessor"	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													if not isinstance(lowerCamelCase__   ,							lowerCamelCase__	):
  																				__SCREAMING_SNAKE_CASE								=      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."""	)
  
  													__SCREAMING_SNAKE_CASE								=      auto_class
  
  
  
  
  
  
  						@classmethod
  						def  _A			(					cls   ,							_A   ,							**_A	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													__SCREAMING_SNAKE_CASE								=      []
  													for attribute_name in cls.attributes:
  																				__SCREAMING_SNAKE_CASE								=      getattr(cls   ,							f"""{attribute_name}_class"""	)
  																				if isinstance(lowerCamelCase__   ,							lowerCamelCase__	):
  																											__SCREAMING_SNAKE_CASE								=      tuple(getattr(lowerCamelCase__   ,							lowerCamelCase__	) if n is not None else None for n in class_name	)
  																											__SCREAMING_SNAKE_CASE								=      kwargs.get('use_fast'   ,							lowerCamelCase__	)
  																											if use_fast and classes[1] is not None:
  																																		__SCREAMING_SNAKE_CASE								=      classes[1]
  																											else:
  																																		__SCREAMING_SNAKE_CASE								=      classes[0]
  																				else:
  																											__SCREAMING_SNAKE_CASE								=      getattr(lowerCamelCase__   ,							lowerCamelCase__	)
  
  																				args.append(attribute_class.from_pretrained(lowerCamelCase__   ,							**lowerCamelCase__	)	)
  													return args
  
  
  
  
  
  
  						@property
  						def  _A			(					self	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													__SCREAMING_SNAKE_CASE								=      getattr(self   ,							self.attributes[0]	)
  													return getattr(lowerCamelCase__   ,							'model_input_names'   ,							lowerCamelCase__	)
  
  
  
  
  
  
  
  lowerCAmelCase__	:  Dict 		=copy_func(ProcessorMixin.push_to_hub)
  if ProcessorMixin.push_to_hub.__doc__ is not None:
  			lowerCAmelCase__	:  List[str] 		=ProcessorMixin.push_to_hub.__doc__.format(
  			    object='''processor''', object_class='''AutoProcessor''', object_files='''processor files'''
  			)
  
  
  
  
  
  
  
style_context: 
  
  
  
  from __future__ import annotations
  
  class      UpperCAmelCase_						:
  
  						'''simple docstring'''
  
  
  
  
  						def __init__(					self   ,							_A	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													__SCREAMING_SNAKE_CASE								=      value
  													__SCREAMING_SNAKE_CASE								=      None
  													__SCREAMING_SNAKE_CASE								=      None
  
  
  
  
  
  
  
  class      UpperCAmelCase_						:
  
  						'''simple docstring'''
  
  
  
  
  						UpperCamelCase__    :				int
  
  
  
  
  
  
  						def __init__(					self	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													__SCREAMING_SNAKE_CASE								=      0
  
  
  
  
  
  
  						def  _A			(					self   ,							_A   ,							_A	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													if node is None:
  																				return
  
  													if path_sum == self.target:
  																				self.paths += 1
  
  													if node.left:
  																				self.depth_first_search(node.left   ,							path_sum + node.left.value	)
  													if node.right:
  																				self.depth_first_search(node.right   ,							path_sum + node.right.value	)
  
  
  
  
  
  
  						def  _A			(					self   ,							_A   ,							_A = None	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													if node is None:
  																				return 0
  													if target is not None:
  																				__SCREAMING_SNAKE_CASE								=      target
  
  													self.depth_first_search(_A   ,							node.value	)
  													self.path_sum(node.left	)
  													self.path_sum(node.right	)
  
  													return self.paths
  
  
  if __name__ == "__main__":
  			import doctest
  
  			doctest.testmod()
  
  
  
  
  
  
  