






"""simple docstring"""



def 		_SCREAMING_SNAKE_CASE					(       __snake_case     :    int = 99_80_01       ):





  '''simple docstring'''





  for number in range(n - 1						,   99_99						,   -1       ):
    lowercase				       =			str(__snake_case       )

    # checks whether 'str_number' is a palindrome.
    if str_number == str_number[::-1]:
      lowercase				       =			9_99

      # if 'number' is a product of two 3-digit numbers
      # then number is the answer otherwise fetch next number.
      while divisor != 99:
        if (number % divisor == 0) and (len(str(number // divisor       )       ) == 3.0):
          return number
        divisor -= 1
  raise ValueError('That number is larger than our acceptable range.'       )


if __name__ == "__main__":
    print(F'''{solution() = }''')



"""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


UpperCamelCase_							:							Optional[int]				 =		logging.get_logger(__name__)

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


UpperCamelCase_							:							Optional[int]				 =		{
    """AutoTokenizer""": """PreTrainedTokenizerBase""",
    """AutoFeatureExtractor""": """FeatureExtractionMixin""",
    """AutoImageProcessor""": """ImageProcessingMixin""",
}


class       _lowercase		( __lowerCamelCase	):
				lowerCamelCase__							=							['feature_extractor', 'tokenizer']
				# Names need to be attr_class for attr in attributes
				lowerCamelCase__							=							None
				lowerCamelCase__							=							None
				lowerCamelCase__							=							None

				def __init__(  self							:     Any							,     *_lowercase							:     Optional[int]							,     **_lowercase							:     int  ):


										'''simple docstring'''
										# Sanitize args and kwargs
										for key in kwargs:
																if key not in self.attributes:
																						raise TypeError(f'Unexpected keyword argument {key}.'  )
										for arg, attribute_name in zip(_lowercase							,     self.attributes  ):
																if attribute_name in kwargs:
																						raise TypeError(f'Got multiple values for argument {attribute_name}.'  )
																else:
																						UpperCAmelCase__       						=		arg

										if len(_lowercase  ) != len(self.attributes  ):
																raise ValueError(
																    f'This processor requires {len(self.attributes  )} arguments: {", ".join(self.attributes  )}. Got '
																    f'{len(_lowercase  )} 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():
																UpperCAmelCase__       						=		getattr(self							,     f'{attribute_name}_class'  )
																# Nothing is ever going to be an instance of "AutoXxx", in that case we check the base class.
																UpperCAmelCase__       						=		AUTO_TO_BASE_CLASS_MAPPING.get(_lowercase							,     _lowercase  )
																if isinstance(_lowercase							,     _lowercase  ):
																						UpperCAmelCase__       						=		tuple(getattr(_lowercase							,     _lowercase  ) for n in class_name if n is not None  )
																else:
																						UpperCAmelCase__       						=		getattr(_lowercase							,     _lowercase  )

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

																setattr(self							,     _lowercase							,     _lowercase  )

				def __repr__(  self							:     Tuple  ):


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

				def 							A			(  self							:     Tuple							,     _lowercase							:     Dict							,     _lowercase							:     bool = False							,     **_lowercase							:     List[str]  ):


										'''simple docstring'''
										os.makedirs(_lowercase							,     exist_ok=_lowercase  )

										if push_to_hub:
																UpperCAmelCase__       						=		kwargs.pop("""commit_message"""							,     _lowercase  )
																UpperCAmelCase__       						=		kwargs.pop("""repo_id"""							,     save_directory.split(os.path.sep  )[-1]  )
																UpperCAmelCase__       						=		self._create_repo(_lowercase							,     **_lowercase  )
																UpperCAmelCase__       						=		self._get_files_timestamps(_lowercase  )
										# 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:
																UpperCAmelCase__       						=		[getattr(self							,     _lowercase  ) for attribute_name in self.attributes]
																UpperCAmelCase__       						=		[(a.init_kwargs if isinstance(_lowercase							,     _lowercase  ) else a) for a in attrs]
																custom_object_save(self							,     _lowercase							,     config=_lowercase  )

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

										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:
																						UpperCAmelCase__       						=		getattr(self							,     _lowercase  )
																						if isinstance(_lowercase							,     _lowercase  ):
																												del attribute.init_kwargs["auto_map"]

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

				@classmethod
				def 							A			(  cls							:     Dict							,     _lowercase							:     Union[str, os.PathLike]							,     _lowercase							:     Optional[Union[str, os.PathLike]] = None							,     _lowercase							:     bool = False							,     _lowercase							:     bool = False							,     _lowercase							:     Optional[Union[str, bool]] = None							,     _lowercase							:     str = "main"							,     **_lowercase							:     Dict							,     ):


										'''simple docstring'''
										UpperCAmelCase__       						=		cache_dir
										UpperCAmelCase__       						=		force_download
										UpperCAmelCase__       						=		local_files_only
										UpperCAmelCase__       						=		revision

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

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

										UpperCAmelCase__       						=		cls._get_arguments_from_pretrained(_lowercase							,     **_lowercase  )
										return cls(*_lowercase  )

				@classmethod
				def 							A			(  cls							:     List[Any]							,     _lowercase							:     Dict="AutoProcessor"  ):


										'''simple docstring'''
										if not isinstance(_lowercase							,     _lowercase  ):
																UpperCAmelCase__       						=		auto_class.__name__

										import transformers.models.auto as auto_module

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

										UpperCAmelCase__       						=		auto_class

				@classmethod
				def 							A			(  cls							:     Any							,     _lowercase							:     Tuple							,     **_lowercase							:     List[Any]  ):


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

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

				@property
				def 							A			(  self							:     int  ):


										'''simple docstring'''
										UpperCAmelCase__       						=		getattr(self							,     self.attributes[0]  )
										return getattr(_lowercase							,     """model_input_names"""							,     _lowercase  )
UpperCamelCase_							:							List[Any]				 =		copy_func(ProcessorMixin.push_to_hub)
if ProcessorMixin.push_to_hub.__doc__ is not None:
						UpperCamelCase_							:							Dict				 =		ProcessorMixin.push_to_hub.__doc__.format(
						    object="""processor""", object_class="""AutoProcessor""", object_files="""processor files"""
						)

