


import warnings

from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor


A      :    int		=					logging.get_logger(__name__)







class 			_lowercase (							lowercase_):


       """simple docstring"""




       def __init__(   self							:			Dict					,      *__lowerCamelCase							:			Tuple					,      **__lowerCamelCase							:			List[Any]       ):


             '''simple docstring'''



             warnings.warn(
                 "The class LayoutLMv2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."
                 " Please use LayoutLMv2ImageProcessor instead."					,      __lowerCamelCase					,      )
             super().__init__(*__lowerCamelCase					,      **__lowerCamelCase       )





from __future__ import annotations

import collections
import pprint
from pathlib import Path





def 					__lowerCamelCase	( UpperCamelCase__      ):







							'''simple docstring'''






							return "".join(sorted(UpperCamelCase__      )      )





def 					__lowerCamelCase	( UpperCamelCase__      ):







							'''simple docstring'''






							return word_by_signature[signature(UpperCamelCase__      )]


_UpperCAmelCase		:   str										=       Path(__file__).parent.joinpath("""words.txt""").read_text(encoding="""utf-8""")
_UpperCAmelCase		:   Dict										=       sorted({word.strip().lower() for word in data.splitlines()})

_UpperCAmelCase		:   List[str]										=       collections.defaultdict(list)
for word in word_list:
					word_by_signature[signature(word)].append(word)

if __name__ == "__main__":
					_UpperCAmelCase		:   Dict										=       {word: anagram(word) for word in word_list if len(anagram(word)) > 1}

					with open("""anagrams.txt""", """w""") as file:
										file.write("""all_anagrams = \n """)
										file.write(pprint.pformat(all_anagrams))




