





from __future__ import annotations

import collections
import pprint
from pathlib import Path


def 							SCREAMING_SNAKE_CASE__  (      __a				):
	return "".join(sorted(__a				)				)


def 							SCREAMING_SNAKE_CASE__  (      __a				):
	return word_by_signature[signature(__a				)]


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

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

if __name__ == "__main__":
						_SCREAMING_SNAKE_CASE 		=						{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))








import warnings

from ..trainer import Trainer
from ..utils import logging


_SCREAMING_SNAKE_CASE 		=						logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE_  (   snake_case_   ):






						def __init__( self : Any						,				_A : str=None						,				**_A : Union[str, Any]		)							->      Any:







							"""simple docstring"""


							warnings.warn(
							    '`SageMakerTrainer` is deprecated and will be removed in v5 of Transformers. You can use `Trainer` '
							    'instead.'						,				_A						,				)
							super().__init__(args=_A						,				**_A		)

