


from __future__ import annotations

import collections
import pprint
from pathlib import Path




def    snake_case_     (  snake_case     )  ->				str:
       return "".join(sorted(_lowerCAmelCase     )     )




def    snake_case_     (  snake_case     )  ->				list[str]:
       return word_by_signature[signature(_lowerCAmelCase     )]


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

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

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







'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__a          =		{
    "configuration_timesformer": ["TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "TimesformerConfig"],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __a          =		[
           "TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TimesformerModel",
           "TimesformerForVideoClassification",
           "TimesformerPreTrainedModel",
       ]

if TYPE_CHECKING:
       from .configuration_timesformer import TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, TimesformerConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_timesformer import (
                  TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TimesformerForVideoClassification,
                  TimesformerModel,
                  TimesformerPreTrainedModel,
              )

else:
       import sys

       __a          =		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
