




def 							__lowerCAmelCase			(UpperCAmelCase_		):
    a__  			=							word.upper()
    a__  			=							0
    a__  			=							{}
    a__  			=							[]

    for letter in word:
        if letter not in letter_nums:
            a__  			=							str(_SCREAMING_SNAKE_CASE		)
            next_num += 1
        word_pattern.append(letter_nums[letter]		)
    return ".".join(_SCREAMING_SNAKE_CASE		)


if __name__ == "__main__":
 import pprint
 import time

 SCREAMING_SNAKE_CASE_    :       List[Any]       =							time.time()
 with open('''dictionary.txt''') as in_file:
  SCREAMING_SNAKE_CASE_    :       Tuple       =							in_file.read().splitlines()

 SCREAMING_SNAKE_CASE_    :       dict       =							{}
 for word in word_list:
  SCREAMING_SNAKE_CASE_    :       List[str]       =							get_word_pattern(word)
  if pattern in all_patterns:
   all_patterns[pattern].append(word)
  else:
   SCREAMING_SNAKE_CASE_    :       Tuple       =							[word]

 with open('''word_patterns.txt''', '''w''') as out_file:
  out_file.write(pprint.pformat(all_patterns))

 SCREAMING_SNAKE_CASE_    :       Dict       =							round(time.time() - start_time, 2)
 print(F"Done!  {len(all_patterns):,} word patterns found in {total_time} seconds.")
 # Done!  9,581 word patterns found in 0.58 seconds.







"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase      : Dict       ={'''configuration_sew_d''': ['''SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SEWDConfig''']}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase      : List[str]       =[
           '''SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''SEWDForCTC''',
           '''SEWDForSequenceClassification''',
           '''SEWDModel''',
           '''SEWDPreTrainedModel''',
       ]

if TYPE_CHECKING:
       from .configuration_sew_d import SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWDConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_sew_d import (
                  SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST,
                  SEWDForCTC,
                  SEWDForSequenceClassification,
                  SEWDModel,
                  SEWDPreTrainedModel,
              )


else:
       import sys

       lowerCamelCase      : str       =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



