"""simple docstring"""



import os
from string import ascii_letters

__magic_name__    				=					ascii_letters + " \t\n"





def   _lowerCamelCase ( )							->     dict[str, None]:


   '''simple docstring'''


   a__     				=		os.path.split(os.path.realpath(UpperCAmelCase__					)					)
   a__     				=		{}
   with open(path[0] + '/dictionary.txt'					) as dictionary_file:
      for word in dictionary_file.read().split('\n'					):
         a__     				=		None
   return english_words


__magic_name__    				=					load_dictionary()





def   _lowerCamelCase ( UpperCAmelCase__					)							->     float:


   '''simple docstring'''


   a__     				=		message.upper()
   a__     				=		remove_non_letters(UpperCAmelCase__					)
   a__     				=		message.split()
   a__     				=		len([word for word in possible_words if word in ENGLISH_WORDS]					)
   return float(UpperCAmelCase__					) / len(UpperCAmelCase__					)





def   _lowerCamelCase ( UpperCAmelCase__					)							->     str:


   '''simple docstring'''


   return "".join(symbol for symbol in message if symbol in LETTERS_AND_SPACE					)





def   _lowerCamelCase ( UpperCAmelCase__,UpperCAmelCase__ = 20,UpperCAmelCase__ = 85					)							->     bool:


   '''simple docstring'''


   a__     				=		get_english_count(UpperCAmelCase__					) * 1_00 >= word_percentage
   a__     				=		len(remove_non_letters(UpperCAmelCase__					)					)
   a__     				=		(float(UpperCAmelCase__					) / len(UpperCAmelCase__					)) * 1_00
   a__     				=		message_letters_percentage >= letter_percentage
   return words_match and letters_match


if __name__ == "__main__":
     import doctest

     doctest.testmod()



"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


__magic_name__    				=					{"configuration_hubert": ["HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "HubertConfig"]}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __magic_name__    				=					[
         "HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
         "HubertForCTC",
         "HubertForSequenceClassification",
         "HubertModel",
         "HubertPreTrainedModel",
     ]


try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __magic_name__    				=					[
         "TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
         "TFHubertForCTC",
         "TFHubertModel",
         "TFHubertPreTrainedModel",
     ]

if TYPE_CHECKING:
     from .configuration_hubert import HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, HubertConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_hubert import (
              HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
              HubertForCTC,
              HubertForSequenceClassification,
              HubertModel,
              HubertPreTrainedModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_hubert import (
              TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFHubertForCTC,
              TFHubertModel,
              TFHubertPreTrainedModel,
          )


else:
     import sys

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


