import os
from string import ascii_letters

UpperCAmelCase							=       ascii_letters + " \t\n"






def 					SCREAMING_SNAKE_CASE_			(		):
						snake_case_     :			List[str]       =       os.path.split(os.path.realpath(lowerCAmelCase_     )     )
						snake_case_     :			dict[str, None]       =       {}
						with open(path[0] + "/dictionary.txt"     ) as dictionary_file:
												for word in dictionary_file.read().split("\n"     ):
																		snake_case_     :			List[Any]       =       None
						return english_words


UpperCAmelCase							=       load_dictionary()






def 					SCREAMING_SNAKE_CASE_			(		lowerCAmelCase_: str     ):
						snake_case_     :			List[str]       =       message.upper()
						snake_case_     :			str       =       remove_non_letters(lowerCAmelCase_     )
						snake_case_     :			List[str]       =       message.split()
						snake_case_     :			str       =       len([word for word in possible_words if word in ENGLISH_WORDS]     )
						return float(lowerCAmelCase_     ) / len(lowerCAmelCase_     )






def 					SCREAMING_SNAKE_CASE_			(		lowerCAmelCase_: str     ):
						return "".join(symbol for symbol in message if symbol in LETTERS_AND_SPACE     )






def 					SCREAMING_SNAKE_CASE_			(		lowerCAmelCase_: str ,	lowerCAmelCase_: int = 2_0 ,	lowerCAmelCase_: int = 8_5     ):
						snake_case_     :			Any       =       get_english_count(lowerCAmelCase_     ) * 1_0_0 >= word_percentage
						snake_case_     :			Optional[int]       =       len(remove_non_letters(lowerCAmelCase_     )     )
						snake_case_     :			Tuple       =       (float(lowerCAmelCase_     ) / len(lowerCAmelCase_     )) * 1_0_0
						snake_case_     :			List[Any]       =       message_letters_percentage >= letter_percentage
						return words_match and letters_match


if __name__ == "__main__":
					import doctest

					doctest.testmod()




from typing import TYPE_CHECKING

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


UpperCAmelCase							=       {
    "configuration_nystromformer": ["NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "NystromformerConfig"],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase							=       [
         "NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
         "NystromformerForMaskedLM",
         "NystromformerForMultipleChoice",
         "NystromformerForQuestionAnswering",
         "NystromformerForSequenceClassification",
         "NystromformerForTokenClassification",
         "NystromformerLayer",
         "NystromformerModel",
         "NystromformerPreTrainedModel",
     ]


if TYPE_CHECKING:
     from .configuration_nystromformer import NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, NystromformerConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_nystromformer import (
              NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              NystromformerForMaskedLM,
              NystromformerForMultipleChoice,
              NystromformerForQuestionAnswering,
              NystromformerForSequenceClassification,
              NystromformerForTokenClassification,
              NystromformerLayer,
              NystromformerModel,
              NystromformerPreTrainedModel,
          )


else:
     import sys

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



