




from typing import TYPE_CHECKING

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


lowerCamelCase    :		List[Any]			   =       {
    "configuration_squeezebert": [
        "SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "SqueezeBertConfig",
        "SqueezeBertOnnxConfig",
    ],
    "tokenization_squeezebert": ["SqueezeBertTokenizer"],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase    :		Dict			   =       ["SqueezeBertTokenizerFast"]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase    :		Any			   =       [
     "SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
     "SqueezeBertForMaskedLM",
     "SqueezeBertForMultipleChoice",
     "SqueezeBertForQuestionAnswering",
     "SqueezeBertForSequenceClassification",
     "SqueezeBertForTokenClassification",
     "SqueezeBertModel",
     "SqueezeBertModule",
     "SqueezeBertPreTrainedModel",
 ]


if TYPE_CHECKING:
 from .configuration_squeezebert import (
     SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
     SqueezeBertConfig,
     SqueezeBertOnnxConfig,
 )
 from .tokenization_squeezebert import SqueezeBertTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_squeezebert import (
      SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
      SqueezeBertForMaskedLM,
      SqueezeBertForMultipleChoice,
      SqueezeBertForQuestionAnswering,
      SqueezeBertForSequenceClassification,
      SqueezeBertForTokenClassification,
      SqueezeBertModel,
      SqueezeBertModule,
      SqueezeBertPreTrainedModel,
  )

else:
 import sys

 lowerCamelCase    :		Tuple			   =       _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)









def       _SCREAMING_SNAKE_CASE      (							lowercase     :	str     ,							lowercase     :	int					):


      '''simple docstring'''



      return [sentence[i : i + ngram_size] for i in range(len(lowercase					) - ngram_size + 1					)]


if __name__ == "__main__":
 from doctest import testmod

 testmod()



