


from typing import TYPE_CHECKING

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


_snake_case  :	Union[str, 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:
   _snake_case  :	Union[str, Any]			      =       ["SqueezeBertTokenizerFast"]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case  :	List[str]			      =       [
       "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

   _snake_case  :	Optional[int]			      =       _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





from maths.prime_check import is_prime







def        lowerCAmelCase_  (      __lowerCamelCase			):
							if not isinstance(__lowerCamelCase							,			__lowerCamelCase			):
														__snake_case	:    List[str]											=     F'Input value of [number={number}] must be an integer'
														raise TypeError(__lowerCamelCase			)
							if is_prime(__lowerCamelCase			) and is_prime(number + 2			):
														return number + 2
							else:
														return -1


if __name__ == "__main__":
			import doctest

			doctest.testmod()

