

from typing import TYPE_CHECKING

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


_UpperCamelCase 			=		{
    "configuration_biogpt": ["BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BioGptConfig"],
    "tokenization_biogpt": ["BioGptTokenizer"],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _UpperCamelCase 			=		[
     "BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST",
     "BioGptForCausalLM",
     "BioGptForTokenClassification",
     "BioGptForSequenceClassification",
     "BioGptModel",
     "BioGptPreTrainedModel",
 ]


if TYPE_CHECKING:
 from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
 from .tokenization_biogpt import BioGptTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_biogpt import (
      BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
      BioGptForCausalLM,
      BioGptForSequenceClassification,
      BioGptForTokenClassification,
      BioGptModel,
      BioGptPreTrainedModel,
  )


else:
 import sys

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





def 		_lowercase (     lowercase__   ,	lowercase__						):

      if density <= 0:
            raise ValueError('''Impossible fluid density'''						)
      if bulk_modulus <= 0:
            raise ValueError('''Impossible bulk modulus'''						)

      return (bulk_modulus / density) ** 0.5


if __name__ == "__main__":
 import doctest

 doctest.testmod()


