

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a_    :						Any    		=      {
    "configuration_bigbird_pegasus": [
        "BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "BigBirdPegasusConfig",
        "BigBirdPegasusOnnxConfig",
    ],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      a_    :						Tuple    		=      [
          "BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST",
          "BigBirdPegasusForCausalLM",
          "BigBirdPegasusForConditionalGeneration",
          "BigBirdPegasusForQuestionAnswering",
          "BigBirdPegasusForSequenceClassification",
          "BigBirdPegasusModel",
          "BigBirdPegasusPreTrainedModel",
      ]


if TYPE_CHECKING:
      from .configuration_bigbird_pegasus import (
          BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP,
          BigBirdPegasusConfig,
          BigBirdPegasusOnnxConfig,
      )

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_bigbird_pegasus import (
                BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
                BigBirdPegasusForCausalLM,
                BigBirdPegasusForConditionalGeneration,
                BigBirdPegasusForQuestionAnswering,
                BigBirdPegasusForSequenceClassification,
                BigBirdPegasusModel,
                BigBirdPegasusPreTrainedModel,
            )


else:
      import sys

      a_    :						List[Any]    		=      _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




import numpy as np


def        __lowerCAmelCase    (       _UpperCamelCase		:  np.ndarray	)		->							np.ndarray:
 '''simple docstring'''


 return 1 / (1 + np.exp(-vector	))


def        __lowerCAmelCase    (       _UpperCamelCase		:  np.ndarray	)		->							np.ndarray:
 '''simple docstring'''


 return vector * sigmoid(_UpperCamelCase	)


if __name__ == "__main__":
      import doctest

      doctest.testmod()

