

from typing import TYPE_CHECKING

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


_lowerCamelCase							={"configuration_hubert": ["HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "HubertConfig"]}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCamelCase							=[
     "HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
     "HubertForCTC",
     "HubertForSequenceClassification",
     "HubertModel",
     "HubertPreTrainedModel",
 ]


try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCamelCase							=[
     "TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
     "TFHubertForCTC",
     "TFHubertModel",
     "TFHubertPreTrainedModel",
 ]

if TYPE_CHECKING:
 from .configuration_hubert import HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, HubertConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_hubert import (
      HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
      HubertForCTC,
      HubertForSequenceClassification,
      HubertModel,
      HubertPreTrainedModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_hubert import (
      TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFHubertForCTC,
      TFHubertModel,
      TFHubertPreTrainedModel,
  )


else:
 import sys

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




import numpy as np







def      snake_case__							(  lowerCAmelCase_     ):





     """simple docstring"""







     SCREAMING_SNAKE_CASE 		=np.exp(lowerCAmelCase_     )

     # Add up the all the exponentials
     SCREAMING_SNAKE_CASE 		=np.sum(lowerCAmelCase_     )

     # Divide every exponent by the sum of all exponents
     SCREAMING_SNAKE_CASE 		=exponent_vector / sum_of_exponents

     return softmax_vector


if __name__ == "__main__":
 print(softmax((0,)))

