
'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


A							     = {
    "configuration_marian": ["MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP", "MarianConfig", "MarianOnnxConfig"],
}

try:
     if not is_sentencepiece_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A							     = ["MarianTokenizer"]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A							     = [
         "MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST",
         "MarianForCausalLM",
         "MarianModel",
         "MarianMTModel",
         "MarianPreTrainedModel",
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A							     = ["TFMarianModel", "TFMarianMTModel", "TFMarianPreTrainedModel"]

try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A							     = ["FlaxMarianModel", "FlaxMarianMTModel", "FlaxMarianPreTrainedModel"]

if TYPE_CHECKING:
     from .configuration_marian import MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP, MarianConfig, MarianOnnxConfig

     try:
          if not is_sentencepiece_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_marian import MarianTokenizer

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_marian import (
              MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST,
              MarianForCausalLM,
              MarianModel,
              MarianMTModel,
              MarianPreTrainedModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_marian import TFMarianModel, TFMarianMTModel, TFMarianPreTrainedModel

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flax_marian import FlaxMarianModel, FlaxMarianMTModel, FlaxMarianPreTrainedModel

else:
     import sys

     A							     = _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,)))

