"""simple docstring"""







from typing import TYPE_CHECKING

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


__SCREAMING_SNAKE_CASE								={
    "configuration_lxmert": ["LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LxmertConfig"],
    "tokenization_lxmert": ["LxmertTokenizer"],
}

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __SCREAMING_SNAKE_CASE								=["LxmertTokenizerFast"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __SCREAMING_SNAKE_CASE								=[
           "LxmertEncoder",
           "LxmertForPreTraining",
           "LxmertForQuestionAnswering",
           "LxmertModel",
           "LxmertPreTrainedModel",
           "LxmertVisualFeatureEncoder",
           "LxmertXLayer",
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __SCREAMING_SNAKE_CASE								=[
           "TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TFLxmertForPreTraining",
           "TFLxmertMainLayer",
           "TFLxmertModel",
           "TFLxmertPreTrainedModel",
           "TFLxmertVisualFeatureEncoder",
       ]


if TYPE_CHECKING:
       from .configuration_lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig
       from .tokenization_lxmert import LxmertTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_lxmert_fast import LxmertTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_lxmert import (
                  LxmertEncoder,
                  LxmertForPreTraining,
                  LxmertForQuestionAnswering,
                  LxmertModel,
                  LxmertPreTrainedModel,
                  LxmertVisualFeatureEncoder,
                  LxmertXLayer,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_lxmert import (
                  TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFLxmertForPreTraining,
                  TFLxmertMainLayer,
                  TFLxmertModel,
                  TFLxmertPreTrainedModel,
                  TFLxmertVisualFeatureEncoder,
              )

else:
       import sys

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


"""simple docstring"""







import numpy as np



def     lowercase__( __SCREAMING_SNAKE_CASE							:  np.array   ):
     return 1 / (1 + np.exp(-vector   ))


if __name__ == "__main__":
       import doctest

       doctest.testmod()

