



from typing import TYPE_CHECKING

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


_lowercase		:				str      		={
    '''configuration_lxmert''': ['''LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LxmertConfig'''],
    '''tokenization_lxmert''': ['''LxmertTokenizer'''],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowercase		:				Union[str, Any]      		=['''LxmertTokenizerFast''']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowercase		:				List[Any]      		=[
      '''LxmertEncoder''',
      '''LxmertForPreTraining''',
      '''LxmertForQuestionAnswering''',
      '''LxmertModel''',
      '''LxmertPreTrainedModel''',
      '''LxmertVisualFeatureEncoder''',
      '''LxmertXLayer''',
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowercase		:				List[Any]      		=[
      '''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

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









def      lowerCAmelCase_					(  _lowercase    :       int)							->	int:







			"""simple docstring"""

			if not isinstance(_lowercase						,       _lowercase):
						raise TypeError("""only integers accepted as input""")
			else:
						a__       :						Any							=  str(abs(_lowercase))
						a__       :						str							=  [list(_lowercase) for char in range(len(_lowercase))]
						for index in range(len(_lowercase)):
									num_transpositions[index].pop(_lowercase)
						return max(
						    int("""""".join(list(_lowercase))) for transposition in num_transpositions)


if __name__ == "__main__":
		__import__("doctest").testmod()




