


'''simple docstring'''



from typing import TYPE_CHECKING

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


A__						:   Optional[int]				=    {
    """configuration_transfo_xl""": ["""TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TransfoXLConfig"""],
    """tokenization_transfo_xl""": ["""TransfoXLCorpus""", """TransfoXLTokenizer"""],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__						:   Dict				=    [
          """TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """AdaptiveEmbedding""",
          """TransfoXLForSequenceClassification""",
          """TransfoXLLMHeadModel""",
          """TransfoXLModel""",
          """TransfoXLPreTrainedModel""",
          """load_tf_weights_in_transfo_xl""",
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__						:   List[Any]				=    [
          """TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """TFAdaptiveEmbedding""",
          """TFTransfoXLForSequenceClassification""",
          """TFTransfoXLLMHeadModel""",
          """TFTransfoXLMainLayer""",
          """TFTransfoXLModel""",
          """TFTransfoXLPreTrainedModel""",
      ]


if TYPE_CHECKING:
      from .configuration_transfo_xl import TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP, TransfoXLConfig
      from .tokenization_transfo_xl import TransfoXLCorpus, TransfoXLTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_transfo_xl import (
                TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
                AdaptiveEmbedding,
                TransfoXLForSequenceClassification,
                TransfoXLLMHeadModel,
                TransfoXLModel,
                TransfoXLPreTrainedModel,
                load_tf_weights_in_transfo_xl,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_transfo_xl import (
                TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFAdaptiveEmbedding,
                TFTransfoXLForSequenceClassification,
                TFTransfoXLLMHeadModel,
                TFTransfoXLMainLayer,
                TFTransfoXLModel,
                TFTransfoXLPreTrainedModel,
            )

else:
      import sys

      A__						:   int				=    _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)










'''simple docstring'''



import argparse


A__						:   Optional[Any]				=    """docs/source/_static/js/custom.js"""



def      UpperCAmelCase__   (      UpperCAmelCase_       :							Optional[int]				)	->						int:
     with open(UpperCAmelCase_ ,       encoding='utf-8' ,       newline='\n'				) as f:
          __lowerCamelCase  :      Dict														=						f.readlines()
     __lowerCamelCase  :      Tuple														=						0

     # First let's put the right version
     while not lines[index].startswith('const stableVersion ='				):
          index += 1
     __lowerCamelCase  :      Dict														=						F'const stableVersion = "v{version}"\n'

     # Then update the dictionary
     while not lines[index].startswith('const versionMapping = {'				):
          index += 1

     # We go until the end
     while not lines[index].startswith('}'				):
          index += 1
     # We add the new version at the end
     lines[index - 1] += F'    "v{version}": "v{version}",\n'

     with open(UpperCAmelCase_ ,       'w' ,       encoding='utf-8' ,       newline='\n'				) as f:
          f.writelines(UpperCAmelCase_				)


if __name__ == "__main__":
      A__						:   str				=    argparse.ArgumentParser()
      parser.add_argument("""--version""", help="""Release version.""")
      A__						:   Any				=    parser.parse_args()
      update_custom_js(args.version)






