"""simple docstring"""







from typing import TYPE_CHECKING

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


__SCREAMING_SNAKE_CASE								={"configuration_xlnet": ["XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLNetConfig"]}

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

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

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __SCREAMING_SNAKE_CASE								=[
       "XLNET_PRETRAINED_MODEL_ARCHIVE_LIST",
       "XLNetForMultipleChoice",
       "XLNetForQuestionAnswering",
       "XLNetForQuestionAnsweringSimple",
       "XLNetForSequenceClassification",
       "XLNetForTokenClassification",
       "XLNetLMHeadModel",
       "XLNetModel",
       "XLNetPreTrainedModel",
       "load_tf_weights_in_xlnet",
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __SCREAMING_SNAKE_CASE								=[
       "TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST",
       "TFXLNetForMultipleChoice",
       "TFXLNetForQuestionAnsweringSimple",
       "TFXLNetForSequenceClassification",
       "TFXLNetForTokenClassification",
       "TFXLNetLMHeadModel",
       "TFXLNetMainLayer",
       "TFXLNetModel",
       "TFXLNetPreTrainedModel",
   ]


if TYPE_CHECKING:
   from .configuration_xlnet import XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLNetConfig

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_xlnet import XLNetTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_xlnet_fast import XLNetTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_xlnet import (
          XLNET_PRETRAINED_MODEL_ARCHIVE_LIST,
          XLNetForMultipleChoice,
          XLNetForQuestionAnswering,
          XLNetForQuestionAnsweringSimple,
          XLNetForSequenceClassification,
          XLNetForTokenClassification,
          XLNetLMHeadModel,
          XLNetModel,
          XLNetPreTrainedModel,
          load_tf_weights_in_xlnet,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_xlnet import (
          TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFXLNetForMultipleChoice,
          TFXLNetForQuestionAnsweringSimple,
          TFXLNetForSequenceClassification,
          TFXLNetForTokenClassification,
          TFXLNetLMHeadModel,
          TFXLNetMainLayer,
          TFXLNetModel,
          TFXLNetPreTrainedModel,
      )

else:
   import sys

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


"""simple docstring"""







from argparse import ArgumentParser

from .env import EnvironmentCommand



def     lowercase__( ):
     lowercase_			:       List[Any]									=			ArgumentParser('Diffusers CLI tool'  ,    usage='diffusers-cli <command> [<args>]'   )
     lowercase_			:       int									=			parser.add_subparsers(help='diffusers-cli command helpers'   )

     # Register commands
     EnvironmentCommand.register_subcommand(__SCREAMING_SNAKE_CASE   )

     # Let's go
     lowercase_			:       str									=			parser.parse_args()

     if not hasattr(__SCREAMING_SNAKE_CASE  ,    'func'   ):
          parser.print_help()
          exit(1   )

     # Run
     lowercase_			:       Optional[Any]									=			args.func(__SCREAMING_SNAKE_CASE   )
     service.run()


if __name__ == "__main__":
       main()

