


'''simple docstring'''






from typing import TYPE_CHECKING

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


a_    :			Dict      				=			{"""configuration_xlnet""": ["""XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLNetConfig"""]}

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

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a_    :			Union[str, Any]      				=			["""XLNetTokenizerFast"""]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a_    :			Optional[int]      				=			[
     """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:
 a_    :			int      				=			[
     """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

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








from ..utils import is_flax_available, is_torch_available


if is_torch_available():
    from .autoencoder_kl import AutoencoderKL
    from .controlnet import ControlNetModel
    from .dual_transformer_ad import DualTransformeraDModel
    from .modeling_utils import ModelMixin
    from .prior_transformer import PriorTransformer
    from .ta_film_transformer import TaFilmDecoder
    from .transformer_ad import TransformeraDModel
    from .unet_ad import UNetaDModel
    from .unet_ad import UNetaDModel
    from .unet_ad_condition import UNetaDConditionModel
    from .unet_ad_condition import UNetaDConditionModel
    from .vq_model import VQModel

if is_flax_available():
    from .controlnet_flax import FlaxControlNetModel
    from .unet_ad_condition_flax import FlaxUNetaDConditionModel
    from .vae_flax import FlaxAutoencoderKL


