


from typing import TYPE_CHECKING

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


a					  =     {'configuration_xlnet': ['XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'XLNetConfig']}

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

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

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							a					  =     [
							    '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					  =     [
							    '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					  =     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






def 			UpperCAmelCase_				(      UpperCAmelCase__  ):
					return " ".join(input_str.split()[::-1]  )


if __name__ == "__main__":
							import doctest

							doctest.testmod()


