



"""simple docstring"""






from typing import TYPE_CHECKING

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


__snake_case				:  Union[str, Any] =       {
    '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:
	__snake_case				:  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:
	__snake_case				:  int =       [
	    '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

	__snake_case				:  Tuple =       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




"""simple docstring"""






from ..utils import DummyObject, requires_backends



class      A__  (    metaclass=__SCREAMING_SNAKE_CASE				):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE        =      ['torch', 'transformers', 'onnx']

	def __init__(	self:						Union[str, Any]			,     *_SCREAMING_SNAKE_CASE:						Any			,     **_SCREAMING_SNAKE_CASE:						int)							->			List[Any]:

				"""simple docstring"""

				requires_backends(self			,     ["torch", "transformers", "onnx"])

	@classmethod
	def 				_SCREAMING_SNAKE_CASE  (	cls:						Union[str, Any]			,     *_SCREAMING_SNAKE_CASE:						List[Any]			,     **_SCREAMING_SNAKE_CASE:						Union[str, Any])							->			Union[str, Any]:

				"""simple docstring"""

				requires_backends(cls			,     ["torch", "transformers", "onnx"])







	@classmethod
	def 				_SCREAMING_SNAKE_CASE  (	cls:						int			,     *_SCREAMING_SNAKE_CASE:						Any			,     **_SCREAMING_SNAKE_CASE:						str)							->			Union[str, Any]:

				"""simple docstring"""

				requires_backends(cls			,     ["torch", "transformers", "onnx"])






class      A__  (    metaclass=__SCREAMING_SNAKE_CASE				):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE        =      ['torch', 'transformers', 'onnx']

	def __init__(	self:						Tuple			,     *_SCREAMING_SNAKE_CASE:						Optional[Any]			,     **_SCREAMING_SNAKE_CASE:						List[str])							->			Optional[int]:

				"""simple docstring"""

				requires_backends(self			,     ["torch", "transformers", "onnx"])

	@classmethod
	def 				_SCREAMING_SNAKE_CASE  (	cls:						Dict			,     *_SCREAMING_SNAKE_CASE:						Optional[Any]			,     **_SCREAMING_SNAKE_CASE:						int)							->			List[Any]:

				"""simple docstring"""

				requires_backends(cls			,     ["torch", "transformers", "onnx"])







	@classmethod
	def 				_SCREAMING_SNAKE_CASE  (	cls:						Optional[Any]			,     *_SCREAMING_SNAKE_CASE:						Dict			,     **_SCREAMING_SNAKE_CASE:						Optional[Any])							->			Union[str, Any]:

				"""simple docstring"""

				requires_backends(cls			,     ["torch", "transformers", "onnx"])






class      A__  (    metaclass=__SCREAMING_SNAKE_CASE				):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE        =      ['torch', 'transformers', 'onnx']

	def __init__(	self:						int			,     *_SCREAMING_SNAKE_CASE:						List[Any]			,     **_SCREAMING_SNAKE_CASE:						int)							->			List[str]:

				"""simple docstring"""

				requires_backends(self			,     ["torch", "transformers", "onnx"])

	@classmethod
	def 				_SCREAMING_SNAKE_CASE  (	cls:						Dict			,     *_SCREAMING_SNAKE_CASE:						Any			,     **_SCREAMING_SNAKE_CASE:						Any)							->			str:

				"""simple docstring"""

				requires_backends(cls			,     ["torch", "transformers", "onnx"])







	@classmethod
	def 				_SCREAMING_SNAKE_CASE  (	cls:						List[Any]			,     *_SCREAMING_SNAKE_CASE:						List[str]			,     **_SCREAMING_SNAKE_CASE:						int)							->			int:

				"""simple docstring"""

				requires_backends(cls			,     ["torch", "transformers", "onnx"])






class      A__  (    metaclass=__SCREAMING_SNAKE_CASE				):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE        =      ['torch', 'transformers', 'onnx']

	def __init__(	self:						Tuple			,     *_SCREAMING_SNAKE_CASE:						List[str]			,     **_SCREAMING_SNAKE_CASE:						List[str])							->			Optional[Any]:

				"""simple docstring"""

				requires_backends(self			,     ["torch", "transformers", "onnx"])

	@classmethod
	def 				_SCREAMING_SNAKE_CASE  (	cls:						List[str]			,     *_SCREAMING_SNAKE_CASE:						Tuple			,     **_SCREAMING_SNAKE_CASE:						int)							->			int:

				"""simple docstring"""

				requires_backends(cls			,     ["torch", "transformers", "onnx"])







	@classmethod
	def 				_SCREAMING_SNAKE_CASE  (	cls:						Optional[int]			,     *_SCREAMING_SNAKE_CASE:						str			,     **_SCREAMING_SNAKE_CASE:						Any)							->			int:

				"""simple docstring"""

				requires_backends(cls			,     ["torch", "transformers", "onnx"])






class      A__  (    metaclass=__SCREAMING_SNAKE_CASE				):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE        =      ['torch', 'transformers', 'onnx']

	def __init__(	self:						Optional[Any]			,     *_SCREAMING_SNAKE_CASE:						Union[str, Any]			,     **_SCREAMING_SNAKE_CASE:						Optional[int])							->			str:

				"""simple docstring"""

				requires_backends(self			,     ["torch", "transformers", "onnx"])

	@classmethod
	def 				_SCREAMING_SNAKE_CASE  (	cls:						Optional[int]			,     *_SCREAMING_SNAKE_CASE:						List[Any]			,     **_SCREAMING_SNAKE_CASE:						Tuple)							->			Union[str, Any]:

				"""simple docstring"""

				requires_backends(cls			,     ["torch", "transformers", "onnx"])







	@classmethod
	def 				_SCREAMING_SNAKE_CASE  (	cls:						int			,     *_SCREAMING_SNAKE_CASE:						str			,     **_SCREAMING_SNAKE_CASE:						Any)							->			Optional[Any]:

				"""simple docstring"""

				requires_backends(cls			,     ["torch", "transformers", "onnx"])






class      A__  (    metaclass=__SCREAMING_SNAKE_CASE				):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE        =      ['torch', 'transformers', 'onnx']

	def __init__(	self:						List[Any]			,     *_SCREAMING_SNAKE_CASE:						List[str]			,     **_SCREAMING_SNAKE_CASE:						List[str])							->			int:

				"""simple docstring"""

				requires_backends(self			,     ["torch", "transformers", "onnx"])

	@classmethod
	def 				_SCREAMING_SNAKE_CASE  (	cls:						Union[str, Any]			,     *_SCREAMING_SNAKE_CASE:						Optional[int]			,     **_SCREAMING_SNAKE_CASE:						Optional[Any])							->			List[Any]:

				"""simple docstring"""

				requires_backends(cls			,     ["torch", "transformers", "onnx"])







	@classmethod
	def 				_SCREAMING_SNAKE_CASE  (	cls:						str			,     *_SCREAMING_SNAKE_CASE:						Optional[int]			,     **_SCREAMING_SNAKE_CASE:						Dict)							->			Optional[Any]:

				"""simple docstring"""

				requires_backends(cls			,     ["torch", "transformers", "onnx"])