



class 				lowerCAmelCase__	:




					class 				lowerCAmelCase__	:
										__A  :     Dict     =    '_prev', '_data', '_next'







										def __init__(							self   :  Union[str, Any]      ,		_A   :  Any      ,		_A   :  str      ,		_A   :  str):
																A__						:				List[Any]         =			link_p
																A__						:				List[str]         =			element
																A__						:				int         =			link_n







										def 			_lowercase      (							self   :  List[str]):
																return (
																    F' Prev -> {self._prev is not None}, Next -> {self._next is not None}'
																)







					def __init__(							self   :  List[str]):
											A__						:				List[Any]         =			self._Node(lowercase__      ,		lowercase__      ,		lowercase__)
											A__						:				Optional[Any]         =			self._Node(lowercase__      ,		lowercase__      ,		lowercase__)
											A__						:				List[str]         =			self._trailer
											A__						:				Optional[Any]         =			self._header
											A__						:				Dict         =			0







					def __len__(							self   :  int):
											return self._size







					def 			_lowercase      (							self   :  List[str]):
											return self.__len__() == 0







					def 			_lowercase      (							self   :  str      ,		_A   :  Any      ,		_A   :  List[Any]      ,		_A   :  int):
											# Create new_node by setting it's prev.link -> header
											# setting it's next.link -> trailer
											A__						:				Union[str, Any]         =			self._Node(lowercase__      ,		lowercase__      ,		lowercase__)
											A__						:				Any         =			new_node
											A__						:				List[Any]         =			new_node
											self._size += 1
											return self







					def 			_lowercase      (							self   :  int      ,		_A   :  Optional[int]):
											A__						:				List[str]         =			node._prev
											A__						:				Optional[Any]         =			node._next

											A__						:				int         =			successor
											A__						:				List[str]         =			predecessor
											self._size -= 1
											A__						:				Dict         =			node._data
											A__						:				Tuple         =			None
											del node
											return temp




class 				lowerCAmelCase__	(						_DoublyLinkedBase    ):







					def 			_lowercase      (							self   :  int):
											if self.is_empty():
																	raise Exception("List is empty")
											return self._header._next._data







					def 			_lowercase      (							self   :  List[Any]):
											if self.is_empty():
																	raise Exception("List is empty")
											return self._trailer._prev._data







					def 			_lowercase      (							self   :  List[Any]      ,		_A   :  Union[str, Any]):
											return self._insert(self._header      ,		lowercase__      ,		self._header._next)







					def 			_lowercase      (							self   :  Tuple      ,		_A   :  Union[str, Any]):
											return self._insert(self._trailer._prev      ,		lowercase__      ,		self._trailer)







					def 			_lowercase      (							self   :  Any):
											if self.is_empty():
																	raise IndexError("remove_first from empty list")
											return self._delete(self._header._next)







					def 			_lowercase      (							self   :  Any):
											if self.is_empty():
																	raise IndexError("remove_first from empty list")
											return self._delete(self._trailer._prev)







from typing import TYPE_CHECKING

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


snake_case_   :	Dict							      ={'''configuration_t5''': ['''T5_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''T5Config''', '''T5OnnxConfig''']}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_   :	Optional[Any]							      =['''T5Tokenizer''']

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_   :	Any							      =['''T5TokenizerFast''']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_   :	Optional[int]							      =[
					    '''T5_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''T5EncoderModel''',
					    '''T5ForConditionalGeneration''',
					    '''T5Model''',
					    '''T5PreTrainedModel''',
					    '''load_tf_weights_in_t5''',
					    '''T5ForQuestionAnswering''',
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_   :	Optional[Any]							      =[
					    '''TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''TFT5EncoderModel''',
					    '''TFT5ForConditionalGeneration''',
					    '''TFT5Model''',
					    '''TFT5PreTrainedModel''',
					]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_   :	Tuple							      =[
					    '''FlaxT5EncoderModel''',
					    '''FlaxT5ForConditionalGeneration''',
					    '''FlaxT5Model''',
					    '''FlaxT5PreTrainedModel''',
					]


if TYPE_CHECKING:
					from .configuration_ta import T5_PRETRAINED_CONFIG_ARCHIVE_MAP, TaConfig, TaOnnxConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_ta import TaTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_ta_fast import TaTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_ta import (
										    T5_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TaEncoderModel,
										    TaForConditionalGeneration,
										    TaForQuestionAnswering,
										    TaModel,
										    TaPreTrainedModel,
										    load_tf_weights_in_ta,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_ta import (
										    TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFTaEncoderModel,
										    TFTaForConditionalGeneration,
										    TFTaModel,
										    TFTaPreTrainedModel,
										)

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_ta import (
										    FlaxTaEncoderModel,
										    FlaxTaForConditionalGeneration,
										    FlaxTaModel,
										    FlaxTaPreTrainedModel,
										)


else:
					import sys

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

