
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,
)


lowercase  : Optional[Any]						   =							{
    """configuration_xlm_roberta""": [
        """XLM_ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """XLMRobertaConfig""",
        """XLMRobertaOnnxConfig""",
    ],
}

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

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase  : Optional[int]						   =							["""XLMRobertaTokenizerFast"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase  : Tuple						   =							[
      """XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """XLMRobertaForCausalLM""",
      """XLMRobertaForMaskedLM""",
      """XLMRobertaForMultipleChoice""",
      """XLMRobertaForQuestionAnswering""",
      """XLMRobertaForSequenceClassification""",
      """XLMRobertaForTokenClassification""",
      """XLMRobertaModel""",
      """XLMRobertaPreTrainedModel""",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase  : str						   =							[
      """TF_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """TFXLMRobertaForCausalLM""",
      """TFXLMRobertaForMaskedLM""",
      """TFXLMRobertaForMultipleChoice""",
      """TFXLMRobertaForQuestionAnswering""",
      """TFXLMRobertaForSequenceClassification""",
      """TFXLMRobertaForTokenClassification""",
      """TFXLMRobertaModel""",
      """TFXLMRobertaPreTrainedModel""",
  ]

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase  : int						   =							[
      """FLAX_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """FlaxXLMRobertaForMaskedLM""",
      """FlaxXLMRobertaForCausalLM""",
      """FlaxXLMRobertaForMultipleChoice""",
      """FlaxXLMRobertaForQuestionAnswering""",
      """FlaxXLMRobertaForSequenceClassification""",
      """FlaxXLMRobertaForTokenClassification""",
      """FlaxXLMRobertaModel""",
      """FlaxXLMRobertaPreTrainedModel""",
  ]

if TYPE_CHECKING:
  from .configuration_xlm_roberta import (
      XLM_ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP,
      XLMRobertaConfig,
      XLMRobertaOnnxConfig,
  )

  try:
    if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_xlm_roberta import XLMRobertaTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_xlm_roberta_fast import XLMRobertaTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_xlm_roberta import (
        XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
        XLMRobertaForCausalLM,
        XLMRobertaForMaskedLM,
        XLMRobertaForMultipleChoice,
        XLMRobertaForQuestionAnswering,
        XLMRobertaForSequenceClassification,
        XLMRobertaForTokenClassification,
        XLMRobertaModel,
        XLMRobertaPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_xlm_roberta import (
        TF_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFXLMRobertaForCausalLM,
        TFXLMRobertaForMaskedLM,
        TFXLMRobertaForMultipleChoice,
        TFXLMRobertaForQuestionAnswering,
        TFXLMRobertaForSequenceClassification,
        TFXLMRobertaForTokenClassification,
        TFXLMRobertaModel,
        TFXLMRobertaPreTrainedModel,
    )

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_xlm_roberta import (
        FLAX_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
        FlaxXLMRobertaForCausalLM,
        FlaxXLMRobertaForMaskedLM,
        FlaxXLMRobertaForMultipleChoice,
        FlaxXLMRobertaForQuestionAnswering,
        FlaxXLMRobertaForSequenceClassification,
        FlaxXLMRobertaForTokenClassification,
        FlaxXLMRobertaModel,
        FlaxXLMRobertaPreTrainedModel,
    )

else:
  import sys

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


class __snake_case		:
    def __init__(  self		,snake_case		,snake_case=None		,snake_case=None				):



           '''simple docstring'''







           lowercase							:					Tuple	     =				data
           lowercase							:					List[Any]	     =				previous
           lowercase							:					List[str]	     =				next_node
    def __str__(  self				):



           '''simple docstring'''







           return f"{self.data}"
    def 				_SCREAMING_SNAKE_CASE	(  self				):



           '''simple docstring'''







           return self.data
    def 				_SCREAMING_SNAKE_CASE	(  self				):



           '''simple docstring'''







           return self.next
    def 				_SCREAMING_SNAKE_CASE	(  self				):



           '''simple docstring'''







           return self.previous






class __snake_case		:
    def __init__(  self		,snake_case				):



           '''simple docstring'''







           lowercase							:					Optional[int]	     =				head
    def __iter__(  self				):



           '''simple docstring'''







           return self
    def 				_SCREAMING_SNAKE_CASE	(  self				):



           '''simple docstring'''







           if not self.current:
                  raise StopIteration
           else:
                  lowercase							:					Union[str, Any]	     =				self.current.get_data()
                  lowercase							:					Optional[Any]	     =				self.current.get_next()
                  return value






class __snake_case		:
    def __init__(  self				):



           '''simple docstring'''







           lowercase							:					str	     =				None  # First node in list
           lowercase							:					str	     =				None  # Last node in list
    def __str__(  self				):



           '''simple docstring'''







           lowercase							:					int	     =				self.head
           lowercase							:					str	     =				[]
           while current is not None:
                  nodes.append(current.get_data()				)
                  lowercase							:					Dict	     =				current.get_next()
           return " ".join(str(snake_case				) for node in nodes				)
    def __contains__(  self		,snake_case				):



           '''simple docstring'''







           lowercase							:					Dict	     =				self.head
           while current:
                  if current.get_data() == value:
                         return True
                  lowercase							:					Any	     =				current.get_next()
           return False
    def __iter__(  self				):



           '''simple docstring'''







           return LinkedListIterator(self.head				)
    def 				_SCREAMING_SNAKE_CASE	(  self				):



           '''simple docstring'''







           if self.head:
                  return self.head.get_data()
           return None
    def 				_SCREAMING_SNAKE_CASE	(  self				):



           '''simple docstring'''







           if self.tail:
                  return self.tail.get_data()
           return None
    def 				_SCREAMING_SNAKE_CASE	(  self		,snake_case				):



           '''simple docstring'''







           if self.head is None:
                  lowercase							:					Any	     =				node
                  lowercase							:					Dict	     =				node
           else:
                  self.insert_before_node(self.head		,snake_case				)
    def 				_SCREAMING_SNAKE_CASE	(  self		,snake_case				):



           '''simple docstring'''







           if self.head is None:
                  self.set_head(snake_case				)
           else:
                  self.insert_after_node(self.tail		,snake_case				)
    def 				_SCREAMING_SNAKE_CASE	(  self		,snake_case				):



           '''simple docstring'''







           lowercase							:					Dict	     =				Node(snake_case				)
           if self.head is None:
                  self.set_head(snake_case				)
           else:
                  self.set_tail(snake_case				)
    def 				_SCREAMING_SNAKE_CASE	(  self		,snake_case		,snake_case				):



           '''simple docstring'''







           lowercase							:					Optional[int]	     =				node
           lowercase							:					Optional[int]	     =				node.previous

           if node.get_previous() is None:
                  lowercase							:					Optional[int]	     =				node_to_insert
           else:
                  lowercase							:					Optional[int]	     =				node_to_insert

           lowercase							:					List[Any]	     =				node_to_insert
    def 				_SCREAMING_SNAKE_CASE	(  self		,snake_case		,snake_case				):



           '''simple docstring'''







           lowercase							:					Dict	     =				node
           lowercase							:					List[str]	     =				node.next

           if node.get_next() is None:
                  lowercase							:					Union[str, Any]	     =				node_to_insert
           else:
                  lowercase							:					List[str]	     =				node_to_insert

           lowercase							:					Dict	     =				node_to_insert
    def 				_SCREAMING_SNAKE_CASE	(  self		,snake_case		,snake_case				):



           '''simple docstring'''







           lowercase							:					List[Any]	     =				1
           lowercase							:					List[str]	     =				Node(snake_case				)
           lowercase							:					Any	     =				self.head
           while node:
                  if current_position == position:
                         self.insert_before_node(snake_case		,snake_case				)
                         return
                  current_position += 1
                  lowercase							:					List[Any]	     =				node.next
           self.insert_after_node(self.tail		,snake_case				)
    def 				_SCREAMING_SNAKE_CASE	(  self		,snake_case				):



           '''simple docstring'''







           lowercase							:					Optional[int]	     =				self.head
           while node:
                  if node.get_data() == item:
                         return node
                  lowercase							:					Any	     =				node.get_next()
           raise Exception("""Node not found"""				)
    def 				_SCREAMING_SNAKE_CASE	(  self		,snake_case				):



           '''simple docstring'''







           if (node := self.get_node(snake_case				)) is not None:
                  if node == self.head:
                         lowercase							:					Optional[Any]	     =				self.head.get_next()

                  if node == self.tail:
                         lowercase							:					List[str]	     =				self.tail.get_previous()

                  self.remove_node_pointers(snake_case				)
    @staticmethod
    def 				_SCREAMING_SNAKE_CASE	(  snake_case				):



           '''simple docstring'''







           if node.get_next():
                  lowercase							:					Optional[int]	     =				node.previous

           if node.get_previous():
                  lowercase							:					Union[str, Any]	     =				node.next

           lowercase							:					Union[str, Any]	     =				None
           lowercase							:					Optional[Any]	     =				None
    def 				_SCREAMING_SNAKE_CASE	(  self				):



           '''simple docstring'''







           return self.head is None







def 						_snake_case(  )			->   None:
       pass


if __name__ == "__main__":
  import doctest

  doctest.testmod()
