
class 			UpperCamelCase__		:







	'''simple docstring'''





	def __init__(      self					,							UpperCamelCase__		):
					A__	:						List[Any]								=				data
					A__	:						Union[str, Any]								=				None
					A__	:						str								=				None





	def __str__(      self		):
					return F"{self.data}"







class 			UpperCamelCase__		:







	'''simple docstring'''





	def __init__(      self		):
					A__	:						str								=				None
					A__	:						List[str]								=				None





	def __iter__(      self		):
					A__	:						int								=				self.head
					while node:
									yield node.data
									A__	:						Dict								=				node.next





	def __str__(      self		):
					return "->".join([str(UpperCamelCase__		) for item in self]		)





	def __len__(      self		):
					return sum(1 for _ in self		)





	def 	__snake_case					(      self					,							UpperCamelCase__		):
					self.insert_at_nth(0					,							UpperCamelCase__		)





	def 	__snake_case					(      self					,							UpperCamelCase__		):
					self.insert_at_nth(len(self		)					,							UpperCamelCase__		)





	def 	__snake_case					(      self					,							UpperCamelCase__					,							UpperCamelCase__		):
					A__	:						int								=				len(self		)

					if not 0 <= index <= length:
									raise IndexError('''list index out of range'''		)
					A__	:						Union[str, Any]								=				Node(UpperCamelCase__		)
					if self.head is None:
									A__	:						Optional[Any]								=				new_node
					elif index == 0:
									A__	:						Union[str, Any]								=				new_node
									A__	:						Dict								=				self.head
									A__	:						List[str]								=				new_node
					elif index == length:
									A__	:						List[str]								=				new_node
									A__	:						Union[str, Any]								=				self.tail
									A__	:						List[Any]								=				new_node
					else:
									A__	:						List[str]								=				self.head
									for _ in range(0					,							UpperCamelCase__		):
													A__	:						List[Any]								=				temp.next
									A__	:						Tuple								=				new_node
									A__	:						int								=				temp.previous
									A__	:						int								=				temp
									A__	:						Any								=				new_node





	def 	__snake_case					(      self		):
					return self.delete_at_nth(0		)





	def 	__snake_case					(      self		):
					return self.delete_at_nth(len(self		) - 1		)





	def 	__snake_case					(      self					,							UpperCamelCase__		):
					A__	:						Dict								=				len(self		)

					if not 0 <= index <= length - 1:
									raise IndexError('''list index out of range'''		)
					A__	:						Union[str, Any]								=				self.head  # default first node
					if length == 1:
									A__	:						Tuple								=				None
					elif index == 0:
									A__	:						Optional[int]								=				self.head.next
									A__	:						Union[str, Any]								=				None
					elif index == length - 1:
									A__	:						str								=				self.tail
									A__	:						Dict								=				self.tail.previous
									A__	:						int								=				None
					else:
									A__	:						Tuple								=				self.head
									for _ in range(0					,							UpperCamelCase__		):
													A__	:						Optional[int]								=				temp.next
									A__	:						List[str]								=				temp
									A__	:						str								=				temp.previous
									A__	:						str								=				temp.next
					return delete_node.data





	def 	__snake_case					(      self					,							UpperCamelCase__		):
					A__	:						Union[str, Any]								=				self.head

					while current.data != data:  # Find the position to delete
									if current.next:
													A__	:						int								=				current.next
									else:  # We have reached the end an no value matches
													raise ValueError('''No data matching given value'''		)

					if current == self.head:
									self.delete_head()

					elif current == self.tail:
									self.delete_tail()

					else:  # Before: 1 <--> 2(current) <--> 3
									A__	:						Union[str, Any]								=				current.next  # 1 --> 3
									A__	:						Any								=				current.previous  # 1 <--> 3
					return data





	def 	__snake_case					(      self		):
					return len(self		) == 0




def 					SCREAMING_SNAKE_CASE  (   )			->							None:

				"""simple docstring"""







				A__	:						Dict								=				DoublyLinkedList()
				assert linked_list.is_empty() is True
				assert str(__UpperCamelCase							) == ""

				try:
								linked_list.delete_head()
								raise AssertionError  # This should not happen.
				except IndexError:
								assert True  # This should happen.

				try:
								linked_list.delete_tail()
								raise AssertionError  # This should not happen.
				except IndexError:
								assert True  # This should happen.

				for i in range(10							):
								assert len(__UpperCamelCase							) == i
								linked_list.insert_at_nth(__UpperCamelCase				,    i + 1							)
				assert str(__UpperCamelCase							) == "->".join(str(__UpperCamelCase							) for i in range(1				,    11							)							)

				linked_list.insert_at_head(0							)
				linked_list.insert_at_tail(11							)
				assert str(__UpperCamelCase							) == "->".join(str(__UpperCamelCase							) for i in range(0				,    12							)							)

				assert linked_list.delete_head() == 0
				assert linked_list.delete_at_nth(9							) == 10
				assert linked_list.delete_tail() == 11
				assert len(__UpperCamelCase							) == 9
				assert str(__UpperCamelCase							) == "->".join(str(__UpperCamelCase							) for i in range(1				,    10							)							)


if __name__ == "__main__":
					from doctest import testmod

					testmod()

from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE     :   Optional[Any]							 =      {
    'configuration_flaubert': ['FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FlaubertConfig', 'FlaubertOnnxConfig'],
    'tokenization_flaubert': ['FlaubertTokenizer'],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_SCREAMING_SNAKE_CASE     :   Tuple							 =      [
					    'FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'FlaubertForMultipleChoice',
					    'FlaubertForQuestionAnswering',
					    'FlaubertForQuestionAnsweringSimple',
					    'FlaubertForSequenceClassification',
					    'FlaubertForTokenClassification',
					    'FlaubertModel',
					    'FlaubertWithLMHeadModel',
					    'FlaubertPreTrainedModel',
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_SCREAMING_SNAKE_CASE     :   Dict							 =      [
					    'TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'TFFlaubertForMultipleChoice',
					    'TFFlaubertForQuestionAnsweringSimple',
					    'TFFlaubertForSequenceClassification',
					    'TFFlaubertForTokenClassification',
					    'TFFlaubertModel',
					    'TFFlaubertPreTrainedModel',
					    'TFFlaubertWithLMHeadModel',
					]


if TYPE_CHECKING:
					from .configuration_flaubert import FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, FlaubertConfig, FlaubertOnnxConfig
					from .tokenization_flaubert import FlaubertTokenizer

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flaubert import (
										    FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    FlaubertForMultipleChoice,
										    FlaubertForQuestionAnswering,
										    FlaubertForQuestionAnsweringSimple,
										    FlaubertForSequenceClassification,
										    FlaubertForTokenClassification,
										    FlaubertModel,
										    FlaubertPreTrainedModel,
										    FlaubertWithLMHeadModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_flaubert import (
										    TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFFlaubertForMultipleChoice,
										    TFFlaubertForQuestionAnsweringSimple,
										    TFFlaubertForSequenceClassification,
										    TFFlaubertForTokenClassification,
										    TFFlaubertModel,
										    TFFlaubertPreTrainedModel,
										    TFFlaubertWithLMHeadModel,
										)

else:
					import sys

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