






from __future__ import annotations

from collections.abc import Iterable
from dataclasses import dataclass
from typing import Any


class _lowerCAmelCase	:
						SCREAMING_SNAKE_CASE_:				List[Any]   				=							('_front', '_back', '_len')


						@dataclass
						class _lowerCAmelCase	:
												SCREAMING_SNAKE_CASE_:				int   				=							None
												SCREAMING_SNAKE_CASE_:				Optional[Any]   				=							None
												SCREAMING_SNAKE_CASE_:				Optional[Any]   				=							None







						class _lowerCAmelCase	:
												SCREAMING_SNAKE_CASE_:				List[Any]   				=							('_cur',)







												def __init__(						self      ,							lowerCAmelCase_       )		->       List[Any]:
																_SCREAMING_SNAKE_CASE      :		Union[str, Any]							=						cur







												def __iter__(						self       )		->       Optional[Any]:
																return self







												def  A			(						self       )		->       Tuple:

																if self._cur is None:
																				# finished iterating
																				raise StopIteration
																_SCREAMING_SNAKE_CASE      :		str							=						self._cur.val
																_SCREAMING_SNAKE_CASE      :		str							=						self._cur.next_node

																return val







						def __init__(						self      ,							lowerCAmelCase_ = None       )		->       Union[str, Any]:
										_SCREAMING_SNAKE_CASE      :		Any							=						None
										_SCREAMING_SNAKE_CASE      :		Any							=						None
										_SCREAMING_SNAKE_CASE      :		int							=						0

										if iterable is not None:
														# append every value to the deque
														for val in iterable:
																		self.append(_lowerCamelCase       )







						def  A			(						self      ,							lowerCAmelCase_       )		->       str:
										_SCREAMING_SNAKE_CASE      :		Optional[Any]							=						self._Node(_lowerCamelCase      ,							_lowerCamelCase      ,							_lowerCamelCase       )
										if self.is_empty():
														# front = back
														_SCREAMING_SNAKE_CASE      :		List[str]							=						node
														_SCREAMING_SNAKE_CASE      :		Dict							=						1
										else:
														# connect nodes
														_SCREAMING_SNAKE_CASE      :		str							=						node
														_SCREAMING_SNAKE_CASE      :		List[Any]							=						self._back
														_SCREAMING_SNAKE_CASE      :		List[Any]							=						node  # assign new back to the new node

														self._len += 1

														# make sure there were no errors
														assert not self.is_empty(), "Error on appending value."







						def  A			(						self      ,							lowerCAmelCase_       )		->       Union[str, Any]:
										_SCREAMING_SNAKE_CASE      :		List[str]							=						self._Node(_lowerCamelCase      ,							_lowerCamelCase      ,							_lowerCamelCase       )
										if self.is_empty():
														# front = back
														_SCREAMING_SNAKE_CASE      :		Optional[int]							=						node
														_SCREAMING_SNAKE_CASE      :		int							=						1
										else:
														# connect nodes
														_SCREAMING_SNAKE_CASE      :		Union[str, Any]							=						self._front
														_SCREAMING_SNAKE_CASE      :		Optional[int]							=						node
														_SCREAMING_SNAKE_CASE      :		List[Any]							=						node  # assign new front to the new node

														self._len += 1

														# make sure there were no errors
														assert not self.is_empty(), "Error on appending value."







						def  A			(						self      ,							lowerCAmelCase_       )		->       List[str]:

										for val in iterable:
														self.append(_lowerCamelCase       )







						def  A			(						self      ,							lowerCAmelCase_       )		->       Dict:

										for val in iterable:
														self.appendleft(_lowerCamelCase       )







						def  A			(						self       )		->       Union[str, Any]:
										assert not self.is_empty(), "Deque is empty."

										_SCREAMING_SNAKE_CASE      :		Optional[Any]							=						self._back
										_SCREAMING_SNAKE_CASE      :		Any							=						self._back.prev_node  # set new back
										# drop the last node - python will deallocate memory automatically
										_SCREAMING_SNAKE_CASE      :		Optional[Any]							=						None

										self._len -= 1

										return topop.val







						def  A			(						self       )		->       Any:
										assert not self.is_empty(), "Deque is empty."

										_SCREAMING_SNAKE_CASE      :		Optional[Any]							=						self._front
										_SCREAMING_SNAKE_CASE      :		str							=						self._front.next_node  # set new front and drop the first node
										_SCREAMING_SNAKE_CASE      :		Optional[int]							=						None

										self._len -= 1

										return topop.val







						def  A			(						self       )		->       Optional[int]:
										return self._front is None







						def __len__(						self       )		->       Optional[int]:
										return self._len







						def __eq__(						self      ,							lowerCAmelCase_       )		->       Tuple:

										if not isinstance(_lowerCamelCase      ,							_lowerCamelCase       ):
														return NotImplemented

										_SCREAMING_SNAKE_CASE      :		str							=						self._front
										_SCREAMING_SNAKE_CASE      :		str							=						other._front

										# if the length of the dequeues are not the same, they are not equal
										if len(self       ) != len(_lowerCamelCase       ):
														return False

										while me is not None and oth is not None:
														# compare every value
														if me.val != oth.val:
																		return False
														_SCREAMING_SNAKE_CASE      :		List[Any]							=						me.next_node
														_SCREAMING_SNAKE_CASE      :		int							=						oth.next_node

										return True







						def __iter__(						self       )		->       Union[str, Any]:
										return Deque._Iterator(self._front       )







						def __repr__(						self       )		->       Optional[Any]:
										_SCREAMING_SNAKE_CASE      :		List[str]							=						[]
										_SCREAMING_SNAKE_CASE      :		Union[str, Any]							=						self._front
										while aux is not None:
														# append the values in a list to display
														values_list.append(aux.val       )
														_SCREAMING_SNAKE_CASE      :		str							=						aux.next_node

										return F"""[{", ".join(repr(_lowerCamelCase       ) for val in values_list       )}]"""


if __name__ == "__main__":
			import doctest

			doctest.testmod()









"""simple docstring"""
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,
)


lowerCAmelCase__							= {
    'configuration_big_bird': ['BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BigBirdConfig', 'BigBirdOnnxConfig'],
}

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

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

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase__							= [
			    'BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'BigBirdForCausalLM',
			    'BigBirdForMaskedLM',
			    'BigBirdForMultipleChoice',
			    'BigBirdForPreTraining',
			    'BigBirdForQuestionAnswering',
			    'BigBirdForSequenceClassification',
			    'BigBirdForTokenClassification',
			    'BigBirdLayer',
			    'BigBirdModel',
			    'BigBirdPreTrainedModel',
			    'load_tf_weights_in_big_bird',
			]

try:
			if not is_flax_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase__							= [
			    'FlaxBigBirdForCausalLM',
			    'FlaxBigBirdForMaskedLM',
			    'FlaxBigBirdForMultipleChoice',
			    'FlaxBigBirdForPreTraining',
			    'FlaxBigBirdForQuestionAnswering',
			    'FlaxBigBirdForSequenceClassification',
			    'FlaxBigBirdForTokenClassification',
			    'FlaxBigBirdModel',
			    'FlaxBigBirdPreTrainedModel',
			]

if TYPE_CHECKING:
			from .configuration_big_bird import BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP, BigBirdConfig, BigBirdOnnxConfig

			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_big_bird import BigBirdTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_big_bird_fast import BigBirdTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_big_bird import (
						    BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST,
						    BigBirdForCausalLM,
						    BigBirdForMaskedLM,
						    BigBirdForMultipleChoice,
						    BigBirdForPreTraining,
						    BigBirdForQuestionAnswering,
						    BigBirdForSequenceClassification,
						    BigBirdForTokenClassification,
						    BigBirdLayer,
						    BigBirdModel,
						    BigBirdPreTrainedModel,
						    load_tf_weights_in_big_bird,
						)

			try:
						if not is_flax_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_flax_big_bird import (
						    FlaxBigBirdForCausalLM,
						    FlaxBigBirdForMaskedLM,
						    FlaxBigBirdForMultipleChoice,
						    FlaxBigBirdForPreTraining,
						    FlaxBigBirdForQuestionAnswering,
						    FlaxBigBirdForSequenceClassification,
						    FlaxBigBirdForTokenClassification,
						    FlaxBigBirdModel,
						    FlaxBigBirdPreTrainedModel,
						)

else:
			import sys

			lowerCAmelCase__							= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

