"""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,
)


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

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

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

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						SCREAMING_SNAKE_CASE						=    [
						    '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:
						SCREAMING_SNAKE_CASE						=    [
						    '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

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




"""simple docstring"""







from __future__ import annotations

import random
from collections.abc import Iterable
from typing import Any, Generic, TypeVar

SCREAMING_SNAKE_CASE						=    TypeVar('T', bound=bool)



class 			_lowerCamelCase      (Generic[T]  ):







				def __init__(			self     :							Any      ,       lowerCamelCase_     :							T    ):

					"""simple docstring"""






					_lowercase			:     T      					=				value
					_lowercase			:     RandomizedHeapNode[T] | None      					=				None
					_lowercase			:     RandomizedHeapNode[T] | None      					=				None







				@property
				def 				__UpperCAmelCase       (			self     :							int    ):

					"""simple docstring"""






					return self._value







				@staticmethod
				def 				__UpperCAmelCase       (			lowerCamelCase_     :							RandomizedHeapNode[T] | None      ,       lowerCamelCase_     :							RandomizedHeapNode[T] | None    ):

					"""simple docstring"""






					if not roota:
						return roota

					if not roota:
						return roota

					if roota.value > roota.value:
						_lowercase					,   _lowercase			:     List[Any]      					=				roota, roota

					if random.choice([True, False]    ):
						_lowercase					,   _lowercase			:     Optional[int]      					=				roota.right, roota.left

					_lowercase			:     Tuple      					=				RandomizedHeapNode.merge(roota.left      ,       lowerCamelCase_    )

					return roota



class 			_lowerCamelCase      (Generic[T]  ):







				def __init__(			self     :							Optional[Any]      ,       lowerCamelCase_     :							Iterable[T] | None = ()    ):

					"""simple docstring"""






					_lowercase			:     RandomizedHeapNode[T] | None      					=				None

					if data:
						for item in data:
							self.insert(lowerCamelCase_    )







				def 				__UpperCAmelCase       (			self     :							Tuple      ,       lowerCamelCase_     :							T    ):

					"""simple docstring"""






					_lowercase			:     str      					=				RandomizedHeapNode.merge(self._root      ,       RandomizedHeapNode(lowerCamelCase_    )    )







				def 				__UpperCAmelCase       (			self     :							int    ):

					"""simple docstring"""






					_lowercase			:     Any      					=				self.top()

					if self._root is None:
						return None

					_lowercase			:     List[Any]      					=				RandomizedHeapNode.merge(self._root.left      ,       self._root.right    )

					return result







				def 				__UpperCAmelCase       (			self     :							List[Any]    ):

					"""simple docstring"""






					if not self._root:
						raise IndexError('Can\'t get top element for the empty heap.'    )
					return self._root.value







				def 				__UpperCAmelCase       (			self     :							Any    ):

					"""simple docstring"""






					_lowercase			:     List[Any]      					=				None







				def 				__UpperCAmelCase       (			self     :							Union[str, Any]    ):

					"""simple docstring"""






					_lowercase			:     List[Any]      					=				[]
					while self:
						result.append(self.pop()    )

					return result







				def __bool__(			self     :							List[str]    ):

					"""simple docstring"""






					return self._root is not None


if __name__ == "__main__":
						import doctest

						doctest.testmod()



