


"""simple docstring"""






from __future__ import annotations

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

lowercase  		=			TypeVar("""T""", bound=bool)


class 			SCREAMING_SNAKE_CASE_  (   Generic[T]):




							'''simple docstring'''





							def __init__(						self	,					lowerCamelCase__)   ->	None:







								'''simple docstring'''




								snake_case__  :						T		=      value
								snake_case__  :						SkewNode[T] | None		=      None
								snake_case__  :						SkewNode[T] | None		=      None




							@property
							def        UpperCAmelCase (						self)   ->	T:







								'''simple docstring'''




								return self._value







							@staticmethod
							def        UpperCAmelCase (						lowerCamelCase__	,					lowerCamelCase__)   ->	SkewNode[T] | None:







								'''simple docstring'''




								if not roota:
									return roota

								if not roota:
									return roota

								if roota.value > roota.value:
									snake_case__,					snake_case__  :						Any		=      roota, roota

								snake_case__  :						Optional[int]		=      roota
								snake_case__  :						int		=      roota.right
								snake_case__  :						Union[str, Any]		=      roota.left
								snake_case__  :						List[str]		=      SkewNode.merge(lowerCamelCase__	,					lowerCamelCase__)

								return result


class 			SCREAMING_SNAKE_CASE_  (   Generic[T]):




							'''simple docstring'''





							def __init__(						self	,					lowerCamelCase__ = ())   ->	None:







								'''simple docstring'''




								snake_case__  :						SkewNode[T] | None		=      None
								if data:
									for item in data:
										self.insert(lowerCamelCase__)




							def __bool__(						self)   ->	bool:







								'''simple docstring'''




								return self._root is not None




							def __iter__(						self)   ->	Iterator[T]:







								'''simple docstring'''




								snake_case__  :						list[Any]		=      []
								while self:
									result.append(self.pop())

								# Pushing items back to the heap not to clear it.
								for item in result:
									self.insert(lowerCamelCase__)

								return iter(lowerCamelCase__)




							def        UpperCAmelCase (						self	,					lowerCamelCase__)   ->	None:







								'''simple docstring'''




								snake_case__  :						List[str]		=      SkewNode.merge(self._root	,					SkewNode(lowerCamelCase__))




							def        UpperCAmelCase (						self)   ->	T | None:







								'''simple docstring'''




								snake_case__  :						Tuple		=      self.top()
								snake_case__  :						List[Any]		=      (
								    SkewNode.merge(self._root.left	,					self._root.right) if self._root else None
								)

								return result




							def        UpperCAmelCase (						self)   ->	T:







								'''simple docstring'''




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







							def        UpperCAmelCase (						self)   ->	None:







								'''simple docstring'''




								snake_case__  :						Any		=      None


if __name__ == "__main__":
					import doctest

					doctest.testmod()











from typing import TYPE_CHECKING

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


UpperCAmelCase_    ={
    """configuration_splinter""": ["""SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SplinterConfig"""],
    """tokenization_splinter""": ["""SplinterTokenizer"""],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		UpperCAmelCase_    =["""SplinterTokenizerFast"""]

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		UpperCAmelCase_    =[
		    """SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST""",
		    """SplinterForQuestionAnswering""",
		    """SplinterForPreTraining""",
		    """SplinterLayer""",
		    """SplinterModel""",
		    """SplinterPreTrainedModel""",
		]


if TYPE_CHECKING:
		from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
		from .tokenization_splinter import SplinterTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_splinter_fast import SplinterTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_splinter import (
				    SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    SplinterForPreTraining,
				    SplinterForQuestionAnswering,
				    SplinterLayer,
				    SplinterModel,
				    SplinterPreTrainedModel,
				)


else:
		import sys

		UpperCAmelCase_    =_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



