"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


_UpperCamelCase         =		{
    'configuration_segformer': ['SEGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SegformerConfig', 'SegformerOnnxConfig']
}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCamelCase         =		['SegformerFeatureExtractor']
					_UpperCamelCase         =		['SegformerImageProcessor']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCamelCase         =		[
					    'SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'SegformerDecodeHead',
					    'SegformerForImageClassification',
					    'SegformerForSemanticSegmentation',
					    'SegformerLayer',
					    'SegformerModel',
					    'SegformerPreTrainedModel',
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCamelCase         =		[
					    'TF_SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'TFSegformerDecodeHead',
					    'TFSegformerForImageClassification',
					    'TFSegformerForSemanticSegmentation',
					    'TFSegformerModel',
					    'TFSegformerPreTrainedModel',
					]


if TYPE_CHECKING:
					from .configuration_segformer import SEGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, SegformerConfig, SegformerOnnxConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_segformer import SegformerFeatureExtractor
										from .image_processing_segformer import SegformerImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_segformer import (
										    SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    SegformerDecodeHead,
										    SegformerForImageClassification,
										    SegformerForSemanticSegmentation,
										    SegformerLayer,
										    SegformerModel,
										    SegformerPreTrainedModel,
										)
					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_segformer import (
										    TF_SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFSegformerDecodeHead,
										    TFSegformerForImageClassification,
										    TFSegformerForSemanticSegmentation,
										    TFSegformerModel,
										    TFSegformerPreTrainedModel,
										)

else:
					import sys

					_UpperCamelCase         =		_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

_UpperCamelCase         =		TypeVar("T", bound=bool)
class 	__UpperCAmelCase						(Generic[T]    ):







			'''simple docstring'''





			def __init__( self      ,			snake_case_       ):







										'''simple docstring'''


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





			@property
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										return self._value





			@staticmethod
			def 		lowerCamelCase				( snake_case_      ,			snake_case_       ):







										'''simple docstring'''


										if not roota:
																	return roota

										if not roota:
																	return roota

										if roota.value > roota.value:
																	A__							,       A__					:    Union[str, Any]														= roota, roota

										if random.choice([True, False]       ):
																	A__							,       A__					:    Any														= roota.right, roota.left

										A__					:    Dict														= RandomizedHeapNode.merge(roota.left      ,			snake_case_       )

										return roota





class 	__UpperCAmelCase						(Generic[T]    ):







			'''simple docstring'''





			def __init__( self      ,			snake_case_ = ()       ):







										'''simple docstring'''


										A__					:    RandomizedHeapNode[T] | None														= None

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





			def 		lowerCamelCase				( self      ,			snake_case_       ):







										'''simple docstring'''


										A__					:    Dict														= RandomizedHeapNode.merge(self._root      ,			RandomizedHeapNode(snake_case_       )       )





			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										A__					:    List[str]														= self.top()

										if self._root is None:
																	return None

										A__					:    str														= RandomizedHeapNode.merge(self._root.left      ,			self._root.right       )

										return result





			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


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





			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										A__					:    List[Any]														= None





			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										A__					:    int														= []
										while self:
																	result.append(self.pop()       )

										return result





			def __bool__( self       ):







										'''simple docstring'''


										return self._root is not None


if __name__ == "__main__":
				import doctest

				doctest.testmod()





