



'''simple docstring'''




import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING


UpperCamelCase__       :	Tuple    = logging.get_logger(__name__)






class 						_UpperCamelCase  (							lowerCamelCase__    ):


			'''simple docstring'''

			_A      :		str			    =		'''upernet'''

			def __init__(							self     : Dict							,     lowerCAmelCase__     : Optional[Any]=None							,     lowerCAmelCase__     : Any=5_1_2							,     lowerCAmelCase__     : Optional[Any]=0.02							,     lowerCAmelCase__     : List[str]=[1, 2, 3, 6]							,     lowerCAmelCase__     : int=True							,     lowerCAmelCase__     : str=0.4							,     lowerCAmelCase__     : Optional[Any]=3_8_4							,     lowerCAmelCase__     : int=2_5_6							,     lowerCAmelCase__     : Union[str, Any]=1							,     lowerCAmelCase__     : Optional[int]=False							,     lowerCAmelCase__     : Optional[Any]=2_5_5							,     **lowerCAmelCase__     : Any							,     ):





					"""simple docstring"""






					super().__init__(**lowerCAmelCase__						)

					if backbone_config is None:
							logger.info("""`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."""						)
							__SCREAMING_SNAKE_CASE       :		str           =		CONFIG_MAPPING["""resnet"""](out_features=["""stage1""", """stage2""", """stage3""", """stage4"""]						)
					elif isinstance(lowerCAmelCase__							,     lowerCAmelCase__						):
							__SCREAMING_SNAKE_CASE       :		Union[str, Any]           =		backbone_config.get("""model_type"""						)
							__SCREAMING_SNAKE_CASE       :		Any           =		CONFIG_MAPPING[backbone_model_type]
							__SCREAMING_SNAKE_CASE       :		Optional[Any]           =		config_class.from_dict(lowerCAmelCase__						)

					__SCREAMING_SNAKE_CASE       :		int           =		backbone_config
					__SCREAMING_SNAKE_CASE       :		int           =		hidden_size
					__SCREAMING_SNAKE_CASE       :		Union[str, Any]           =		initializer_range
					__SCREAMING_SNAKE_CASE       :		Optional[int]           =		pool_scales
					__SCREAMING_SNAKE_CASE       :		Any           =		use_auxiliary_head
					__SCREAMING_SNAKE_CASE       :		Tuple           =		auxiliary_loss_weight
					__SCREAMING_SNAKE_CASE       :		str           =		auxiliary_in_channels
					__SCREAMING_SNAKE_CASE       :		Optional[Any]           =		auxiliary_channels
					__SCREAMING_SNAKE_CASE       :		Optional[int]           =		auxiliary_num_convs
					__SCREAMING_SNAKE_CASE       :		Any           =		auxiliary_concat_input
					__SCREAMING_SNAKE_CASE       :		int           =		loss_ignore_index



			def UpperCamelCase__					(							self     : List[str]						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		str           =		copy.deepcopy(self.__dict__						)
					__SCREAMING_SNAKE_CASE       :		int           =		self.backbone_config.to_dict()
					__SCREAMING_SNAKE_CASE       :		Optional[int]           =		self.__class__.model_type
					return output




'''simple docstring'''




def 				lowerCAmelCase_   (	_lowerCamelCase:   list					):
		if any(not isinstance(_lowerCamelCase       ,      _lowerCamelCase					) or x < 0 for x in sequence					):
				raise TypeError("""Sequence must be list of non-negative integers"""					)
		for _ in range(len(_lowerCamelCase					)					):
				for i, (rod_upper, rod_lower) in enumerate(zip(_lowerCamelCase       ,      sequence[1:]					)					):
						if rod_upper > rod_lower:
								sequence[i] -= rod_upper - rod_lower
								sequence[i + 1] += rod_upper - rod_lower
		return sequence


if __name__ == "__main__":
						assert bead_sort([5, 4, 3, 2, 1]) == [1, 2, 3, 4, 5]
						assert bead_sort([7, 9, 4, 3, 5]) == [3, 4, 5, 7, 9]