
'''simple docstring'''






import copy

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


UpperCAmelCase_       :   List[Any]   =       logging.get_logger(__name__)

class  UpperCAmelCase__						(       A ):
    lowerCAmelCase_				    =		'upernet'



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

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

          _lowerCamelCase				:   List[Any]								=   backbone_config
          _lowerCamelCase				:   Any								=   hidden_size
          _lowerCamelCase				:   Optional[Any]								=   initializer_range
          _lowerCamelCase				:   Dict								=   pool_scales
          _lowerCamelCase				:   Any								=   use_auxiliary_head
          _lowerCamelCase				:   Any								=   auxiliary_loss_weight
          _lowerCamelCase				:   str								=   auxiliary_in_channels
          _lowerCamelCase				:   str								=   auxiliary_channels
          _lowerCamelCase				:   Optional[int]								=   auxiliary_num_convs
          _lowerCamelCase				:   Dict								=   auxiliary_concat_input
          _lowerCamelCase				:   List[Any]								=   loss_ignore_index



    def   lowerCamelCase_  (	self      :       Optional[int]     ):
          _lowerCamelCase				:   Union[str, Any]								=   copy.deepcopy(self.__dict__     )
          _lowerCamelCase				:   List[Any]								=   self.backbone_config.to_dict()
          _lowerCamelCase				:   Optional[int]								=   self.__class__.model_type
          return output

'''simple docstring'''






from __future__ import annotations

from collections.abc import Iterable, Iterator
from dataclasses import dataclass

UpperCAmelCase_       :   str   =       (3, 9, -11, 0, 7, 5, 1, -1)
UpperCAmelCase_       :   int   =       (4, 6, 2, 0, 8, 10, 3, -2)

@dataclass
class  UpperCAmelCase__						:
    lowerCAmelCase_				    =		42
    lowerCAmelCase_				    =		42


class  UpperCAmelCase__						:



    def __init__(	self      :       Optional[int],__A      :       Iterable[int]     ):
          _lowerCamelCase				:   Node | None								=   None
          for i in sorted(__A,reverse=__A     ):
                _lowerCamelCase				:   Dict								=   Node(__A,self.head     )



    def __iter__(	self      :       str     ):
          _lowerCamelCase				:   Dict								=   self.head
          while node:
                yield node.data
                _lowerCamelCase				:   Optional[Any]								=   node.next_node



    def __len__(	self      :       str     ):
          return sum(1 for _ in self     )



    def __str__(	self      :       str     ):
          return " -> ".join([str(__A     ) for node in self]     )







def 		A_       (	_lowerCAmelCase   :    SortedLinkedList				,	_lowerCAmelCase   :    SortedLinkedList							):



      """simple docstring"""




      return SortedLinkedList(list(_lowerCAmelCase							) + list(_lowerCAmelCase							)							)


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 UpperCAmelCase_       :   List[str]   =       SortedLinkedList
 print(merge_lists(SSL(test_data_odd), SSL(test_data_even)))