
"""simple docstring"""


from __future__ import annotations

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

A_    							=					(3, 9, -11, 0, 7, 5, 1, -1)
A_    							=					(4, 6, 2, 0, 8, 10, 3, -2)




@dataclass
class  __lowerCamelCase  :
				a__:      int
				a__:      Node | None




class  __lowerCamelCase  :




				def __init__(				self							,						UpperCAmelCase   ):
							lowerCamelCase_					=  None
							for i in sorted(UpperCAmelCase							,						reverse=UpperCAmelCase   ):
										lowerCamelCase_					=  Node(UpperCAmelCase							,						self.head   )




				def __iter__(				self   ):
							lowerCamelCase_					=  self.head
							while node:
										yield node.data
										lowerCamelCase_					=  node.next_node




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





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






def  lowercase						(	lowerCAmelCase__	,lowerCAmelCase__						):
			return SortedLinkedList(list(lowerCAmelCase__						) + list(lowerCAmelCase__						)						)


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						A_    							=					SortedLinkedList
						print(merge_lists(SSL(test_data_odd), SSL(test_data_even)))






"""simple docstring"""


from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase													={
    "configuration_informer": [
        "INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "InformerConfig",
    ],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase													=[
      "INFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
      "InformerForPrediction",
      "InformerModel",
      "InformerPreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_informer import INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, InformerConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_informer import (
        INFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        InformerForPrediction,
        InformerModel,
        InformerPreTrainedModel,
    )

else:
  import sys

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




