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 			UpperCAmelCase__    :



  """simple docstring"""






  lowerCAmelCase__		:	int
  lowerCAmelCase__		:	Node | None






class 			UpperCAmelCase__    :



  """simple docstring"""






  def __init__(				self:			Union[str, Any]				,				__lowerCAmelCase:			Iterable[int]   ) -> None:




    '''simple docstring'''




    __UpperCAmelCase						    =       None
    for i in sorted(__lowerCAmelCase				,				reverse=__lowerCAmelCase   ):
      __UpperCAmelCase						    =       Node(__lowerCAmelCase				,				self.head   )






  def __iter__(				self:			List[str]   ) -> Iterator[int]:




    '''simple docstring'''




    __UpperCAmelCase						    =       self.head
    while node:
      yield node.data
      __UpperCAmelCase						    =       node.next_node






  def __len__(				self:			Optional[Any]   ) -> int:




    '''simple docstring'''




    return sum(1 for _ in self   )






  def __str__(				self:			Any   ) -> str:




    '''simple docstring'''




    return " -> ".join([str(__lowerCAmelCase   ) for node in self]   )






def       __lowerCAmelCase      (						A_   : SortedLinkedList						,	A_   : SortedLinkedList					)    ->  SortedLinkedList:
  return SortedLinkedList(list(A_					) + list(A_					)					)


if __name__ == "__main__":
   import doctest

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




from typing import TYPE_CHECKING

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


a_							=      {
    """configuration_altclip""": [
        """ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """AltCLIPConfig""",
        """AltCLIPTextConfig""",
        """AltCLIPVisionConfig""",
    ],
    """processing_altclip""": ["""AltCLIPProcessor"""],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a_							=      [
           """ALTCLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """AltCLIPPreTrainedModel""",
           """AltCLIPModel""",
           """AltCLIPTextModel""",
           """AltCLIPVisionModel""",
       ]


if TYPE_CHECKING:
       from .configuration_altclip import (
           ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
           AltCLIPConfig,
           AltCLIPTextConfig,
           AltCLIPVisionConfig,
       )
       from .processing_altclip import AltCLIPProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_altclip import (
                  ALTCLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
                  AltCLIPModel,
                  AltCLIPPreTrainedModel,
                  AltCLIPTextModel,
                  AltCLIPVisionModel,
              )


else:
       import sys

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



