


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"""






    UpperCAmelCase__						:		int
    UpperCAmelCase__						:		Node | None






class    UpperCAmelCase__	:



    """simple docstring"""






    def __init__(      self ,       A_   )  ->	None:
         __UpperCamelCase   							=None
         for i in sorted(A_ ,       reverse=A_   ):
              __UpperCamelCase   							=Node(A_ ,       self.head   )






    def __iter__(      self   )  ->	Iterator[int]:
         __UpperCamelCase   							=self.head
         while node:
              yield node.data
              __UpperCamelCase   							=node.next_node






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






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

def 						_UpperCAmelCase    (      SCREAMING_SNAKE_CASE__      : SortedLinkedList      ,					SCREAMING_SNAKE_CASE__      : SortedLinkedList    ):
     return SortedLinkedList(list(SCREAMING_SNAKE_CASE__    ) + list(SCREAMING_SNAKE_CASE__    )    )


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_flax_available,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


_A			=						{'configuration_vit': ['VIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTConfig', 'ViTOnnxConfig']}

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _A			=						['ViTFeatureExtractor']
   _A			=						['ViTImageProcessor']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _A			=						[
       'VIT_PRETRAINED_MODEL_ARCHIVE_LIST',
       'ViTForImageClassification',
       'ViTForMaskedImageModeling',
       'ViTModel',
       'ViTPreTrainedModel',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _A			=						[
       'TFViTForImageClassification',
       'TFViTModel',
       'TFViTPreTrainedModel',
   ]

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _A			=						[
       'FlaxViTForImageClassification',
       'FlaxViTModel',
       'FlaxViTPreTrainedModel',
   ]

if TYPE_CHECKING:
   from .configuration_vit import VIT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTConfig, ViTOnnxConfig

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .feature_extraction_vit import ViTFeatureExtractor
      from .image_processing_vit import ViTImageProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_vit import (
          VIT_PRETRAINED_MODEL_ARCHIVE_LIST,
          ViTForImageClassification,
          ViTForMaskedImageModeling,
          ViTModel,
          ViTPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_vit import TFViTForImageClassification, TFViTModel, TFViTPreTrainedModel

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_vit import FlaxViTForImageClassification, FlaxViTModel, FlaxViTPreTrainedModel


else:
   import sys

   _A			=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





