




'''simple docstring'''


from collections import deque



def  _SCREAMING_SNAKE_CASE     (      UpperCamelCase__    :					Any				):




     """simple docstring"""


     a_     :							Optional[int]     						=  len(UpperCamelCase__				)
     a_     :							List[str]     						=  deque()
     a_     :							str     						=  [False for _ in range(UpperCamelCase__				)]
     a_     :							Dict     						=  [-1 for _ in range(UpperCamelCase__				)]
     a_     :							Optional[Any]     						=  index_of[:]

     def strong_connect(UpperCamelCase__    :					Tuple ,    UpperCamelCase__    :					Any ,    UpperCamelCase__    :					str				):
          a_     :							Union[str, Any]     						=  index  # the number when this node is seen
          a_     :							Dict     						=  index  # lowest rank node reachable from here
          index += 1
          stack.append(UpperCamelCase__				)
          a_     :							Optional[Any]     						=  True

          for w in g[v]:
               if index_of[w] == -1:
                    a_     :							Dict     						=  strong_connect(UpperCamelCase__ ,    UpperCamelCase__ ,    UpperCamelCase__				)
                    a_     :							Tuple     						=  (
                        lowlink_of[w] if lowlink_of[w] < lowlink_of[v] else lowlink_of[v]
                    )
               elif on_stack[w]:
                    a_     :							List[str]     						=  (
                        lowlink_of[w] if lowlink_of[w] < lowlink_of[v] else lowlink_of[v]
                    )

          if lowlink_of[v] == index_of[v]:
               a_     :							Optional[int]     						=  []
               a_     :							Union[str, Any]     						=  stack.pop()
               a_     :							Tuple     						=  False
               component.append(UpperCamelCase__				)
               while w != v:
                    a_     :							List[str]     						=  stack.pop()
                    a_     :							Union[str, Any]     						=  False
                    component.append(UpperCamelCase__				)
               components.append(UpperCamelCase__				)
          return index

     a_     :							List[str]     						=  []
     for v in range(UpperCamelCase__				):
          if index_of[v] == -1:
               strong_connect(UpperCamelCase__ ,    0 ,    UpperCamelCase__				)

     return components



def  _SCREAMING_SNAKE_CASE     (      UpperCamelCase__    :					List[Any] ,    UpperCamelCase__    :					Any				):




     """simple docstring"""


     a_     :							Optional[int]     						=  [[] for _ in range(UpperCamelCase__				)]
     for u, v in edges:
          g[u].append(UpperCamelCase__				)
     return g


if __name__ == "__main__":
 # Test
 lowerCAmelCase_      :  Union[str, Any]				     =  7
 lowerCAmelCase_      :  Optional[int]				     =  [0, 0, 1, 2, 3, 3, 4, 4, 6]
 lowerCAmelCase_      :  List[Any]				     =  [1, 3, 2, 0, 1, 4, 5, 6, 5]
 lowerCAmelCase_      :  Union[str, Any]				     =  [(u, v) for u, v in zip(source, target)]
 lowerCAmelCase_      :  Optional[Any]				     =  create_graph(n_vertices, edges)

 assert [[5], [6], [4], [3, 2, 1, 0]] == tarjan(g)






'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


lowerCAmelCase_      :  Optional[Any]				     =  {
    'configuration_mobilevit': ['MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MobileViTConfig', 'MobileViTOnnxConfig'],
}

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_      :  int				     =  ['MobileViTFeatureExtractor']
 lowerCAmelCase_      :  int				     =  ['MobileViTImageProcessor']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_      :  str				     =  [
     'MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
     'MobileViTForImageClassification',
     'MobileViTForSemanticSegmentation',
     'MobileViTModel',
     'MobileViTPreTrainedModel',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_      :  Optional[Any]				     =  [
     'TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
     'TFMobileViTForImageClassification',
     'TFMobileViTForSemanticSegmentation',
     'TFMobileViTModel',
     'TFMobileViTPreTrainedModel',
 ]

if TYPE_CHECKING:
 from .configuration_mobilevit import MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, MobileViTConfig, MobileViTOnnxConfig

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_mobilevit import MobileViTFeatureExtractor
  from .image_processing_mobilevit import MobileViTImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_mobilevit import (
      MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
      MobileViTForImageClassification,
      MobileViTForSemanticSegmentation,
      MobileViTModel,
      MobileViTPreTrainedModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_mobilevit import (
      TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFMobileViTForImageClassification,
      TFMobileViTForSemanticSegmentation,
      TFMobileViTModel,
      TFMobileViTPreTrainedModel,
  )


else:
 import sys

 lowerCAmelCase_      :  List[Any]				     =  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
