




def SCREAMING_SNAKE_CASE    (	lowercase_						)       ->	str:



       """simple docstring"""

       A__							=   [0] * len(lowercase_						)
       A__							=   []
       A__							=   []
       A__							=   0

       for values in graph.values():
              for i in values:
                     indegree[i] += 1

       for i in range(len(lowercase_						)						):
              if indegree[i] == 0:
                     queue.append(lowercase_						)

       while queue:
              A__							=   queue.pop(0						)
              cnt += 1
              topo.append(lowercase_						)
              for x in graph[vertex]:
                     indegree[x] -= 1
                     if indegree[x] == 0:
                            queue.append(lowercase_						)

       if cnt != len(lowercase_						):
              print('''Cycle exists'''						)
       else:
              print(lowercase_						)


# Adjacency List of Graph
_lowerCamelCase     :		Optional[Any]								=       {0: [1, 2], 1: [3], 2: [3], 3: [4, 5], 4: [], 5: []}
topological_sort(graph)








from typing import TYPE_CHECKING

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


_lowerCamelCase     :		Union[str, Any]								=       {
    """configuration_swiftformer""": [
        """SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """SwiftFormerConfig""",
        """SwiftFormerOnnxConfig""",
    ]
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCamelCase     :		Union[str, Any]								=       [
      """SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """SwiftFormerForImageClassification""",
      """SwiftFormerModel""",
      """SwiftFormerPreTrainedModel""",
  ]

if TYPE_CHECKING:
  from .configuration_swiftformer import (
      SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
      SwiftFormerConfig,
      SwiftFormerOnnxConfig,
  )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_swiftformer import (
        SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        SwiftFormerForImageClassification,
        SwiftFormerModel,
        SwiftFormerPreTrainedModel,
    )

else:
  import sys

  _lowerCamelCase     :		str								=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


