






a    =       {
    0: 'underwear',
    1: 'pants',
    2: 'belt',
    3: 'suit',
    4: 'shoe',
    5: 'socks',
    6: 'shirt',
    7: 'tie',
    8: 'watch',
}

a    =       [[1, 4], [2, 4], [3], [], [], [4], [2, 7], [3], []]

a    =       [0 for x in range(len(graph))]
a    =       []
def       a__						(  A		,				A					):
   lowercase__						:	Union[str, Any]         = 1
   while stack:
      lowercase__						:	List[str]         = stack.pop()
      print(A		,				clothes[current_clothing]					)
      order += 1
def       a__						(  A		,				A		,				A					):
   lowercase__						:	Any         = 1
   for v in graph[u]:
      if not visited[v]:
         depth_first_search(A		,				A		,				A					)

   stack.append(A					)
def       a__						(  A		,				A					):
   for v in range(len(A					)					):
      if not visited[v]:
         depth_first_search(A		,				A		,				A					)


if __name__ == "__main__":
 topological_sort(graph, visited)
 print(stack)
 print_stack(stack, clothes)










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a    =       {'configuration_nat': ['NAT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NatConfig']}


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a    =       [
     'NAT_PRETRAINED_MODEL_ARCHIVE_LIST',
     'NatForImageClassification',
     'NatModel',
     'NatPreTrainedModel',
     'NatBackbone',
 ]

if TYPE_CHECKING:
 from .configuration_nat import NAT_PRETRAINED_CONFIG_ARCHIVE_MAP, NatConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_nat import (
      NAT_PRETRAINED_MODEL_ARCHIVE_LIST,
      NatBackbone,
      NatForImageClassification,
      NatModel,
      NatPreTrainedModel,
  )

else:
 import sys

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


