






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

UpperCamelCase__						:      Any								=					[[1, 4], [2, 4], [3], [], [], [4], [2, 7], [3], []]

UpperCamelCase__						:      str								=					[0 for x in range(len(graph))]
UpperCamelCase__						:      Union[str, Any]								=					[]





def   SCREAMING_SNAKE_CASE__						(   snake_case_,  snake_case_  )   ->  Optional[int]:


	"""simple docstring"""



	a		=			1
	while stack:
		a		=			stack.pop()
		print(snake_case_,  clothes[current_clothing]  )
		order += 1





def   SCREAMING_SNAKE_CASE__						(   snake_case_,  snake_case_,  snake_case_  )   ->  Union[str, Any]:


	"""simple docstring"""



	a		=			1
	for v in graph[u]:
		if not visited[v]:
			depth_first_search(snake_case_,  snake_case_,  snake_case_  )

	stack.append(snake_case_  )





def   SCREAMING_SNAKE_CASE__						(   snake_case_,  snake_case_  )   ->  str:


	"""simple docstring"""



	for v in range(len(snake_case_  )  ):
		if not visited[v]:
			depth_first_search(snake_case_,  snake_case_,  snake_case_  )


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













from typing import TYPE_CHECKING

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


UpperCamelCase__						:      Tuple								=					{
    """configuration_nystromformer""": ["""NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """NystromformerConfig"""],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCamelCase__						:      Any								=					[
				    """NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """NystromformerForMaskedLM""",
				    """NystromformerForMultipleChoice""",
				    """NystromformerForQuestionAnswering""",
				    """NystromformerForSequenceClassification""",
				    """NystromformerForTokenClassification""",
				    """NystromformerLayer""",
				    """NystromformerModel""",
				    """NystromformerPreTrainedModel""",
				]


if TYPE_CHECKING:
				from .configuration_nystromformer import NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, NystromformerConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_nystromformer import (
								    NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
								    NystromformerForMaskedLM,
								    NystromformerForMultipleChoice,
								    NystromformerForQuestionAnswering,
								    NystromformerForSequenceClassification,
								    NystromformerForTokenClassification,
								    NystromformerLayer,
								    NystromformerModel,
								    NystromformerPreTrainedModel,
								)


else:
				import sys

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





