






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

__UpperCamelCase   :						str							=  [[1, 4], [2, 4], [3], [], [], [4], [2, 7], [3], []]

__UpperCamelCase   :						List[Any]							=  [0 for x in range(len(graph))]
__UpperCamelCase   :						Any							=  []
def        a_	( _A ,				_A					)     ->     List[Any]:







				"""simple docstring"""
				snake_case__													=       1
				while stack:
								snake_case__													=       stack.pop()
								print(_A ,				clothes[current_clothing]					)
								order += 1
def        a_	( _A ,				_A ,				_A					)     ->     List[Any]:







				"""simple docstring"""
				snake_case__													=       1
				for v in graph[u]:
								if not visited[v]:
												depth_first_search(_A ,				_A ,				_A					)

				stack.append(_A					)
def        a_	( _A ,				_A					)     ->     Any:







				"""simple docstring"""
				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_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__UpperCamelCase   :						int							=  {
    """configuration_openai""": ["""OPENAI_GPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """OpenAIGPTConfig"""],
    """tokenization_openai""": ["""OpenAIGPTTokenizer"""],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase   :						Optional[Any]							=  ["""OpenAIGPTTokenizerFast"""]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase   :						List[str]							=  [
							    """OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """OpenAIGPTDoubleHeadsModel""",
							    """OpenAIGPTForSequenceClassification""",
							    """OpenAIGPTLMHeadModel""",
							    """OpenAIGPTModel""",
							    """OpenAIGPTPreTrainedModel""",
							    """load_tf_weights_in_openai_gpt""",
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase   :						Dict							=  [
							    """TF_OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """TFOpenAIGPTDoubleHeadsModel""",
							    """TFOpenAIGPTForSequenceClassification""",
							    """TFOpenAIGPTLMHeadModel""",
							    """TFOpenAIGPTMainLayer""",
							    """TFOpenAIGPTModel""",
							    """TFOpenAIGPTPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_openai import OPENAI_GPT_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenAIGPTConfig
							from .tokenization_openai import OpenAIGPTTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_openai_fast import OpenAIGPTTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_openai import (
														    OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    OpenAIGPTDoubleHeadsModel,
														    OpenAIGPTForSequenceClassification,
														    OpenAIGPTLMHeadModel,
														    OpenAIGPTModel,
														    OpenAIGPTPreTrainedModel,
														    load_tf_weights_in_openai_gpt,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_openai import (
														    TF_OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFOpenAIGPTDoubleHeadsModel,
														    TFOpenAIGPTForSequenceClassification,
														    TFOpenAIGPTLMHeadModel,
														    TFOpenAIGPTMainLayer,
														    TFOpenAIGPTModel,
														    TFOpenAIGPTPreTrainedModel,
														)

else:
							import sys

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




