"""simple docstring"""





def      lowerCamelCase_(__SCREAMING_SNAKE_CASE  )->    Union[str, Any]:  # noqa: E741
							_SCREAMING_SNAKE_CASE		:						Optional[int]			  =    len(_snake_case  )
							_SCREAMING_SNAKE_CASE		:						Optional[int]			  =    0
							_SCREAMING_SNAKE_CASE		:						Optional[int]			  =    [0] * n
							_SCREAMING_SNAKE_CASE		:						List[Any]			  =    [False] * n
							_SCREAMING_SNAKE_CASE		:						Optional[int]			  =    [False] * n

							def dfs(__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE  ):
														if parent == root:
																					out_edge_count += 1
														_SCREAMING_SNAKE_CASE		:						Tuple			  =    True
														_SCREAMING_SNAKE_CASE		:						int			  =    at

														for to in l[at]:
																					if to == parent:
																												pass
																					elif not visited[to]:
																												_SCREAMING_SNAKE_CASE		:						int			  =    dfs(_snake_case     ,	_snake_case     ,	_snake_case     ,	_snake_case  )
																												_SCREAMING_SNAKE_CASE		:						Any			  =    min(low[at]     ,	low[to]  )

																												# AP found via bridge
																												if at < low[to]:
																																			_SCREAMING_SNAKE_CASE		:						List[str]			  =    True
																												# AP found via cycle
																												if at == low[to]:
																																			_SCREAMING_SNAKE_CASE		:						Optional[int]			  =    True
																					else:
																												_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    min(low[at]     ,	_snake_case  )
														return out_edge_count

							for i in range(_snake_case  ):
														if not visited[i]:
																					_SCREAMING_SNAKE_CASE		:						Tuple			  =    0
																					_SCREAMING_SNAKE_CASE		:						Tuple			  =    dfs(_snake_case     ,	_snake_case     ,	-1     ,	_snake_case  )
																					_SCREAMING_SNAKE_CASE		:						Optional[Any]			  =    out_edge_count > 1

							for x in range(len(_snake_case  )  ):
														if is_art[x] is True:
																					print(_snake_case  )


# Adjacency list of graph
lowerCAmelCase_     =	{
    0: [1, 2],
    1: [0, 2],
    2: [0, 1, 3, 5],
    3: [2, 4],
    4: [3],
    5: [2, 6, 8],
    6: [5, 7],
    7: [6, 8],
    8: [5, 7],
}


compute_ap(data)



"""simple docstring"""





# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import torch

from ..models.auto import AutoModelForSequenceClassification, AutoTokenizer
from .base import PipelineTool




class  _snake_case		(    __snake_case ):







				"""simple docstring"""






				a			=						"facebook/bart-large-mnli"
				a			=						(
				    "This is a tool that classifies an English text using provided labels. It takes two inputs: `text`, which "
				    "should be the text to classify, and `labels`, which should be the list of labels to use for classification. "
				    "It returns the most likely label in the list of provided `labels` for the input text."
				)
				a			=						"text_classifier"
				a			=						AutoTokenizer
				a			=						AutoModelForSequenceClassification

				a			=						["text", ["text"]]
				a			=						["text"]





				def 		_lowerCAmelCase		(      self							:							int):



											"""simple docstring"""







											super().setup()
											_SCREAMING_SNAKE_CASE		:						Any			  =    self.model.config
											_SCREAMING_SNAKE_CASE		:						Any			  =    -1
											for idx, label in config.idalabel.items():
																		if label.lower().startswith("""entail"""):
																									_SCREAMING_SNAKE_CASE		:						List[Any]			  =    int(_A)
											if self.entailment_id == -1:
																		raise ValueError("""Could not determine the entailment ID from the model config, please pass it at init.""")





				def 		_lowerCAmelCase		(      self							:							Optional[Any]      ,    _A							:							Tuple      ,    _A							:							List[str]):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						Optional[Any]			  =    labels
											return self.pre_processor(
											    [text] * len(_A)      ,    [f"""This example is {label}""" for label in labels]      ,    return_tensors="""pt"""      ,    padding="""max_length"""      ,    )





				def 		_lowerCAmelCase		(      self							:							Tuple      ,    _A							:							Optional[Any]):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						str			  =    outputs.logits
											_SCREAMING_SNAKE_CASE		:						List[Any]			  =    torch.argmax(logits[:, 2]).item()
											return self._labels[label_id]


