

class     snake_case_			:


							"""simple docstring"""





							def __init__( self							):
												__lowerCAmelCase					=							{}  # Mapping from char to TrieNode
												__lowerCAmelCase					=							False




							def        A__  ( self					,						_A							):
												for word in words:
																	self.insert(_A							)




							def        A__  ( self					,						_A							):
												__lowerCAmelCase					=							self
												for char in word:
																	if char not in curr.nodes:
																						__lowerCAmelCase					=							TrieNode()
																	__lowerCAmelCase					=							curr.nodes[char]
												__lowerCAmelCase					=							True




							def        A__  ( self					,						_A							):
												__lowerCAmelCase					=							self
												for char in word:
																	if char not in curr.nodes:
																						return False
																	__lowerCAmelCase					=							curr.nodes[char]
												return curr.is_leaf




							def        A__  ( self					,						_A							):

												def _delete(_A					,						_A					,						_A							) -> bool:
																	if index == len(_A							):
																						# If word does not exist
																						if not curr.is_leaf:
																											return False
																						__lowerCAmelCase					=							False
																						return len(curr.nodes							) == 0
																	__lowerCAmelCase					=							word[index]
																	__lowerCAmelCase					=							curr.nodes.get(_A							)
																	# If char not in current trie node
																	if not char_node:
																						return False
																	# Flag to check if node can be deleted
																	__lowerCAmelCase					=							_delete(_A					,						_A					,						index + 1							)
																	if delete_curr:
																						del curr.nodes[char]
																						return len(curr.nodes							) == 0
																	return delete_curr

												_delete(self					,						_A					,						0							)


def        __lowercase    (  UpperCAmelCase__		,					UpperCAmelCase__      ):

					"""simple docstring"""






					if node.is_leaf:
										print(UpperCAmelCase__		,					end=' '      )

					for key, value in node.nodes.items():
										print_words(UpperCAmelCase__		,					word + key      )


def        __lowercase    (  ):

					"""simple docstring"""






					__lowerCAmelCase					=							'banana bananas bandana band apple all beast'.split()
					__lowerCAmelCase					=							TrieNode()
					root.insert_many(UpperCAmelCase__      )
					# print_words(root, "")
					assert all(root.find(UpperCAmelCase__      ) for word in words      )
					assert root.find('banana'      )
					assert not root.find('bandanas'      )
					assert not root.find('apps'      )
					assert root.find('apple'      )
					assert root.find('all'      )
					root.delete('all'      )
					assert not root.find('all'      )
					root.delete('banana'      )
					assert not root.find('banana'      )
					assert root.find('bananas'      )
					return True


def        __lowercase    (  UpperCAmelCase__		,					UpperCAmelCase__      ):

					"""simple docstring"""






					print(str(UpperCAmelCase__      )		,					'works!' if passes else 'doesn\'t work :('      )


def        __lowercase    (  ):

					"""simple docstring"""






					assert test_trie()


def        __lowercase    (  ):

					"""simple docstring"""






					print_results('Testing trie functionality'		,					test_trie()      )


if __name__ == "__main__":
		main()









# 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_			(				_a							):


							"""simple docstring"""





							__UpperCAmelCase       ="""facebook/bart-large-mnli"""
							__UpperCAmelCase       =(
							    """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."""
							)
							__UpperCAmelCase       ="""text_classifier"""
							__UpperCAmelCase       =AutoTokenizer
							__UpperCAmelCase       =AutoModelForSequenceClassification

							__UpperCAmelCase       =["""text""", ["""text"""]]
							__UpperCAmelCase       =["""text"""]




							def        A__  ( self							):
												super().setup()
												__lowerCAmelCase					=							self.model.config
												__lowerCAmelCase					=							-1
												for idx, label in config.idalabel.items():
																	if label.lower().startswith('entail'							):
																						__lowerCAmelCase					=							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        A__  ( self					,						_A					,						_A							):
												__lowerCAmelCase					=							labels
												return self.pre_processor(
												    [text] * len(_A							)					,						[F"""This example is {label}""" for label in labels]					,						return_tensors='pt'					,						padding='max_length'					,						)




							def        A__  ( self					,						_A							):
												__lowerCAmelCase					=							outputs.logits
												__lowerCAmelCase					=							torch.argmax(logits[:, 2]							).item()
												return self._labels[label_id]






