



# 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  lowerCamelCase__    (							lowerCamelCase__):




		'''simple docstring'''



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

		snake_case_			=["""text""", ["""text"""]]
		snake_case_			=["""text"""]



		def 	lowerCAmelCase__   (self				)  ->    List[str]:

						"""simple docstring"""






						super().setup()
						lowerCAmelCase__  :       List[str]				=  self.model.config
						lowerCAmelCase__  :       List[Any]				=  -1
						for idx, label in config.idalabel.items():
										if label.lower().startswith('''entail'''				):
														lowerCAmelCase__  :       List[Any]				=  int(__lowerCamelCase				)
						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	,__lowerCamelCase	,__lowerCamelCase				)  ->    List[str]:

						"""simple docstring"""






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



		def 	lowerCAmelCase__   (self	,__lowerCamelCase				)  ->    Tuple:

						"""simple docstring"""






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






from __future__ import annotations






def 			lowerCAmelCase__	(					lowerCamelCase_	:	list[int]):





				'''simple docstring'''

				return len(set(lowerCamelCase_)) == len(lowerCamelCase_)


if __name__ == "__main__":
							import doctest

							doctest.testmod()

