



'''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 (__lowercase   ):
       lowerCAmelCase__  :List[str]						   =					"facebook/bart-large-mnli"
       lowerCAmelCase__  :Tuple						   =					(
           "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."
       )
       lowerCAmelCase__  :Optional[int]						   =					"text_classifier"
       lowerCAmelCase__  :str						   =					AutoTokenizer
       lowerCAmelCase__  :Dict						   =					AutoModelForSequenceClassification

       lowerCAmelCase__  :List[str]						   =					["text", ["text"]]
       lowerCAmelCase__  :Union[str, Any]						   =					["text"]



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







       def 							_a      (				self     ,UpperCAmelCase_      )  ->							Optional[int]:
           lowercase__		       =						outputs.logits
           lowercase__		       =						torch.argmax(logits[:, 2]      ).item()
           return self._labels[label_id]









'''simple docstring'''





def        lowerCamelCase  (				_snake_case  :						int     ,_snake_case  :						int       ):





    '''simple docstring'''


    return x if y == 0 else greatest_common_divisor(_snake_case     ,x % y       )




def        lowerCamelCase  (				_snake_case  :						int     ,_snake_case  :						int       ):





    '''simple docstring'''


    return (x * y) // greatest_common_divisor(_snake_case     ,_snake_case       )




def        lowerCamelCase  (				_snake_case  :						int = 20       ):





    '''simple docstring'''


    lowercase__		       =						1
    for i in range(1     ,n + 1       ):
        lowercase__		       =						lcm(_snake_case     ,_snake_case       )
    return g


if __name__ == "__main__":
 print(f'''{solution() = }''')




