"""simple docstring"""




from __future__ import annotations

import math




def        lowerCAmelCase_			(					__A,  __A							)					->    Any:







      '''simple docstring'''


      UpperCAmelCase__								=  u
      for i in range(1,  __a							):
            UpperCAmelCase__								=  temp * (u - i)
      return temp




def        lowerCAmelCase_			(					)					->    Tuple:







      '''simple docstring'''


      UpperCAmelCase__								=  int(input("enter the numbers of values: "							)							)
      UpperCAmelCase__								=  []
      for _ in range(__a							):
            y.append([]							)
      for i in range(__a							):
            for j in range(__a							):
                  y[i].append(__a							)
                  UpperCAmelCase__								=  0

      print("enter the values of parameters in a list: "							)
      UpperCAmelCase__								=  list(map(__a,  input().split()							)							)

      print("enter the values of corresponding parameters: "							)
      for i in range(__a							):
            UpperCAmelCase__								=  float(input()							)

      UpperCAmelCase__								=  int(input("enter the value to interpolate: "							)							)
      UpperCAmelCase__								=  (value - x[0]) / (x[1] - x[0])

      # for calculating forward difference table

      for i in range(1,  __a							):
            for j in range(n - i							):
                  UpperCAmelCase__								=  y[j + 1][i - 1] - y[j][i - 1]

      UpperCAmelCase__								=  y[0][0]
      for i in range(1,  __a							):
            summ += (ucal(__a,  __a							) * y[0][i]) / math.factorial(__a							)

      print(f"""the value at {value} is {summ}"""							)


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 					A							(    UpperCAmelCase_					):
   __UpperCAmelCase			:			List[Any]              =      'facebook/bart-large-mnli'
   __UpperCAmelCase			:			Optional[Any]              =      (
       '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			:			Optional[int]              =      'text_classifier'
   __UpperCAmelCase			:			int              =      AutoTokenizer
   __UpperCAmelCase			:			Dict              =      AutoModelForSequenceClassification

   __UpperCAmelCase			:			int              =      ['text', ['text']]
   __UpperCAmelCase			:			Optional[int]              =      ['text']


   def       lowercase_				(self					:						List[Any]		)						->    List[str]:
         """simple docstring"""



         super().setup()
         UpperCAmelCase__								=  self.model.config
         UpperCAmelCase__								=  -1
         for idx, label in config.idalabel.items():
               if label.lower().startswith("entail"		):
                     UpperCAmelCase__								=  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       lowercase_				(self					:						Union[str, Any]	,  __UpperCAmelCase					:						Dict	,  __UpperCAmelCase					:						int		)						->    Optional[int]:
         """simple docstring"""



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





   def       lowercase_				(self					:						Dict	,  __UpperCAmelCase					:						Tuple		)						->    int:
         """simple docstring"""



         UpperCAmelCase__								=  outputs.logits
         UpperCAmelCase__								=  torch.argmax(logits[:, 2]		).item()
         return self._labels[label_id]



