





"""simple docstring"""



import math
import unittest







def 		__lowercase     (   snake_case_  :  int						)   ->bool:



    '''simple docstring'''







    assert isinstance(snake_case_				,snake_case_						) and (
        number >= 0
    ), "'number' must been an int and positive"

    if 1 < number < 4:
        # 2 and 3 are primes
        return True
    elif number < 2 or number % 2 == 0 or number % 3 == 0:
        # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
        return False

    # All primes number are in format of 6k +/- 1
    for i in range(5				,int(math.sqrt(snake_case_						) + 1						)				,6						):
        if number % i == 0 or number % (i + 2) == 0:
            return False
    return True






class 		__snake_case					(		unittest.TestCase     ):





 """simple docstring"""


 def 					UpperCamelCase__(    self  ):



     '''simple docstring'''




     self.assertTrue(is_prime(2  )  )
     self.assertTrue(is_prime(3  )  )
     self.assertTrue(is_prime(5  )  )
     self.assertTrue(is_prime(7  )  )
     self.assertTrue(is_prime(11  )  )
     self.assertTrue(is_prime(13  )  )
     self.assertTrue(is_prime(17  )  )
     self.assertTrue(is_prime(19  )  )
     self.assertTrue(is_prime(23  )  )
     self.assertTrue(is_prime(29  )  )







 def 					UpperCamelCase__(    self  ):



     '''simple docstring'''




     with self.assertRaises(__lowerCamelCase  ):
         is_prime(-19  )
     self.assertFalse(
         is_prime(0  )					,						'''Zero doesn\'t have any positive factors, primes must have exactly two.'''					,						)
     self.assertFalse(
         is_prime(1  )					,						'''One only has 1 positive factor, primes must have exactly two.'''					,						)
     self.assertFalse(is_prime(2 * 2  )  )
     self.assertFalse(is_prime(2 * 3  )  )
     self.assertFalse(is_prime(3 * 3  )  )
     self.assertFalse(is_prime(3 * 5  )  )
     self.assertFalse(is_prime(3 * 5 * 7  )  )


if __name__ == "__main__":
       unittest.main()











"""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					(		SCREAMING_SNAKE_CASE__     ):





 """simple docstring"""


 _lowerCamelCase        =     """facebook/bart-large-mnli"""
 _lowerCamelCase        =     (
     """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        =     """text_classifier"""
 _lowerCamelCase        =     AutoTokenizer
 _lowerCamelCase        =     AutoModelForSequenceClassification

 _lowerCamelCase        =     ["""text""", ["""text"""]]
 _lowerCamelCase        =     ["""text"""]

 def 					UpperCamelCase__(    self  ):



     '''simple docstring'''




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



     '''simple docstring'''




     __A    :						Union[str, 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 					UpperCamelCase__(    self					,						__lowerCamelCase  ):



     '''simple docstring'''




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




