


import torch

from ..models.auto import AutoModelForSequenceClassification, AutoTokenizer
from .base import PipelineTool




class    UpperCAmelCase					(       __a    ):
			lowercase						= "facebook/bart-large-mnli"
			lowercase						= (
			    "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."
			)
			lowercase						= "text_classifier"
			lowercase						= AutoTokenizer
			lowercase						= AutoModelForSequenceClassification

			lowercase						= ["text", ["text"]]
			lowercase						= ["text"]




			def   lowerCamelCase_					(						self							:		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(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							:		Dict       ,       __magic_name__							:		Union[str, Any]       ,       __magic_name__							:		Dict						):







						"""simple docstring"""







						UpperCamelCase         =					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							:		Tuple       ,       __magic_name__							:		int						):







						"""simple docstring"""







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



import math
import unittest






def 							_lowercase    (		SCREAMING_SNAKE_CASE_   :		int	):





			"""simple docstring"""




			assert isinstance(SCREAMING_SNAKE_CASE_       ,  SCREAMING_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(SCREAMING_SNAKE_CASE_	) + 1	)       ,  6	):
						if number % i == 0 or number % (i + 2) == 0:
									return False
			return True




class    UpperCAmelCase					(       unittest.TestCase    ):




			def   lowerCamelCase_					(						self							:		Any						):







						"""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(1_1						)						)
						self.assertTrue(is_prime(1_3						)						)
						self.assertTrue(is_prime(1_7						)						)
						self.assertTrue(is_prime(1_9						)						)
						self.assertTrue(is_prime(2_3						)						)
						self.assertTrue(is_prime(2_9						)						)





			def   lowerCamelCase_					(						self							:		Dict						):







						"""simple docstring"""







						with self.assertRaises(__magic_name__						):
									is_prime(-1_9						)
						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()




