
import math
import unittest

def 		UpperCamelCase						(   lowercase_ )		->						bool:


  '''simple docstring'''






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



class    _snake_case (						unittest.TestCase				):


 def   lowercase__  (       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   lowercase__  (       self):


   '''simple docstring'''




   with self.assertRaises(SCREAMING_SNAKE_CASE_):
     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'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available


__lowerCamelCase									=     {
    '''configuration_ernie''': ['''ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ErnieConfig''', '''ErnieOnnxConfig'''],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __lowerCamelCase									=     [
          '''ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''ErnieForCausalLM''',
          '''ErnieForMaskedLM''',
          '''ErnieForMultipleChoice''',
          '''ErnieForNextSentencePrediction''',
          '''ErnieForPreTraining''',
          '''ErnieForQuestionAnswering''',
          '''ErnieForSequenceClassification''',
          '''ErnieForTokenClassification''',
          '''ErnieModel''',
          '''ErniePreTrainedModel''',
      ]

if TYPE_CHECKING:
      from .configuration_ernie import ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieConfig, ErnieOnnxConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_ernie import (
                ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST,
                ErnieForCausalLM,
                ErnieForMaskedLM,
                ErnieForMultipleChoice,
                ErnieForNextSentencePrediction,
                ErnieForPreTraining,
                ErnieForQuestionAnswering,
                ErnieForSequenceClassification,
                ErnieForTokenClassification,
                ErnieModel,
                ErniePreTrainedModel,
            )

else:
      import sys

      __lowerCamelCase									=     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
