





import itertools
import math


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):







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


def     SCREAMING_SNAKE_CASE			(      ):
							_UpperCamelCase              =						2
							while True:
														if is_prime(lowerCAmelCase					):
																					yield num
														num += 1


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase = 10_001					):
							return next(itertools.islice(prime_generator()    ,       nth - 1    ,       lowerCAmelCase					)					)


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













import os
import sys
import unittest


lowercase    : Any    	=  os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))

import check_dummies  # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_backend, read_init  # noqa: E402


# Align TRANSFORMERS_PATH in check_dummies with the current path
lowercase    : int    	=  os.path.join(git_repo_path, """src""", """transformers""")

lowercase    : str    	=  """
{0} = None
"""

lowercase    : Union[str, Any]    	=  """
class {0}(metaclass=DummyObject):
    _backends = {1}

    def __init__(self, *args, **kwargs):
        requires_backends(self, {1})
"""


lowercase    : Optional[Any]    	=  """
def {0}(*args, **kwargs):
    requires_backends({0}, {1})
"""

class  __A(						unittest.TestCase ):

     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            _UpperCamelCase              =						find_backend('''    _import_structure["models.albert"].append("AlbertTokenizerFast")'''      )
            self.assertIsNone(A      )

            _UpperCamelCase              =						find_backend('''    if not is_tokenizers_available():'''      )
            self.assertEqual(A,       '''tokenizers'''      )

            _UpperCamelCase              =						find_backend('''    if not is_tensorflow_text_available():'''      )
            self.assertEqual(A,       '''tensorflow_text'''      )

            _UpperCamelCase              =						find_backend('''    if not (is_sentencepiece_available() and is_tokenizers_available()):'''      )
            self.assertEqual(A,       '''sentencepiece_and_tokenizers'''      )

            _UpperCamelCase              =						find_backend(
                '''    if not (is_sentencepiece_available() and is_tensorflow_text_available()):'''      )
            self.assertEqual(A,       '''sentencepiece_and_tensorflow_text'''      )

            _UpperCamelCase              =						find_backend(
                '''    if not (is_sentencepiece_available() and is_tokenizers_available() and is_vision_available()):'''      )
            self.assertEqual(A,       '''sentencepiece_and_tokenizers_and_vision'''      )

     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            _UpperCamelCase              =						read_init()
            # We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
            self.assertIn('''torch''',       A      )
            self.assertIn('''tensorflow_text''',       A      )
            self.assertIn('''sentencepiece_and_tokenizers''',       A      )

            # Likewise, we can't assert on the exact content of a key
            self.assertIn('''BertModel''',       objects['''torch''']      )
            self.assertIn('''TFBertModel''',       objects['''tf''']      )
            self.assertIn('''FlaxBertModel''',       objects['''flax''']      )
            self.assertIn('''BertModel''',       objects['''torch''']      )
            self.assertIn('''TFBertTokenizer''',       objects['''tensorflow_text''']      )
            self.assertIn('''convert_slow_tokenizer''',       objects['''sentencepiece_and_tokenizers''']      )

     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            _UpperCamelCase              =						create_dummy_object('''CONSTANT''',       '''\'torch\''''      )
            self.assertEqual(A,       '''\nCONSTANT = None\n'''      )

            _UpperCamelCase              =						create_dummy_object('''function''',       '''\'torch\''''      )
            self.assertEqual(
                A,       '''\ndef function(*args, **kwargs):\n    requires_backends(function, \'torch\')\n'''      )

            _UpperCamelCase              =						'''
class FakeClass(metaclass=DummyObject):
    _backends = \'torch\'

    def __init__(self, *args, **kwargs):
        requires_backends(self, \'torch\')
'''
            _UpperCamelCase              =						create_dummy_object('''FakeClass''',       '''\'torch\''''      )
            self.assertEqual(A,       A      )



     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            _UpperCamelCase              =						'''# This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends


CONSTANT = None


def function(*args, **kwargs):
    requires_backends(function, ["torch"])


class FakeClass(metaclass=DummyObject):
    _backends = ["torch"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch"])
'''
            _UpperCamelCase              =						create_dummy_files({'''torch''': ['''CONSTANT''', '''function''', '''FakeClass''']}      )
            self.assertEqual(dummy_files['''torch'''],       A      )






