





import itertools
import math




def    __UpperCAmelCase(      lowercase_      ):

       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




def    __UpperCAmelCase(      ):
       _lowerCamelCase							:     List[Any]	=		2
       while True:
              if is_prime(lowercase_      ):
                     yield num
              num += 1




def    __UpperCAmelCase(      lowercase_ = 1_00_01      ):
       return next(itertools.islice(prime_generator() ,    nth - 1 ,    lowercase_      )      )


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






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_lowerCamelCase			       =      {'configuration_opt': ['OPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'OPTConfig']}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _lowerCamelCase			       =      [
           'OPT_PRETRAINED_MODEL_ARCHIVE_LIST',
           'OPTForCausalLM',
           'OPTModel',
           'OPTPreTrainedModel',
           'OPTForSequenceClassification',
           'OPTForQuestionAnswering',
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _lowerCamelCase			       =      ['TFOPTForCausalLM', 'TFOPTModel', 'TFOPTPreTrainedModel']

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _lowerCamelCase			       =      [
           'FlaxOPTForCausalLM',
           'FlaxOPTModel',
           'FlaxOPTPreTrainedModel',
       ]


if TYPE_CHECKING:
       from .configuration_opt import OPT_PRETRAINED_CONFIG_ARCHIVE_MAP, OPTConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_opt import (
                  OPT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  OPTForCausalLM,
                  OPTForQuestionAnswering,
                  OPTForSequenceClassification,
                  OPTModel,
                  OPTPreTrainedModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_opt import TFOPTForCausalLM, TFOPTModel, TFOPTPreTrainedModel

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flax_opt import FlaxOPTForCausalLM, FlaxOPTModel, FlaxOPTPreTrainedModel

else:
       import sys

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

