'''simple docstring'''

import math
from collections.abc import Iterator
from itertools import takewhile
def 			__UpperCamelCase       (   UpperCAmelCase     ):

 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(UpperCAmelCase     ) + 1     )		,     6     ):
  if number % i == 0 or number % (i + 2) == 0:
   return False
 return True
def 			__UpperCamelCase       (   ):
 lowercase__				:    Dict  =					2
 while True:
  if is_prime(UpperCAmelCase     ):
   yield num
  num += 1
def 			__UpperCamelCase       (   UpperCAmelCase = 200_0000     ):
 return sum(takewhile(lambda UpperCAmelCase     : x < n		,     prime_generator()     )     )


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


'''simple docstring'''

from typing import TYPE_CHECKING

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


__a: Dict          =   {
    """configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
    """tokenization_ctrl""": ["""CTRLTokenizer"""],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __a: int          =   [
      """CTRL_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """CTRLForSequenceClassification""",
      """CTRLLMHeadModel""",
      """CTRLModel""",
      """CTRLPreTrainedModel""",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __a: int          =   [
      """TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """TFCTRLForSequenceClassification""",
      """TFCTRLLMHeadModel""",
      """TFCTRLModel""",
      """TFCTRLPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_ctrl import CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP, CTRLConfig
  from .tokenization_ctrl import CTRLTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_ctrl import (
        CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
        CTRLForSequenceClassification,
        CTRLLMHeadModel,
        CTRLModel,
        CTRLPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_ctrl import (
        TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFCTRLForSequenceClassification,
        TFCTRLLMHeadModel,
        TFCTRLModel,
        TFCTRLPreTrainedModel,
    )

else:
  import sys

  __a: Dict          =   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

