


"""simple docstring"""


def   snake_case						(				_a:     int							)->		Optional[Any]:
      '''simple docstring'''


      lowerCamelCase__           =		1
      lowerCamelCase__           =		2
      while i * i <= n:
            lowerCamelCase__           =		0
            while n % i == 0:
                  n //= i
                  multiplicity += 1
            n_divisors *= multiplicity + 1
            i += 1
      if n > 1:
            n_divisors *= 2
      return n_divisors



def   snake_case						(				)->		int:
      '''simple docstring'''


      lowerCamelCase__           =		1
      lowerCamelCase__           =		1

      while True:
            i += 1
            t_num += i

            if count_divisors(_a							) > 500:
                  break

      return t_num


if __name__ == "__main__":
   print(solution())







"""simple docstring"""


from typing import TYPE_CHECKING

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


_snake_case          =							{
    "configuration_blenderbot": [
        "BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "BlenderbotConfig",
        "BlenderbotOnnxConfig",
    ],
    "tokenization_blenderbot": ["BlenderbotTokenizer"],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case          =							["BlenderbotTokenizerFast"]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case          =							[
       "BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST",
       "BlenderbotForCausalLM",
       "BlenderbotForConditionalGeneration",
       "BlenderbotModel",
       "BlenderbotPreTrainedModel",
   ]


try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case          =							[
       "TFBlenderbotForConditionalGeneration",
       "TFBlenderbotModel",
       "TFBlenderbotPreTrainedModel",
   ]


try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case          =							[
       "FlaxBlenderbotForConditionalGeneration",
       "FlaxBlenderbotModel",
       "FlaxBlenderbotPreTrainedModel",
   ]


if TYPE_CHECKING:
   from .configuration_blenderbot import (
       BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
       BlenderbotConfig,
       BlenderbotOnnxConfig,
   )
   from .tokenization_blenderbot import BlenderbotTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_blenderbot import (
          BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
          BlenderbotForCausalLM,
          BlenderbotForConditionalGeneration,
          BlenderbotModel,
          BlenderbotPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_blenderbot import (
          TFBlenderbotForConditionalGeneration,
          TFBlenderbotModel,
          TFBlenderbotPreTrainedModel,
      )

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_blenderbot import (
          FlaxBlenderbotForConditionalGeneration,
          FlaxBlenderbotModel,
          FlaxBlenderbotPreTrainedModel,
      )

else:
   import sys

   _snake_case          =							_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



