





import os

# Precomputes a list of the 100 first triangular numbers
A__:    Tuple  	=	[int(0.5 * n * (n + 1)) for n in range(1, 101)]



def 				lowerCAmelCase_ (							):
    UpperCamelCase__:	Dict					=     os.path.dirname(os.path.realpath(A_))
    UpperCamelCase__:	Optional[int]					=     os.path.join(A_    ,"words.txt")

    UpperCamelCase__:	Tuple					=     ""
    with open(A_) as f:
        UpperCamelCase__:	int					=     f.readline()

    UpperCamelCase__:	str					=     [word.strip("\"") for word in words.strip("\r\n").split(",")]
    UpperCamelCase__:	int					=     [
        word
        for word in [sum(ord(A_) - 64 for x in word) for word in words]
        if word in TRIANGULAR_NUMBERS
    ]
    return len(A_)


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








from typing import TYPE_CHECKING

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


A__:    Any  	=	{
    '''configuration_gpt_neox_japanese''': ['''GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoXJapaneseConfig'''],
    '''tokenization_gpt_neox_japanese''': ['''GPTNeoXJapaneseTokenizer'''],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A__:    Union[str, Any]  	=	[
       '''GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''GPTNeoXJapaneseForCausalLM''',
       '''GPTNeoXJapaneseLayer''',
       '''GPTNeoXJapaneseModel''',
       '''GPTNeoXJapanesePreTrainedModel''',
   ]


if TYPE_CHECKING:
   from .configuration_gpt_neox_japanese import GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXJapaneseConfig
   from .tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_gpt_neox_japanese import (
          GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
          GPTNeoXJapaneseForCausalLM,
          GPTNeoXJapaneseLayer,
          GPTNeoXJapaneseModel,
          GPTNeoXJapanesePreTrainedModel,
      )


else:
   import sys

   A__:    str  	=	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

