import os

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



def lowerCamelCase						(     ):
    '''simple docstring'''







    __UpperCamelCase  :Union[str, Any]    						=	os.path.dirname(os.path.realpath(SCREAMING_SNAKE_CASE			)			)
    __UpperCamelCase  :Dict    						=	os.path.join(SCREAMING_SNAKE_CASE						,    '''words.txt'''			)

    __UpperCamelCase  :Optional[Any]    						=	''''''
    with open(SCREAMING_SNAKE_CASE			) as f:
        __UpperCamelCase  :List[Any]    						=	f.readline()

    __UpperCamelCase  :Any    						=	[word.strip('''"'''			) for word in words.strip('''\r\n'''			).split(''','''			)]
    __UpperCamelCase  :Dict    						=	[
        word
        for word in [sum(ord(SCREAMING_SNAKE_CASE			) - 64 for x in word			) for word in words]
        if word in TRIANGULAR_NUMBERS
    ]
    return len(SCREAMING_SNAKE_CASE			)


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






from typing import TYPE_CHECKING

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


__lowercase											=      {
    '''configuration_audio_spectrogram_transformer''': [
        '''AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''ASTConfig''',
    ]
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowercase											=      [
        '''AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''ASTForAudioClassification''',
        '''ASTModel''',
        '''ASTPreTrainedModel''',
    ]

try:
    if not is_speech_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowercase											=      ['''ASTFeatureExtractor''']

if TYPE_CHECKING:
    from .configuration_audio_spectrogram_transformer import (
        AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
        ASTConfig,
    )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_audio_spectrogram_transformer import (
            AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            ASTForAudioClassification,
            ASTModel,
            ASTPreTrainedModel,
        )

    try:
        if not is_speech_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_audio_spectrogram_transformer import ASTFeatureExtractor


else:
    import sys

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





