



"""simple docstring"""







from typing import TYPE_CHECKING

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


lowerCAmelCase_   						=   {
    'configuration_wav2vec2': ['WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Wav2Vec2Config'],
    'feature_extraction_wav2vec2': ['Wav2Vec2FeatureExtractor'],
    'processing_wav2vec2': ['Wav2Vec2Processor'],
    'tokenization_wav2vec2': ['Wav2Vec2CTCTokenizer', 'Wav2Vec2Tokenizer'],
}


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase_   						=   [
							    'WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'Wav2Vec2ForAudioFrameClassification',
							    'Wav2Vec2ForCTC',
							    'Wav2Vec2ForMaskedLM',
							    'Wav2Vec2ForPreTraining',
							    'Wav2Vec2ForSequenceClassification',
							    'Wav2Vec2ForXVector',
							    'Wav2Vec2Model',
							    'Wav2Vec2PreTrainedModel',
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase_   						=   [
							    'TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'TFWav2Vec2ForCTC',
							    'TFWav2Vec2Model',
							    'TFWav2Vec2PreTrainedModel',
							    'TFWav2Vec2ForSequenceClassification',
							]

try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase_   						=   [
							    'FlaxWav2Vec2ForCTC',
							    'FlaxWav2Vec2ForPreTraining',
							    'FlaxWav2Vec2Model',
							    'FlaxWav2Vec2PreTrainedModel',
							]


if TYPE_CHECKING:
							from .configuration_wavaveca import WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP, WavaVecaConfig
							from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
							from .processing_wavaveca import WavaVecaProcessor
							from .tokenization_wavaveca import WavaVecaCTCTokenizer, WavaVecaTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_wavaveca import (
														    WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST,
														    WavaVecaForAudioFrameClassification,
														    WavaVecaForCTC,
														    WavaVecaForMaskedLM,
														    WavaVecaForPreTraining,
														    WavaVecaForSequenceClassification,
														    WavaVecaForXVector,
														    WavaVecaModel,
														    WavaVecaPreTrainedModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_wavaveca import (
														    TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFWavaVecaForCTC,
														    TFWavaVecaForSequenceClassification,
														    TFWavaVecaModel,
														    TFWavaVecaPreTrainedModel,
														)

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_wavaveca import (
														    FlaxWavaVecaForCTC,
														    FlaxWavaVecaForPreTraining,
														    FlaxWavaVecaModel,
														    FlaxWavaVecaPreTrainedModel,
														)


else:
							import sys

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





"""simple docstring"""







import os



def      __UpperCAmelCase      (    )							->      int:
		with open(os.path.dirname(__lowerCamelCase	) + '''/p022_names.txt'''	) as file:
				lowercase__   :    List[Any]				=			str(file.readlines()[0]	)
				lowercase__   :    Dict				=			names.replace('''"'''						,     ''''''	).split(''','''	)

		names.sort()

		lowercase__   :    int				=			0
		lowercase__   :    Optional[Any]				=			0

		for i, name in enumerate(__lowerCamelCase	):
				for letter in name:
						name_score += ord(__lowerCamelCase	) - 64

				total_score += (i + 1) * name_score
				lowercase__   :    List[str]				=			0
		return total_score


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