






from typing import TYPE_CHECKING

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


UpperCAmelCase__				   =		{
    "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:
     UpperCAmelCase__				   =		[
         "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:
     UpperCAmelCase__				   =		[
         "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:
     UpperCAmelCase__				   =		[
         "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

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










def 						_a    (      a :int = 100 )							->			int:
 a		  =      n * (n + 1) * (2 * n + 1) / 6
 a		  =      (n * (n + 1) / 2) ** 2
 return int(square_of_sum - sum_of_squares )


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


