vllm.transformers_utils.configs.parakeet ¶

@dataclass(kw_only=True, frozen=True)
class ExtractorConfig:
    feature_size: int
    sampling_rate: int
    subsampling_factor: int
    subsampling_conv_kernel_size: int
    subsampling_conv_stride: int
    hop_length: int = 160
    """Default `160`: Matches HF default"""
    clip_duration_s: int = 30
    clip_min_duration_s: float = 0.1

    win_length: int = 400
    preemphasis: float = 0.97
    n_fft: int = 512
    padding_value: float = 0.0

    @classmethod
    def from_hf_config(cls, config: PretrainedConfig) -> "ExtractorConfig":
        assert isinstance(config, PretrainedConfig)
        defaults = ("hop_length", "win_length", "preemphasis", "n_fft", "padding_value")
        optional_kwargs = {
            name: getattr(config, name) for name in defaults if hasattr(config, name)
        }

        return cls(
            feature_size=config.num_mel_bins,
            sampling_rate=config.sampling_rate,
            subsampling_factor=config.subsampling_factor,
            subsampling_conv_kernel_size=config.subsampling_conv_kernel_size,
            subsampling_conv_stride=config.subsampling_conv_stride,
            **optional_kwargs,
        )