augly/audio/transforms.py [295:321]:
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    def __init__(
        self,
        kernel_size: int = 31,
        power: float = 2.0,
        margin: float = 1.0,
        p: float = 1.0,
    ):
        """
        @param kernel_size: kernel size for the median filters

        @param power: exponent for the Wiener filter when constructing soft mask matrices

        @param margin: margin size for the masks

        @param p: the probability of the transform being applied; default value is 1.0
        """
        super().__init__(p)
        self.kernel_size = kernel_size
        self.power = power
        self.margin = margin

    def apply_transform(
        self,
        audio: np.ndarray,
        sample_rate: int,
        metadata: Optional[List[Dict[str, Any]]] = None,
    ) -> Tuple[np.ndarray, int]:
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augly/audio/transforms.py [637:663]:
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    def __init__(
        self,
        kernel_size: int = 31,
        power: float = 2.0,
        margin: float = 1.0,
        p: float = 1.0,
    ):
        """
        @param kernel_size: kernel size for the median filters

        @param power: exponent for the Wiener filter when constructing soft mask matrices

        @param margin: margin size for the masks

        @param p: the probability of the transform being applied; default value is 1.0
        """
        super().__init__(p)
        self.kernel_size = kernel_size
        self.power = power
        self.margin = margin

    def apply_transform(
        self,
        audio: np.ndarray,
        sample_rate: int,
        metadata: Optional[List[Dict[str, Any]]] = None,
    ) -> Tuple[np.ndarray, int]:
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