class_docstr: Make a randomly chosen part of the audio silent.
  Inspired by https://arxiv.org/pdf/1904.08779.pdf
docstr: :param min_band_part: Minimum length of the silent part as a fraction of the
      total sound length. Must be between 0.0 and 1.0
  :param max_band_part: Maximum length of the silent part as a fraction of the
      total sound length. Must be between 0.0 and 1.0
  :param fade: When set to True, add a linear fade in and fade out of the silent
      part. This can smooth out an unwanted abrupt change between two consecutive
      samples (which sounds like a transient/click/pop).
  :param p: The probability of applying this transform
code: def __init__(
      self,
      min_band_part: float = 0.0,
      max_band_part: float = 0.5,
      fade: bool = False,
      p: float = 0.5,
  ):
      """
      :param min_band_part: Minimum length of the silent part as a fraction of the
          total sound length. Must be between 0.0 and 1.0
      :param max_band_part: Maximum length of the silent part as a fraction of the
          total sound length. Must be between 0.0 and 1.0
      :param fade: When set to True, add a linear fade in and fade out of the silent
          part. This can smooth out an unwanted abrupt change between two consecutive
          samples (which sounds like a transient/click/pop).
      :param p: The probability of applying this transform
      """
      super().__init__(p)
      if min_band_part < 0.0 or min_band_part > 1.0:
          raise ValueError("min_band_part must be between 0.0 and 1.0")
      if max_band_part < 0.0 or max_band_part > 1.0:
          raise ValueError("max_band_part must be between 0.0 and 1.0")
      if min_band_part > max_band_part:
          raise ValueError(
              "min_band_part must not be greater than max_band_part"
          )
      self.min_band_part = min_band_part
      self.max_band_part = max_band_part
      self.fade = fade
  
file_path: audiomentations/audiomentations/augmentations/time_mask.py
imports: import random
  import numpy
  from numpy.typing import NDArray
  from audiomentations.core.transforms_interface import BaseWaveformTransform
label_desc: Use image node_id 1 to create a new TimeMask object from inherited base classes: BaseWaveformTransform with example: obj = TimeMask(min_band_part, max_band_part, fade, p)