class_docstr: Resample signal using librosa.core.resample
  
  To do downsampling only set both minimum and maximum sampling rate lower than
  original sampling rate and vice versa to do upsampling only.
docstr: :param min_sample_rate: Minimum sample rate
  :param max_sample_rate: Maximum sample rate
  :param p: The probability of applying this transform
code: def __init__(
      self,
      min_sample_rate: int = 8000,
      max_sample_rate: int = 44100,
      p: float = 0.5,
  ):
      """
      :param min_sample_rate: Minimum sample rate
      :param max_sample_rate: Maximum sample rate
      :param p: The probability of applying this transform
      """
      super().__init__(p)
      assert min_sample_rate <= max_sample_rate
      self.min_sample_rate = min_sample_rate
      self.max_sample_rate = max_sample_rate
  
file_path: audiomentations/audiomentations/augmentations/resample.py
imports: import random
  import librosa
  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 Resample object from inherited base classes: BaseWaveformTransform with example: obj = Resample(min_sample_rate, max_sample_rate, p)