class_docstr: Apply tanh (hyperbolic tangent) distortion to the audio. This technique is sometimes
  used for adding distortion to guitar recordings. The tanh() function can give a rounded
  "soft clipping" kind of distortion, and the distortion amount is proportional to the
  loudness of the input and the pre-gain. Tanh is symmetric, so the positive and
  negative parts of the signal are squashed in the same way. This transform can be
  useful as data augmentation because it adds harmonics. In other words, it changes
  the timbre of the sound.
  
  See this page for examples: http://gdsp.hf.ntnu.no/lessons/3/17/
code: def randomize_parameters(
      self, samples: NDArray[np.float32], sample_rate: int
  ):
      super().randomize_parameters(samples, sample_rate)
      if self.parameters["should_apply"]:
          self.parameters["distortion_amount"] = random.uniform(
              self.min_distortion, self.max_distortion
          )
  
file_path: audiomentations/audiomentations/augmentations/tanh_distortion.py
imports: import random
  import numpy
  from numpy.typing import NDArray
  from audiomentations.core.transforms_interface import BaseWaveformTransform
  from audiomentations.core.utils import calculate_rms
label_desc: Use image node_id 2 for calling the TanhDistortion obj's underlying member method code with example usage: obj.randomize_parameters(samples, sample_rate) without return types