class_docstr: Trim leading and trailing silence from an audio signal using librosa.effects.trim
code: def apply(self, samples: NDArray[np.float32], sample_rate: int):
      samples, lens = librosa.effects.trim(samples, top_db=self.top_db)
      return samples
  
file_path: audiomentations/audiomentations/augmentations/trim.py
imports: import librosa
  import numpy
  from numpy.typing import NDArray
  from audiomentations.core.transforms_interface import BaseWaveformTransform
label_desc: Use image node_id 2 for calling the Trim obj's underlying member method code with example usage: obj.apply(samples, sample_rate) and returns: samples