class_docstr: Example audio process pipeline.
  
  This example load waveform from a file then apply effects and save it to a file.
code: def __init__(self, rir_path: str):
      super().__init__()
      rir, sample_rate = torchaudio.load(rir_path)
      self.register_buffer("rir", rir)
      self.rir_sample_rate: int = sample_rate
  
file_path: audio/examples/libtorchaudio/augmentation/create_jittable_pipeline.py
imports: import argparse
  import os
  import torch
  import torchaudio
label_desc: Use image node_id 1 to create a new Pipeline object from inherited base classes: torch.nn with example: obj = Pipeline(rir_path)