code: def test_encode(
      data, encoder, width, height, hw_accel=None, **config
  ):
      assert data.is_cuda
  
      buffer = io.BytesIO()
      s = StreamWriter(buffer, format="mp4")
      s.add_video_stream(
          encoder=encoder,
          width=width,
          height=height,
          hw_accel=hw_accel,
          **config,
      )
      with s.open():
          t0 = time.monotonic()
          if hw_accel is None:
              data = data.to("cpu")
          s.write_video_chunk(0, data)
          elapsed = time.monotonic() - t0
      size = buffer.tell()
      fps = len(data) / elapsed
      print(
          f" - Processed {len(data)} frames in {elapsed:.2f} seconds. ({fps:.2f} fps)"
      )
      print(f" - Encoded data size: {size} bytes")
      return elapsed, size
  
file_path: audio/examples/tutorials/nvenc_tutorial.py
imports: import torch
  import torchaudio
  import io
  import time
  import matplotlib.pyplot
  from IPython.display import Video
  from torchaudio.io import StreamReader, StreamWriter
  from torchaudio.utils import ffmpeg_utils
label_desc: Use image node_id 2 for calling a global function with example usage: test_encode(data, encoder, width, height, hw_accel) and returns: elapsed,  size