code: def plot():
      fig, axes = plt.subplots(2, 1, sharex=True, figsize=[9.6, 7.2])
  
      for items in zip(time_360, time_720, time_1080, "ov^X+"):
          axes[0].plot(items[:-1], marker=items[-1])
      axes[0].grid(axis="both")
      axes[0].set_xticks(
          [0, 1, 2], ["360p", "720p", "1080p"], visible=True
      )
      axes[0].tick_params(labeltop=False)
      axes[0].legend(
          [
              "Software Encoding (threads=1)",
              "Software Encoding (threads=4)",
              "Software Encoding (threads=8)",
              "Hardware Encoding (CPU Tensor)",
              "Hardware Encoding (CUDA Tensor)",
          ]
      )
      axes[0].set_title(
          "Time to encode videos with different resolutions"
      )
      axes[0].set_ylabel("Time [s]")
  
      for items in zip(size_360, size_720, size_1080, "v^"):
          axes[1].plot(items[:-1], marker=items[-1])
      axes[1].grid(axis="both")
      axes[1].set_xticks([0, 1, 2], ["360p", "720p", "1080p"])
      axes[1].set_ylabel("The encoded size [bytes]")
      axes[1].set_title("The size of encoded videos")
      axes[1].legend(
          [
              "Software Encoding",
              "Hardware Encoding",
          ]
      )
  
      plt.tight_layout()
  
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 4 for calling a global function with example usage: plot() without return types