code: def trace_plot(data, device=None, plot_segments=False):
      """Generate a visualization over time of the memory usage recorded by the trace as an html file.
  
      Args:
          data: Memory snapshot as generated from torch.cuda.memory._snapshot()
          device (torch.device, optional): Generate the trace for this device, needed if multiple devices have allocations.
          plot_segments (bool, optional): Plots memory returned from cudaMalloc, rather than individual allocations.
                                          Defaults to False.
  
      Returns:
          str: HTML of visualization
      """
      return _format_viz(
          data,
          "Active Memory Timeline"
          if not plot_segments
          else "Active Cached Memory Timeline",
          device,
      )
  
imports: import pickle
  import sys
  import os
  import io
  import subprocess
  import json
  from functools import lru_cache
  from typing import Any
  from itertools import groupby
  import base64
  import warnings
label_desc: Use image node_id 17 for calling a global function with example usage: trace_plot(data, device, plot_segments) and returns: _format_viz