code: def disk_usage_metrics(
      *,
      paths_to_monitor=None,
      minibatch=False,
      epoch=False,
      experience=False,
      stream=False,
  ) -> List[DiskPluginMetric]:
      """
      Helper method that can be used to obtain the desired set of
      standalone metrics.
  
      :param minibatch: If True, will return a metric able to log the minibatch
          Disk usage
      :param epoch: If True, will return a metric able to log the epoch
          Disk usage
      :param experience: If True, will return a metric able to log the experience
          Disk usage.
      :param stream: If True, will return a metric able to log the evaluation
          stream Disk usage.
  
      :return: A list of plugin metrics.
      """
  
      metrics: List[DiskPluginMetric] = []
      if minibatch:
          metrics.append(
              MinibatchDiskUsage(paths_to_monitor=paths_to_monitor)
          )
  
      if epoch:
          metrics.append(
              EpochDiskUsage(paths_to_monitor=paths_to_monitor)
          )
  
      if experience:
          metrics.append(
              ExperienceDiskUsage(paths_to_monitor=paths_to_monitor)
          )
  
      if stream:
          metrics.append(
              StreamDiskUsage(paths_to_monitor=paths_to_monitor)
          )
  
      return metrics
  
imports: import os
  from pathlib import Path
  from typing import Union, Sequence, List, Optional
  from avalanche.evaluation import Metric, GenericPluginMetric
label_desc: Use image node_id 1 for calling a global function with example usage: disk_usage_metrics() and returns: metrics