class_docstr: The minibatch CPU usage metric.
  This plugin metric only works at training time.
  
  This metric "logs" the CPU usage for each iteration.
  
  If a more coarse-grained logging is needed, consider using
  :class:`EpochCPUUsage`.
class_docstr_tok: ["The","minibatch","CPU","usage","metric",".","This","plugin","metric","only","works","at","training","time",".","This","metric","``","logs","''","the","CPU","usage","for","each","iteration",".","If","a","more","coarse-grained","logging","is","needed",",","consider","using",":","class",":","`","EpochCPUUsage","`","."]
docstr: Creates an instance of the minibatch CPU usage metric.
docstr_tok: ["Creates","an","instance","of","the","minibatch","CPU","usage","metric","."]
code: def __init__(self):
      """
      Creates an instance of the minibatch CPU usage metric.
      """
      super(MinibatchCPUUsage, self).__init__(
          reset_at="iteration", emit_at="iteration", mode="train"
      )
  
imports: import os
  import warnings
  from typing import Optional, List
  from psutil import Process
  from avalanche.evaluation import Metric, PluginMetric, GenericPluginMetric
  from avalanche.evaluation.metrics import Mean
label_desc: Use image node_id 1 to create a new MinibatchCPUUsage object from inherited base classes: CPUPluginMetric with example: obj = MinibatchCPUUsage()