class_docstr: Class for obtaining an Accuracy Matrix for the evaluation stream
class_docstr_tok: ["Class","for","obtaining","an","Accuracy","Matrix","for","the","evaluation","stream"]
docstr: Performs actions after evaluating an experience.
  
  :param strategy: The strategy object associated with the stream.
docstr_tok: ["Performs","actions","after","evaluating","an","experience",".",":","param","strategy",":","The","strategy","object","associated","with","the","stream","."]
code: def after_eval_exp(self, strategy: "SupervisedTemplate"):
      """Performs actions after evaluating an experience.
  
      :param strategy: The strategy object associated with the stream.
      """
      super().after_eval_exp(strategy)
      curr_exp = strategy.experience.current_experience
      self.update(self.num_training_steps, curr_exp)
  
file_path: avalanche/avalanche/evaluation/metrics/acc_matrix.py
imports: import torch
  from typing import List
  from avalanche.evaluation import PluginMetric
  from avalanche.evaluation.metric_results import MetricValue, MetricResult
  from avalanche.evaluation.metrics.accuracy import Accuracy
  from avalanche.training.templates import SupervisedTemplate
label_desc: Use image node_id 8 for calling the AccuracyMatrixPluginMetric obj's underlying member method code with example usage: obj.after_eval_exp(strategy) without return types