code: def learning_curves_plot(all_metrics: dict):
      """Creates a plot with separate learning curves for each experience.
  
      :param all_metrics: Dictionary of metrics as returned by
          EvaluationPlugin.get_all_metrics
      :return: matplotlib figure
      """
      accs_keys = list(
          filter(lambda x: "Top1_Acc_Exp" in x, all_metrics.keys())
      )
      fig, ax = plt.subplots()
      for ak in accs_keys:
          k = ak.split("/")[-1]
          x, y = all_metrics[ak]
          plt.plot(x, y, label=k)
      ax.legend()
      ax.set_xlabel("Iterations")
      ax.set_ylabel("Experience Accuracy")
      return fig
  
label_desc: Use image node_id 1 for calling a global function with example usage: learning_curves_plot(all_metrics) and returns: fig