code: def collate_dictionaries(dicts):
      """
      Collate a list of dictionaries into a single dictionary.
      """
      if len(dicts) == 0:
          return
  
      res = {}
      for key in dicts[0].keys():
          els = [d[key] for d in dicts]
          if isinstance(els[0], torch.Tensor):
              res[key] = torch.stack(els)
          elif isinstance(els[0], int):
              res[key] = torch.tensor(els)
          else:
              res[key] = els
      return res
  
imports: import unittest
  from avalanche.benchmarks.utils import DataAttribute, ConstantSequence
  from avalanche.models import SimpleMLP
  from avalanche.training.plugins import ReplayPlugin
  import torch
  import avalanche
  import torch.nn
  from avalanche.benchmarks import CLScenario, CLStream, CLExperience
  from avalanche.evaluation.metrics import accuracy_metrics
  import avalanche.training.templates.base
  from avalanche.benchmarks.utils import AvalancheDataset
label_desc: Use image node_id 1 for calling a global function with example usage: collate_dictionaries(dicts) and returns: res