code: def __call__(self, key: str, values):
      # Ensure that tensor is on cpu before aggregation.
      values = torch.cat(values, dim=0).cpu()
      return super().__call__(key, values)
  
imports: import logging
  from collections import deque
  from typing import Any, Callable, Deque, Dict, List, Optional
  import numpy
  import torch
  from reagent.core.tensorboardX import SummaryWriterContext
  from reagent.core.tracker import Aggregator
label_desc: Use image node_id 1 for calling the TensorAggregator obj's underlying member method code with example usage: obj.__call__(key, values) and returns: super