code: def expert_tensor_storage(experts, feat_aggregation):
      expert_storage = {
          "fixed": set(),
          "variable": set(),
          "flaky": set(),
      }
      # fixed_sz_experts, variable_sz_experts, flaky_experts = set(), set(), set()
      for expert, config in feat_aggregation.items():
          if config["temporal"] in {"vlad"}:
              expert_storage["variable"].add(expert)
          elif all(
              [
                  x in {"avg", "max", "ent", "std"}
                  for x in config[  # pylint: disable=use-a-generator
                      "temporal"
                  ].split("-")
              ]
          ):  # pylint: disable=use-a-generator
              expert_storage["fixed"].add(expert)
          else:
              raise ValueError(
                  f"unknown temporal strategy: {config['temporal']}"
              )
          if config.get("flaky", False):
              expert_storage["flaky"].add(expert)
  
      for key, value in expert_storage.items():
          expert_storage[key] = value.intersection(set(experts))
      return expert_storage
  
label_desc: Use image node_id 1 for calling a global function with example usage: expert_tensor_storage(experts, feat_aggregation) and returns: expert_storage