code: def _test_load_rainbow(self, gpu):
      from pfrl.q_functions import DistributionalDuelingDQN
  
      q_func = DistributionalDuelingDQN(4, 51, -10, 10)
      pnn.to_factorized_noisy(q_func, sigma_scale=0.5)
      explorer = explorers.Greedy()
      opt = torch.optim.Adam(
          q_func.parameters(), 6.25e-5, eps=1.5 * 10**-4
      )
      rbuf = replay_buffers.ReplayBuffer(100)
      agent = agents.CategoricalDoubleDQN(
          q_func,
          opt,
          rbuf,
          gpu=gpu,
          gamma=0.99,
          explorer=explorer,
          minibatch_size=32,
          replay_start_size=50,
          target_update_interval=32000,
          update_interval=4,
          batch_accumulator="mean",
          phi=lambda x: x,
      )
  
      downloaded_model, exists = download_model(
          "Rainbow",
          "BreakoutNoFrameskip-v4",
          model_type=self.pretrained_type,
      )
      agent.load(downloaded_model)
      if os.environ.get("PFRL_ASSERT_DOWNLOADED_MODEL_IS_CACHED"):
          assert exists
  
imports: import os
  import numpy
  import pytest
  import torch
  from torch import nn
  import pfrl
  import pfrl.nn
  from pfrl import agents, explorers, replay_buffers
  from pfrl.initializers import init_chainer_default
  from pfrl.utils import download_model
label_desc: Use image node_id 2 for calling the TestLoadRainbow obj's underlying member method code with example usage: obj._test_load_rainbow(gpu) without return types