code: def testTemperatureLoss():
      """Test Sac temperature loss."""
      # pylint: disable=no-member
      policy = DummyActorPolicy()
      policy = DummyActorPolicy()
      spec = MagicMock
      sac = SAC(
          env_spec=spec,
          policy=policy,
          qf1=DummyCriticNet(),
          qf2=DummyCriticNet(),
          sampler=None,
          replay_buffer=None,
          discount=1,
          buffer_batch_size=2,
          target_entropy=3.0,
          initial_log_entropy=4.0,
          optimizer=MagicMock,
          gradient_steps_per_itr=1,
      )
      observations = torch.Tensor([[1.0, 2.0], [3.0, 4.0]])
      action_dists = policy(observations)[0]
      actions = action_dists.rsample_with_pre_tanh_value()
      log_pi = action_dists.log_prob(actions)
      samples_data = dict(observation=observations, action=actions)
      expected_loss = 4.0 * (-10 - 3)
      loss = sac._temperature_objective(log_pi, samples_data).item()
      assert np.all(np.isclose(loss, expected_loss))
  
imports: from unittest.mock import MagicMock
  import numpy
  import pytest
  import torch
  from torch.nn import functional
  from garage.envs import GymEnv, normalize
  from garage.experiment import deterministic
  from garage.replay_buffer import PathBuffer
  from garage.sampler import FragmentWorker, LocalSampler
  from garage.torch import set_gpu_mode
  from garage.torch.algos import SAC
  from garage.torch.policies import TanhGaussianMLPPolicy
  from garage.torch.q_functions import ContinuousMLPQFunction
  from garage.trainer import Trainer
  from tests.fixtures import snapshot_config
label_desc: Use image node_id 3 for calling a global function with example usage: testTemperatureLoss() without return types