class_docstr: Mock QFunction.
class_docstr_tok: ["Mock","QFunction","."]
docstr: Mock Sampling function.
docstr_tok: ["Mock","Sampling","function","."]
code: def __call__(self, observation, actions):
      """Mock Sampling function."""
      # Biggest state is best state.
      value = torch.max(observation, dim=-1).values
      # Biggest action is best action.
      q_value = torch.max(actions, axis=-1).values
      ret = value + q_value
      return ret
  
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 the DummyCriticNet obj's underlying member method code with example usage: obj.__call__(observation, actions) and returns: ret