code: def _algorithm_config():
      eval_env = SequentialVectorEnv(
          [_env_factory for _ in range(2)], logging_prefix="eval"
      )
  
      return ImpalaAlgorithmConfig(
          n_epochs=2,
          epoch_length=2,
          queue_out_of_sync_factor=2,
          patience=15,
          n_rollout_steps=20,
          lr=0.0005,
          gamma=0.98,
          policy_loss_coef=1.0,
          value_loss_coef=0.5,
          entropy_coef=0.0,
          max_grad_norm=0.0,
          device="cpu",
          vtrace_clip_pg_rho_threshold=1,
          vtrace_clip_rho_threshold=1,
          num_actors=1,
          actors_batch_size=5,
          critic_burn_in_epochs=0,
          rollout_evaluator=RolloutEvaluator(
              eval_env=eval_env,
              n_episodes=1,
              model_selection=None,
              deterministic=True,
          ),
      )
  
imports: import torch.nn
  from maze.core.agent.torch_actor_critic import TorchActorCritic
  from maze.core.agent.torch_policy import TorchPolicy
  from maze.core.agent.torch_state_critic import TorchSharedStateCritic
  from maze.core.wrappers.maze_gym_env_wrapper import GymMazeEnv
  from maze.distributions.distribution_mapper import DistributionMapper
  from maze.perception.models.built_in.flatten_concat import FlattenConcatPolicyNet, FlattenConcatStateValueNet
  from maze.train.parallelization.distributed_actors.distributed_actors import DistributedActors
  from maze.train.parallelization.distributed_actors.sequential_distributed_actors import SequentialDistributedActors
  from maze.train.parallelization.distributed_actors.subproc_distributed_actors import SubprocDistributedActors
  from maze.train.parallelization.vector_env.sequential_vector_env import SequentialVectorEnv
  from maze.train.trainers.common.evaluators.rollout_evaluator import RolloutEvaluator
  from maze.train.trainers.impala.impala_algorithm_config import ImpalaAlgorithmConfig
  from maze.train.trainers.impala.impala_trainer import IMPALA
  from maze.utils.timeout import Timeout
label_desc: Use image node_id 3 for calling a global function with example usage: _algorithm_config() and returns: ImpalaAlgorithmConfig