ERROR:AttributeError: 'MAA2CTrainer' object has no attribute '_local_ip' about marllib HOT 7 CLOSED

{
  "actor_lr": 0.0005,
  "batch_mode": "complete_episodes",
  "buffer_size": 25000,
  "critic_lr": 0.0005,
  "env": "mpe_simple_adversary",
  "evaluation_interval": 10,
  "framework": "torch",
  "learning_starts": 400,
  "model": {
    "custom_model_config": {
      "algo_args": {
        "actor_lr": 0.0005,
        "batch_episode": 8,
        "batch_mode": "complete_episodes",
        "buffer_size_episode": 1000,
        "critic_lr": 0.0005,
        "learning_starts_episode": 16,
        "n_step": 1,
        "prioritized_replay": false,
        "smooth_target_policy": false,
        "target_network_update_freq_episode": 1,
        "tau": 0.002,
        "twin_q": false
      },
      "algorithm": "maddpg",
      "env": "mpe",
      "env_args": {
        "continuous_actions": false,
        "map_name": "simple_adversary",
        "max_cycles": 25
      },
      "episode_limit": 25,
      "evaluation_interval": 10,
      "framework": "torch",
      "global_state_flag": false,
      "local_mode": true,
      "mask_flag": false,
      "model_arch_args": {
        "core_arch": "gru",
        "fc_layer": 1,
        "hidden_state_size": 256,
        "out_dim_fc_0": 128
      },
      "num_agents": 3,
      "num_cpus_per_worker": 1,
      "num_gpus": 0,
      "num_gpus_per_worker": 0,
      "num_workers": 0,
      "opp_action_in_cc": true,
      "policy_mapping_info": {
        "simple_adversary": {
          "all_agents_one_policy": false,
          "description": "one team attack, one team survive",
          "one_agent_one_policy": true,
          "team_prefix": [
            "adversary_",
            "agent_"
          ]
        },
        "simple_crypto": {
          "all_agents_one_policy": false,
          "description": "two team cooperate, one team attack",
          "one_agent_one_policy": true,
          "team_prefix": [
            "eve_",
            "bob_",
            "alice_"
          ]
        },
        "simple_push": {
          "all_agents_one_policy": false,
          "description": "one team target on landmark, one team attack",
          "one_agent_one_policy": true,
          "team_prefix": [
            "adversary_",
            "agent_"
          ]
        },
        "simple_reference": {
          "all_agents_one_policy": true,
          "description": "one team cooperate",
          "one_agent_one_policy": true,
          "team_prefix": [
            "agent_"
          ]
        },
        "simple_speaker_listener": {
          "all_agents_one_policy": true,
          "description": "two team cooperate",
          "one_agent_one_policy": true,
          "team_prefix": [
            "speaker_",
            "listener_"
          ]
        },
        "simple_spread": {
          "all_agents_one_policy": true,
          "description": "one team cooperate",
          "one_agent_one_policy": true,
          "team_prefix": [
            "agent_"
          ]
        },
        "simple_tag": {
          "all_agents_one_policy": false,
          "description": "one team attack, one team survive",
          "one_agent_one_policy": true,
          "team_prefix": [
            "adversary_",
            "agent_"
          ]
        },
        "simple_world_comm": {
          "all_agents_one_policy": false,
          "description": "two team cooperate and attack, one team survive",
          "one_agent_one_policy": true,
          "team_prefix": [
            "adversary_",
            "leaderadversary_",
            "agent_"
          ]
        }
      },
      "seed": 123,
      "share_policy": "group",
      "space_act": "Discrete(5)",
      "space_obs": "Dict(obs:Box([-100. -100. -100. -100. -100. -100. -100. -100. -100. -100.], [100. 100. 100. 100. 100. 100. 100. 100. 100. 100.], (10,), float32))",
      "stop_iters": 9999999,
      "stop_reward": 999999,
      "stop_timesteps": 2000000
    },
    "max_seq_len": 25
  },
  "multiagent": {
    "policies": {
      "policy_adversary_": [
        null,
        "Dict(obs:Box([-100. -100. -100. -100. -100. -100. -100. -100. -100. -100.], [100. 100. 100. 100. 100. 100. 100. 100. 100. 100.], (10,), float32))",
        "Discrete(5)",
        {}
      ],
      "policy_agent_": [
        null,
        "Dict(obs:Box([-100. -100. -100. -100. -100. -100. -100. -100. -100. -100.], [100. 100. 100. 100. 100. 100. 100. 100. 100. 100.], (10,), float32))",
        "Discrete(5)",
        {}
      ]
    },
    "policy_mapping_fn": "<function run_cc.<locals>.<lambda> at 0x7f04d34fd4c0>"
  },
  "n_step": 1,
  "num_gpus": 0,
  "num_gpus_per_worker": 0,
  "num_workers": 0,
  "prioritized_replay": false,
  "simple_optimizer": false,
  "smooth_target_policy": false,
  "target_network_update_freq": 25,
  "tau": 0.002,
  "train_batch_size": 8,
  "twin_q": false,
  "zero_init_states": true
}