PPO-baseline-steps-2048000/data

{
    "policy_class": {
        ":type:": "<class 'abc.ABCMeta'>",
        ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
        "__module__": "stable_baselines3.common.policies",
        "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n        a positive standard deviation (cf paper). It allows to keep variance\n        above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n    :param squash_output: Whether to squash the output using a tanh function,\n        this allows to ensure boundaries when using gSDE.\n    :param features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\n    :param normalize_images: Whether to normalize images or not,\n         dividing by 255.0 (True by default)\n    :param optimizer_class: The optimizer to use,\n        ``th.optim.Adam`` by default\n    :param optimizer_kwargs: Additional keyword arguments,\n        excluding the learning rate, to pass to the optimizer\n    ",
        "__init__": "<function ActorCriticPolicy.__init__ at 0x7f97880880e0>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9788088170>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9788088200>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9788088290>",
        "_build": "<function ActorCriticPolicy._build at 0x7f9788088320>",
        "forward": "<function ActorCriticPolicy.forward at 0x7f97880883b0>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9788088440>",
        "_predict": "<function ActorCriticPolicy._predict at 0x7f97880884d0>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9788088560>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f97880885f0>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9788088680>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc_data object at 0x7f97880d3960>"
    },
    "verbose": 1,
    "policy_kwargs": {},
    "observation_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
        ":serialized:": "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",
        "dtype": "float32",
        "_shape": [
            8
        ],
        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
        "high": "[inf inf inf inf inf inf inf inf]",
        "bounded_below": "[False False False False False False False False]",
        "bounded_above": "[False False False False False False False False]",
        "_np_random": null
    },
    "action_space": {
        ":type:": "<class 'gym.spaces.discrete.Discrete'>",
        ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
        "n": 4,
        "_shape": [],
        "dtype": "int64",
        "_np_random": null
    },
    "n_envs": 16,
    "num_timesteps": 2048000,
    "_total_timesteps": 2048000,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1652212308.5209534,
    "learning_rate": 0.0003,
    "tensorboard_log": null,
    "lr_schedule": {
        ":type:": "<class 'function'>",
        ":serialized:": "gAWVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
    },
    "_last_obs": {
        ":type:": "<class 'numpy.ndarray'>",
        ":serialized:": "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"
    },
    "_last_episode_starts": {
        ":type:": "<class 'numpy.ndarray'>",
        ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
    },
    "_last_original_obs": null,
    "_episode_num": 0,
    "use_sde": false,
    "sde_sample_freq": -1,
    "_current_progress_remaining": 0.0,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "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"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 628,
    "n_steps": 1024,
    "gamma": 0.999,
    "gae_lambda": 0.98,
    "ent_coef": 0.01,
    "vf_coef": 0.5,
    "max_grad_norm": 0.5,
    "batch_size": 64,
    "n_epochs": 4,
    "clip_range": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
    },
    "clip_range_vf": null,
    "normalize_advantage": true,
    "target_kl": null
}