myboy-v1/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 0x7f724c78c200>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f724c78c290>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f724c78c320>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f724c78c3b0>",
        "_build": "<function ActorCriticPolicy._build at 0x7f724c78c440>",
        "forward": "<function ActorCriticPolicy.forward at 0x7f724c78c4d0>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f724c78c560>",
        "_predict": "<function ActorCriticPolicy._predict at 0x7f724c78c5f0>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f724c78c680>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f724c78c710>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f724c78c7a0>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc_data object at 0x7f724c7cdd20>"
    },
    "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": 503808,
    "_total_timesteps": 500000,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1661173299.0259356,
    "learning_rate": 0.0003,
    "tensorboard_log": null,
    "lr_schedule": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
    },
    "_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": -0.007616000000000067,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "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"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 205,
    "n_steps": 768,
    "gamma": 0.975,
    "gae_lambda": 0.95,
    "ent_coef": 0.015,
    "vf_coef": 0.5,
    "max_grad_norm": 0.5,
    "batch_size": 128,
    "n_epochs": 5,
    "clip_range": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
    },
    "clip_range_vf": null,
    "normalize_advantage": true,
    "target_kl": null
}