{"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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7853f338cc10>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7853f338cca0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7853f338cd30>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7853f338cdc0>", "_build": "<function ActorCriticPolicy._build at 0x7853f338ce50>", "forward": "<function ActorCriticPolicy.forward at 0x7853f338cee0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7853f338cf70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7853f338d000>", "_predict": "<function ActorCriticPolicy._predict at 0x7853f338d090>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7853f338d120>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7853f338d1b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7853f338d240>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7853f3328c80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 2007040, "_total_timesteps": 2000000.0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1709150348879322746, "learning_rate": 1e-05, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWV9QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaAAAAAAAAAAE2bAj3+v70/lYq4PhCnmz4nSHA8x6M6PgAAAAAAAAAAiolsvr90OT+ysk69LmfPvoaior6eUYw9AAAAAAAAAABtrmG+lDQOvSjKtzUgHLw2RNx6PgnmorUAAAAAAACAPzNHKTw0w7Y/Zf55PnNIGD41lou6+F1YPQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0035199999999999676, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 7360, "n_steps": 2048, "gamma": 0.999, "gae_lambda": 0.99, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 4, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu121", "GPU Enabled": "False", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}