{"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 0x7fd7f5ff8280>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd7f5ff8310>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd7f5ff83a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd7f5ff8430>", "_build": "<function ActorCriticPolicy._build at 0x7fd7f5ff84c0>", "forward": "<function ActorCriticPolicy.forward at 0x7fd7f5ff8550>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fd7f5ff85e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd7f5ff8670>", "_predict": "<function ActorCriticPolicy._predict at 0x7fd7f5ff8700>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd7f5ff8790>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd7f5ff8820>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd7f5ff88b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fd7f5ff64c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1688468035543631203, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAADMplT0fDfy5Np+dOY/HmTQTFUU7c1K7uAAAgD8AAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00044800000000000395, "_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": 3908, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 1, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |