| {"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 0x7883c9a3cd30>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7883c9a3cdc0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7883c9a3ce50>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7883c9a3cee0>", "_build": "<function ActorCriticPolicy._build at 0x7883c9a3cf70>", "forward": "<function ActorCriticPolicy.forward at 0x7883c9a3d000>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7883c9a3d090>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7883c9a3d120>", "_predict": "<function ActorCriticPolicy._predict at 0x7883c9a3d1b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7883c9a3d240>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7883c9a3d2d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7883c9a3d360>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7883c99da600>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 2031616, "_total_timesteps": 2000000.0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1695118314220079621, "learning_rate": 0.0003, "tensorboard_log": null, "_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": -0.015808000000000044, "_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": 496, "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": 16, "n_steps": 2048, "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": 8, "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-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "False", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |