{"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 0x7fea9fc9e3b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fea9fc9e440>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fea9fc9e4d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fea9fc9e560>", "_build": "<function ActorCriticPolicy._build at 0x7fea9fc9e5f0>", "forward": "<function ActorCriticPolicy.forward at 0x7fea9fc9e680>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fea9fc9e710>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fea9fc9e7a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fea9fc9e830>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fea9fc9e8c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fea9fc9e950>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fea9fc9e9e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fea9fca88c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1686847633388899280, "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": 248, "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": 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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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"}}