{"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 0x7baa98999240>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7baa989992d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7baa98999360>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7baa989993f0>", "_build": "<function ActorCriticPolicy._build at 0x7baa98999480>", "forward": "<function ActorCriticPolicy.forward at 0x7baa98999510>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7baa989995a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7baa98999630>", "_predict": "<function ActorCriticPolicy._predict at 0x7baa989996c0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7baa98999750>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7baa989997e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7baa98999870>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7baaa11195c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 10240, "_total_timesteps": 10000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1724386735367616613, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAMBR873rWMw/6g67vmH30DymnB4+stSxuQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": -0.02400000000000002, "_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": 40, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "system_info": {"OS": "Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.1+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}