{"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 0x7ca90e470af0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ca90e470b80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ca90e470c10>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ca90e470ca0>", "_build": "<function ActorCriticPolicy._build at 0x7ca90e470d30>", "forward": "<function ActorCriticPolicy.forward at 0x7ca90e470dc0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ca90e470e50>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ca90e470ee0>", "_predict": "<function ActorCriticPolicy._predict at 0x7ca90e470f70>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ca90e471000>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ca90e471090>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ca90e471120>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ca90e613a40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1703037154930236559, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAJpnUr3XF0a7aPlQvBGGBL4twVE8MyrpPgAAgD8AAIA/zZHOvYlVDT8IUfs6T8R2vr9E5rwswTQ8AAAAAAAAAACtyDi+zS4VP5Pcmj2d4Z2+g/movb5Tcb0AAAAAAAAAAGacAryPEl8/Gz5SPY4kaL4ex/07YmIVPQAAAAAAAAAAzbIxPLXrbT+1K3Q9fVe7vvx8YDue/lU9AAAAAAAAAADzqOW9+c8IPyrIkL3qC5C+EgJaveLQCz0AAAAAAAAAAI1rPz5M+Ic/BnUMP0LIyL4JbCA+gviQPgAAAAAAAAAApiEjPq9ZlD/4/rY+vNazvr/eTz5o/RU8AAAAAAAAAAAzNww8Lzq4PwjC7j0OyM09OBUGvP3XizsAAAAAAAAAAGbzhj1466w/O6QaPj7pyL5V4M49/2uwPQAAAAAAAAAAM6StvDCApT9gPAe+ZDnKvq3OMb1DPtW9AAAAAAAAAAAN7A0+Dcr/PotpdL4fWG6+ixoKvZS8iz0AAAAAAAAAAAAgqL10jbI/GhnevgnDcb41Y8e9iRkuvgAAAAAAAAAAAASIu+HQoboI04w1ge6uMD+sybphI7S0AACAPwAAgD/NY5q9EMopPxZCVb1cWKS+rB9FvS4kmbwAAAAAAAAAAM2Qdj0ZSKM/VpW5PkdR2b5nSP08Bs4ZPgAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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-6.1.58+-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": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}