{"policy_class": {":type:": "", ":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__": "", "_get_constructor_parameters": "", "reset_noise": "", "_build_mlp_extractor": "", "_build": "", "forward": "", "extract_features": "", "_get_action_dist_from_latent": "", "_predict": "", "evaluate_actions": "", "get_distribution": "", "predict_values": "", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7860c8054ec0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1731512563185082128, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAABpdP71PH6g/cEztvR853r69F1e9MmJDvAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "", ":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:": "", ":serialized:": "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"}, "ep_success_buffer": {":type:": "", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 3908, "observation_space": {":type:": "", ":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:": "", ":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:": "", ":serialized:": "gAWVrQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUaACMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFowEZnVuY5SMDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "", ":serialized:": "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"}, "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": "2.5.0+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.0", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}