| {"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 0x7892da9b2ef0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7892da9b2f80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7892da9b3010>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7892da9b30a0>", "_build": "<function ActorCriticPolicy._build at 0x7892da9b3130>", "forward": "<function ActorCriticPolicy.forward at 0x7892da9b31c0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7892da9b3250>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7892da9b32e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7892da9b3370>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7892da9b3400>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7892da9b3490>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7892da9b3520>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7892da94fbc0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 3014656, "_total_timesteps": 3000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1707083473456424791, "learning_rate": 0.003, "tensorboard_log": "tb_logs/lr", "_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": -0.004885333333333408, "_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": 1288, "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": 0.995, "gae_lambda": 0.97, "ent_coef": 0.005, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 7, "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:": "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"}, "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"}} |