| {"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 0x7f34f8e997e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f34f8e99870>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f34f8e99900>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f34f8e99990>", "_build": "<function ActorCriticPolicy._build at 0x7f34f8e99a20>", "forward": "<function ActorCriticPolicy.forward at 0x7f34f8e99ab0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f34f8e99b40>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f34f8e99bd0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f34f8e99c60>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f34f8e99cf0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f34f8e99d80>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f34f8e99e10>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f34f8e8b900>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1686736650802338535, "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": 310, "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": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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-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"}} |