| {"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 0x78e775a5b130>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78e775a5b1c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78e775a5b250>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78e775a5b2e0>", "_build": "<function ActorCriticPolicy._build at 0x78e775a5b370>", "forward": "<function ActorCriticPolicy.forward at 0x78e775a5b400>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x78e775a5b490>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78e775a5b520>", "_predict": "<function ActorCriticPolicy._predict at 0x78e775a5b5b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78e775a5b640>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78e775a5b6d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x78e775a5b760>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x78e775bf6980>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 481230, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1711809528359551712, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAPOscL7bGKc9jbIGPZ4LGb7ieIS8cA+PPQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": 0.519744, "_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": 1876, "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:": "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": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |