| {"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 0x7fbe821376d0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fbe82137760>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fbe821377f0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fbe82137880>", "_build": "<function ActorCriticPolicy._build at 0x7fbe82137910>", "forward": "<function ActorCriticPolicy.forward at 0x7fbe821379a0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fbe82137a30>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fbe82137ac0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fbe82137b50>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fbe82137be0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fbe82137c70>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fbe82137d00>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fbe82138780>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 524288, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1692715823996615404, "learning_rate": 0.1, "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": -0.04857599999999995, "_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": 2010, "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": 0.9, "gae_lambda": 0.95, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "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-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "False", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |