| {"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 0x7874c2f8e710>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7874c2f8e7a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7874c2f8e830>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7874c2f8e8c0>", "_build": "<function ActorCriticPolicy._build at 0x7874c2f8e950>", "forward": "<function ActorCriticPolicy.forward at 0x7874c2f8e9e0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7874c2f8ea70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7874c2f8eb00>", "_predict": "<function ActorCriticPolicy._predict at 0x7874c2f8eb90>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7874c2f8ec20>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7874c2f8ecb0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7874c2f8ed40>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7874c38a4940>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1721929304072926049, "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": 248, "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": 16, "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:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.85+-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": "2.3.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |