| {"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 0x7ef258f13eb0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ef258f13f40>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ef258f18040>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ef258f180d0>", "_build": "<function ActorCriticPolicy._build at 0x7ef258f18160>", "forward": "<function ActorCriticPolicy.forward at 0x7ef258f181f0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ef258f18280>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ef258f18310>", "_predict": "<function ActorCriticPolicy._predict at 0x7ef258f183a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ef258f18430>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ef258f184c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ef258f18550>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ef258f09240>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1706653051332842921, "learning_rate": 0.0009, "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "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-6.1.58+-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"}} |