| {"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 0x7d389a2a2200>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d389a2a22a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d389a2a2340>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d389a2a23e0>", "_build": "<function ActorCriticPolicy._build at 0x7d389a2a2480>", "forward": "<function ActorCriticPolicy.forward at 0x7d389a2a2520>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d389a2a25c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d389a2a2660>", "_predict": "<function ActorCriticPolicy._predict at 0x7d389a2a2700>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d389a2a27a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d389a2a2840>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d389a2a28e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d389a20c400>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1752034028543668432, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": null, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_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:": "gAWV/gAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoC4wCaTiUiYiHlFKUKEsDaA9OTk5K/////0r/////SwB0lGKMCl9ucF9yYW5kb22UTnViLg==", "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-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025", "Python": "3.11.13", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "False", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |