| {"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 0x7b62242d2660>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b62242d2700>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b62242d27a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b62242d2840>", "_build": "<function ActorCriticPolicy._build at 0x7b62242d28e0>", "forward": "<function ActorCriticPolicy.forward at 0x7b62242d2980>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b62242d2a20>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b62242d2ac0>", "_predict": "<function ActorCriticPolicy._predict at 0x7b62242d2b60>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b62242d2c00>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b62242d2ca0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b62242d2d40>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b62243c6580>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1507328, "_total_timesteps": 1500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1757234529308714565, "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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.004885333333333408, "_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": 368, "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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "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": "3.12.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.8.0+cu126", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |