| {"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 0x7babf9453e20>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7babf9453ec0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7babf9453f60>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7babf945c040>", "_build": "<function ActorCriticPolicy._build at 0x7babf945c0e0>", "forward": "<function ActorCriticPolicy.forward at 0x7babf945c180>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7babf945c220>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7babf945c2c0>", "_predict": "<function ActorCriticPolicy._predict at 0x7babf945c360>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7babf945c400>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7babf945c4a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7babf945c540>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7babfa74bc00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1752631128505713707, "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": -0.015808000000000044, "_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": 256, "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": "3.11.13", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |