| {"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 0x77fda8a21f80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x77fda8a22020>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x77fda8a220c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x77fda8a22160>", "_build": "<function ActorCriticPolicy._build at 0x77fda8a22200>", "forward": "<function ActorCriticPolicy.forward at 0x77fda8a222a0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x77fda8a22340>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x77fda8a223e0>", "_predict": "<function ActorCriticPolicy._predict at 0x77fda8a22480>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x77fda8a22520>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x77fda8a225c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x77fda8a22660>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x77fda8b8b940>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1747127126001068822, "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": 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:": "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": "3.11.12", "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"}} |