| {"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 0x7f3b6a4367a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3b6a436840>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f3b6a4368e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f3b6a436980>", "_build": "<function ActorCriticPolicy._build at 0x7f3b6a436a20>", "forward": "<function ActorCriticPolicy.forward at 0x7f3b6a436ac0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f3b6a436b60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f3b6a436c00>", "_predict": "<function ActorCriticPolicy._predict at 0x7f3b6a436ca0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f3b6a436d40>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f3b6a436de0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f3b6a436e80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f3b6a5b8880>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1748987648050515990, "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"}} |