| {"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 0x79cf89724180>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79cf89724220>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79cf897242c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79cf89724360>", "_build": "<function ActorCriticPolicy._build at 0x79cf89724400>", "forward": "<function ActorCriticPolicy.forward at 0x79cf897244a0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x79cf89724540>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79cf897245e0>", "_predict": "<function ActorCriticPolicy._predict at 0x79cf89724680>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79cf89724720>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79cf897247c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x79cf89724860>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x79cf8988bf80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1743057820632559845, "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.11.11", "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"}} |