| {"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 0x7fb6bf1daa20>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fb6bf1daac0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fb6bf1dab60>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fb6bf1dac00>", "_build": "<function ActorCriticPolicy._build at 0x7fb6bf1daca0>", "forward": "<function ActorCriticPolicy.forward at 0x7fb6bf1dad40>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fb6bf1dade0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fb6bf1dae80>", "_predict": "<function ActorCriticPolicy._predict at 0x7fb6bf1daf20>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fb6bf1dafc0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fb6bf1db060>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fb6bf1db100>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fb6c0fe60c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 100352, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1757192647240521064, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlgAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAABasS6+EN+wPzyiD7/3hXi+wdYYvviCgr4AAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLAUsIhpSMAUOUdJRSlC4="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWAQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksBhZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0035199999999999676, "_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": 396, "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": 1, "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"}} |