| {"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 0x7d49c11e0220>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d49c11e02c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d49c11e0360>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d49c11e0400>", "_build": "<function ActorCriticPolicy._build at 0x7d49c11e04a0>", "forward": "<function ActorCriticPolicy.forward at 0x7d49c11e0540>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d49c11e05e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d49c11e0680>", "_predict": "<function ActorCriticPolicy._predict at 0x7d49c11e0720>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d49c11e07c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d49c11e0860>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d49c11e0900>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d49c15b4f40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1760369829016210338, "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-6.6.97+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Sep 6 09:54:41 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"}} |