{"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 0x7d8d91ffae80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d8d91ffaf20>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d8d91ffafc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d8d91ffb060>", "_build": "<function ActorCriticPolicy._build at 0x7d8d91ffb100>", "forward": "<function ActorCriticPolicy.forward at 0x7d8d91ffb1a0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d8d91ffb240>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d8d91ffb2e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7d8d91ffb380>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d8d91ffb420>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d8d91ffb4c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d8d91ffb560>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d8d92320140>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1758702829426255877, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlgAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAADAdxs+opAdP6JIWr77RuW+3aHkvECZZL0AAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////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": -0.00044800000000000395, "_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": 3908, "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-6.6.97+-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"}} |