| {"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 0x7e3aed31d3a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e3aed31d440>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e3aed31d4e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e3aed31d580>", "_build": "<function ActorCriticPolicy._build at 0x7e3aed31d620>", "forward": "<function ActorCriticPolicy.forward at 0x7e3aed31d6c0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e3aed31d760>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e3aed31d800>", "_predict": "<function ActorCriticPolicy._predict at 0x7e3aed31d8a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e3aed31d940>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e3aed31d9e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e3aed31da80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e3aed45a1c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1744582779946876298, "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": "3.11.12", "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"}} |