| {"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 0x78dbd9d54e00>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78dbd9d54ea0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78dbd9d54f40>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78dbd9d54fe0>", "_build": "<function ActorCriticPolicy._build at 0x78dbd9d55080>", "forward": "<function ActorCriticPolicy.forward at 0x78dbd9d55120>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x78dbd9d551c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78dbd9d55260>", "_predict": "<function ActorCriticPolicy._predict at 0x78dbd9d55300>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78dbd9d553a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78dbd9d55440>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x78dbd9d554e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x78dbda181a80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1081344, "_total_timesteps": 3000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1754298959945398134, "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": 0.639552, "_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": 260, "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-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025", "Python": "3.11.13", "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"}} |