| {"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 0x7f8d8f29fd80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8d8f29fe20>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8d8f29fec0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8d8f29ff60>", "_build": "<function ActorCriticPolicy._build at 0x7f8d8f2a8040>", "forward": "<function ActorCriticPolicy.forward at 0x7f8d8f2a80e0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f8d8f2a8180>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8d8f2a8220>", "_predict": "<function ActorCriticPolicy._predict at 0x7f8d8f2a82c0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8d8f2a8360>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8d8f2a8400>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8d8f2a84a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f8d96386700>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1751010128428581617, "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-6.1.123+-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"}} |