| {"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 0x7fe5e6dc1b40>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe5e6dc1bd0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe5e6dc1c60>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fe5e6dc1cf0>", "_build": "<function ActorCriticPolicy._build at 0x7fe5e6dc1d80>", "forward": "<function ActorCriticPolicy.forward at 0x7fe5e6dc1e10>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fe5e6dc1ea0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fe5e6dc1f30>", "_predict": "<function ActorCriticPolicy._predict at 0x7fe5e6dc1fc0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fe5e6dc2050>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fe5e6dc20e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fe5e6dc2170>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fe5e6db7900>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1685824004997588198, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_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:": "gAWVcAIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoB4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoECiWCAAAAAAAAAABAQEBAQEBAZRoFEsIhZRoGHSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBAoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaApLCIWUaBh0lFKUjARoaWdolGgQKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgKSwiFlGgYdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "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-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |