ppo-LunarLander-v2 / config.json
tptodorov's picture
first trained lunar lander
b1f0658 verified
{"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 0x7fb909a715a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fb909a71630>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fb909a716c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fb909a71750>", "_build": "<function ActorCriticPolicy._build at 0x7fb909a717e0>", "forward": "<function ActorCriticPolicy.forward at 0x7fb909a71870>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fb909a71900>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fb909a71990>", "_predict": "<function ActorCriticPolicy._predict at 0x7fb909a71a20>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fb909a71ab0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fb909a71b40>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fb909a71bd0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fb909c13000>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1708352145417581525, "learning_rate": 0.0, "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": 276, "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, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "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:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}