ppo-LunarLander-v2 / config.json
chh6's picture
Upload PPO LunarLander-v2 trained agent
1b4be52
raw
history blame
13.7 kB
{"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 0x7effaa611c60>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7effaa611cf0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7effaa611d80>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7effaa611e10>", "_build": "<function ActorCriticPolicy._build at 0x7effaa611ea0>", "forward": "<function ActorCriticPolicy.forward at 0x7effaa611f30>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7effaa611fc0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7effaa612050>", "_predict": "<function ActorCriticPolicy._predict at 0x7effaa6120e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7effaa612170>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7effaa612200>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7effaa612290>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7effaa614b80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1507328, "_total_timesteps": 1500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1688666687613147107, "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": -0.004885333333333408, "_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": 368, "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:": "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": "3.10.12", "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"}}