ppo-LunarLander-v2 / config.json
viet19197's picture
Upload PPO LunarLander-v2 trained agent
85bcbe4
{"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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7f299896fca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f299896fd30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f299896fdc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f299896fe50>", "_build": "<function ActorCriticPolicy._build at 0x7f299896fee0>", "forward": "<function ActorCriticPolicy.forward at 0x7f299896ff70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2998973040>", "_predict": "<function ActorCriticPolicy._predict at 0x7f29989730d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2998973160>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f29989731f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2998973280>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f2998967f30>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [4], "low": "[-4.8000002e+00 -3.4028235e+38 -4.1887903e-01 -3.4028235e+38]", "high": "[4.8000002e+00 3.4028235e+38 4.1887903e-01 3.4028235e+38]", "bounded_below": "[ True True True True]", "bounded_above": "[ True True True True]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLAowGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 2, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1672149384562435261, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "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, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}