ppo-LunarLander-v2 / config.json
xJimCod's picture
Added LunarLander-v2 model trained with PPO
0d6bc16
{"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 0x7f0756bca5e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0756bca670>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0756bca700>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0756bca790>", "_build": "<function ActorCriticPolicy._build at 0x7f0756bca820>", "forward": "<function ActorCriticPolicy.forward at 0x7f0756bca8b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0756bca940>", "_predict": "<function ActorCriticPolicy._predict at 0x7f0756bca9d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0756bcaa60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0756bcaaf0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0756bcab80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f0756c38de0>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_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": 1670620376007277410, "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": 496, "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"}}