ppo-LunarLander-v2 / config.json
Aitor's picture
V1 lunalander HF-RL-2
3eb1c5a
{"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 0x7f63047ee5e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f63047ee670>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f63047ee700>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f63047ee790>", "_build": "<function ActorCriticPolicy._build at 0x7f63047ee820>", "forward": "<function ActorCriticPolicy.forward at 0x7f63047ee8b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f63047ee940>", "_predict": "<function ActorCriticPolicy._predict at 0x7f63047ee9d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f63047eea60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f63047eeaf0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f63047eeb80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f6304864e70>"}, "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": 1670453977473697707, "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": "3.8.15", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}