ppo-LunarLander-v2 / config.json
SwePalm's picture
next try
da131eb
raw
history blame
15 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 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 0x7f42d97c95e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f42d97c9670>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f42d97c9700>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f42d97c9790>", "_build": "<function ActorCriticPolicy._build at 0x7f42d97c9820>", "forward": "<function ActorCriticPolicy.forward at 0x7f42d97c98b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f42d97c9940>", "_predict": "<function ActorCriticPolicy._predict at 0x7f42d97c99d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f42d97c9a60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f42d97c9af0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f42d97c9b80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f42d97bfea0>"}, "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": 32, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670704872957555620, "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:": "gAWVkwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksghZSMAUOUdJRSlC4="}, "_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": 0.998, "gae_lambda": 0.97, "ent_coef": 0.005, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 32, "n_epochs": 8, "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"}}