ppo-LunarLander-v2 / config.json
mitro99's picture
Upload PPO LunarLander-v2 trained agent
9202a2b
{"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 0x7ff366eee0d0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff366eee160>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff366eee1f0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff366eee280>", "_build": "<function ActorCriticPolicy._build at 0x7ff366eee310>", "forward": "<function ActorCriticPolicy.forward at 0x7ff366eee3a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff366eee430>", "_predict": "<function ActorCriticPolicy._predict at 0x7ff366eee4c0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff366eee550>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff366eee5e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff366eee670>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7ff366ee2ab0>"}, "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": 1672080369746503872, "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": 124, "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"}}