ppo-LunarLander-v2 / config.json
Sushantmenon123's picture
Upload PPO LunarLander-v2 trained agent
e4ef79e
{"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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7fd4c828f250>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd4c828f2e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd4c828f370>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd4c828f400>", "_build": "<function ActorCriticPolicy._build at 0x7fd4c828f490>", "forward": "<function ActorCriticPolicy.forward at 0x7fd4c828f520>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fd4c828f5b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd4c828f640>", "_predict": "<function ActorCriticPolicy._predict at 0x7fd4c828f6d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd4c828f760>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd4c828f7f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd4c828f880>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fd4c8291b40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1684713110300670193, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAGYkJLzXsyi54MHftma4CrHDb6276MYINgAAgD8AAIA/ZjZ/Oxod2z4yEyY8TXNkvviHLb0HtZ68AAAAAAAAAACmHvs99usKPzBEp71JBX++8Ou4u0vSALkAAAAAAAAAANpe+z0fdcq5SoxKO6FF4Dd4CtI7jjVwugAAgD8AAIA/Gh2+vUj/gbpwCrw8eL0CM6dyVLvNzHwyAACAPwAAgD9NOrS9e46Euk2Yu7eXQtSyOdMPugLs2TYAAAAAAACAP7Oi4L394+M+QkkePhf5h71IAm89GmSqOwAAAAAAAAAAzdWpPa55i7pO4+M6MXPjNWfpoDqImAO6AACAPwAAgD+zl0q9MR1XP6iMEL12F6y+AJRuvQbVPrwAAAAAAAAAAM1ytDyurZy6+EH6NP6v1S9eI8w4Ts5ltAAAgD8AAIA/s/Y3PXugkLqmoMK7b58HOJ/JK7vnrC63AACAPwAAgD9zCHY+RyBXP4tG5j0lJKC+5E27PW3B4jwAAAAAAAAAAKaLWr5L6lk/Q5bZvTq6eL7kP+m9JkMKPAAAAAAAAAAAgAyyPfaMUro+GZs7CJECusl3VjuMFaE6AACAPwAAgD8ACBi8glKyPwAtnr4qRZS+ZJ/wO1KIFz0AAAAAAAAAAJpwyz1cAz+6kslwOE/vWDOmhze6vJCOtwAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_shape": [8], "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}