ppo-LunarLander-v2 / config.json
sinny's picture
Upload PPO LunarLander-v2 somewhat trained agent
2c9d457
{"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 0x7ff030c94900>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff030c949a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff030c94a40>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff030c94ae0>", "_build": "<function ActorCriticPolicy._build at 0x7ff030c94b80>", "forward": "<function ActorCriticPolicy.forward at 0x7ff030c94c20>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ff030c94cc0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff030c94d60>", "_predict": "<function ActorCriticPolicy._predict at 0x7ff030c94e00>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff030c94ea0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff030c94f40>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff030c94fe0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ff030f60bc0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1688674786456511929, "learning_rate": 0.0003, "tensorboard_log": null, "_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, "_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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "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-5.15.0-76-generic-x86_64-with-glibc2.35 # 83-Ubuntu SMP Thu Jun 15 19:16:32 UTC 2023", "Python": "3.11.3", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1", "GPU Enabled": "True", "Numpy": "1.25.0", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.24.0"}}