LunarPPO / config.json
alexalvis's picture
Upload PPO LunarLander-v2 trained agent
6d77377 verified
{"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 0x7997cc9c2b00>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7997cc9c2b90>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7997cc9c2c20>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7997cc9c2cb0>", "_build": "<function ActorCriticPolicy._build at 0x7997cc9c2d40>", "forward": "<function ActorCriticPolicy.forward at 0x7997cc9c2dd0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7997cc9c2e60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7997cc9c2ef0>", "_predict": "<function ActorCriticPolicy._predict at 0x7997cc9c2f80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7997cc9c3010>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7997cc9c30a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7997cc9c3130>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7997ccb6d2c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1718732258251776552, "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}