ppo-LunarLander-v2 / config.json
Liamdu's picture
first commit
70aa669 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 0x7ff87f52d510>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff87f52d5a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff87f52d630>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff87f52d6c0>", "_build": "<function ActorCriticPolicy._build at 0x7ff87f52d750>", "forward": "<function ActorCriticPolicy.forward at 0x7ff87f52d7e0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ff87f52d870>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff87f52d900>", "_predict": "<function ActorCriticPolicy._predict at 0x7ff87f52d990>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff87f52da20>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff87f52dab0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff87f52db40>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ff87f4c8fc0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 131072, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1708700024926703683, "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": -0.3107200000000001, "_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": 40, "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": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}