ppo-LunarLander-v2 / config.json
JimChien's picture
push trained model
381d8f7 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 0x79205d478fe0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79205d479080>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79205d479120>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79205d4791c0>", "_build": "<function ActorCriticPolicy._build at 0x79205d479260>", "forward": "<function ActorCriticPolicy.forward at 0x79205d479300>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x79205d4793a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79205d479440>", "_predict": "<function ActorCriticPolicy._predict at 0x79205d4794e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79205d479580>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79205d479620>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x79205d4796c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x79205d5d7340>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1742795702864108735, "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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_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": 310, "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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.11.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}