ppo-LunarLander-v2 / config.json
SSK0908's picture
First Model
ba4a58d
raw
history blame contribute delete
No virus
14.2 kB
{"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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7f79a1286f80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f79a1287010>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f79a12870a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f79a1287130>", "_build": "<function ActorCriticPolicy._build at 0x7f79a12871c0>", "forward": "<function ActorCriticPolicy.forward at 0x7f79a1287250>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f79a12872e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f79a1287370>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f79a1287400>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f79a1287490>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f79a1287520>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f79a1289b80>"}, "verbose": 0, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 12, "num_timesteps": 1007616, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1667277851941657684, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWV9QEAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaAAQAAAAAAAGYYy72kJ3G7r2ayPBUukLwVqqI8NZl3PQAAgD8AAIA/zUudvAQFaT6V+SG87NI/vhgJGL2lAbY8AAAAAAAAAACaHgs9w3d7vIAMZb2jwrK9qCYiPIOkWzwAAIA/AACAP53HVL40EPK8UtQ1u/sMt7n9KVY+0vadOgAAgD8AAIA/zTtNvfwBSD2Fxok9WjQdvsKgBDxiEKI8AAAAAAAAAACaJ/+9+9bOPe5Md73C9I2+0AfGvDNQUz0AAAAAAAAAAOZRBz18ca4/VtMFPuNez77/n5c9a2JWPQAAAAAAAAAAQPILvpHulj4oHRW9G1iGvo2An7wQ3s+8AAAAAAAAAAAzf2c99P2vPyHBgT578aq+xfvpPcVsVD4AAAAAAAAAAA1W6b2a/N4+MWIrvKUGgL7Miw29gB/CPAAAAAAAAAAA5r+8PW+Nqj/HbpU+fdrzvv0mKT62fQQ+AAAAAAAAAACaeUE9mw7yPgjW7b3EZo2+hQu2vIDK3bsAAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLDEsIhpSMAUOUdJRSlC4="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVfwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYMAAAAAAAAAAAAAAAAAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLDIWUjAFDlHSUUpQu"}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.007616000000000067, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 328, "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, "system_info": {"OS": "Linux-5.15.0-52-generic-x86_64-with-glibc2.35 #58-Ubuntu SMP Thu Oct 13 08:03:55 UTC 2022", "Python": "3.10.6", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu117", "GPU Enabled": "True", "Numpy": "1.23.3", "Gym": "0.21.0"}}