PPO-LunarLander-v2-Try / config.json
StanKarz's picture
Trained agent on LunarLander-v2
2af3f88
raw
history blame
14.7 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 0x7f5d86ab1680>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f5d86ab1710>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f5d86ab17a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f5d86ab1830>", "_build": "<function ActorCriticPolicy._build at 0x7f5d86ab18c0>", "forward": "<function ActorCriticPolicy.forward at 0x7f5d86ab1950>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f5d86ab19e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f5d86ab1a70>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f5d86ab1b00>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f5d86ab1b90>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f5d86ab1c20>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f5d86b023f0>"}, "verbose": 1, "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": 25, "num_timesteps": 5504000, "_total_timesteps": 5500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652646757.4214516, "learning_rate": 0.00105, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVjAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYZAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxmFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0007272727272726875, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 1720, "n_steps": 1024, "gamma": 0.9995, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 128, "n_epochs": 8, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}