ppo-LunarLander-v2 / config.json
sinhprous's picture
Upload PPO LunarLander-v2 trained agent
6eea14b
raw
history blame contribute delete
No virus
14.4 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 0x7f0ce108ae60>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0ce108aef0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0ce108af80>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0ce1092050>", "_build": "<function ActorCriticPolicy._build at 0x7f0ce10920e0>", "forward": "<function ActorCriticPolicy.forward at 0x7f0ce1092170>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0ce1092200>", "_predict": "<function ActorCriticPolicy._predict at 0x7f0ce1092290>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0ce1092320>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0ce10923b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0ce1092440>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f0ce10da8d0>"}, "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": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652883537.9599688, "learning_rate": 0.0003, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "n_steps": 1024, "gamma": 0.99, "gae_lambda": 1.0, "ent_coef": 0.01, "vf_coef": 0.1, "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-5.4.188+-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"}}