ppo-LunarLander-v2 / config.json
sonnyky's picture
upload model
6b93b9f
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 0x7f2e92751710>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2e927517a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2e92751830>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2e927518c0>", "_build": "<function ActorCriticPolicy._build at 0x7f2e92751950>", "forward": "<function ActorCriticPolicy.forward at 0x7f2e927519e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2e92751a70>", "_predict": "<function ActorCriticPolicy._predict at 0x7f2e92751b00>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2e92751b90>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2e92751c20>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2e92751cb0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f2e9279f690>"}, "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": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1669780340573639291, "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": 124, "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-5.10.133+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.7.15", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}