ppo-LunarLander-v2 / config.json
mmangino's picture
Mike's first try
9538a76
raw
history blame contribute delete
No virus
14.3 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 0x7f7fb468c680>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7fb468c710>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7fb468c7a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7fb468c830>", "_build": "<function ActorCriticPolicy._build at 0x7f7fb468c8c0>", "forward": "<function ActorCriticPolicy.forward at 0x7f7fb468c950>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7fb468c9e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f7fb468ca70>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7fb468cb00>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7fb468cb90>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7fb468cc20>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f7fb46dc4e0>"}, "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": 1651694352.1370146, "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": 470, "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, "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"}}