lucaordronneau's picture
Upload PPO LunarLander-v2 first trained agent
9fa0202
raw
history blame contribute delete
No virus
14.5 kB
{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__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 0x7fc189e54d40>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc189e54dd0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc189e54e60>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc189e54ef0>", "_build": "<function ActorCriticPolicy._build at 0x7fc189e54f80>", "forward": "<function ActorCriticPolicy.forward at 0x7fc189e5a050>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc189e5a0e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fc189e5a170>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc189e5a200>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc189e5a290>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc189e5a320>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fc189e9e810>"}, "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:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////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": 1653221904.032846, "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:": "gASVmAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDEAAAAAAAAAAAAAAAAAAAAACUdJRiLg=="}, "_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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "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-5.4.188+-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"}}