ppo-LunarLander-v6 / config.json
AnAmbitiousMonk's picture
Upload PPO LunarLander-v2 trained agent
3e1381a
raw
history blame
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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7eff2ce0c280>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7eff2ce0c310>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7eff2ce0c3a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7eff2ce0c430>", "_build": "<function ActorCriticPolicy._build at 0x7eff2ce0c4c0>", "forward": "<function ActorCriticPolicy.forward at 0x7eff2ce0c550>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7eff2ce0c5e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7eff2ce0c670>", "_predict": "<function ActorCriticPolicy._predict at 0x7eff2ce0c700>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7eff2ce0c790>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7eff2ce0c820>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7eff2ce0c8b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7eff2ce0f060>"}, "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": 2031616, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1676652889629034641, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAEAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": 2048, "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:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}