RL_firstTry / config.json
xiaofxiong's picture
first try for RL -- the LunarLander-v2
3e9cc17
{"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 0x7f9aca4b1ca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9aca4b1d30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9aca4b1dc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9aca4b1e50>", "_build": "<function ActorCriticPolicy._build at 0x7f9aca4b1ee0>", "forward": "<function ActorCriticPolicy.forward at 0x7f9aca4b1f70>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f9aca4af040>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9aca4af0d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f9aca4af160>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9aca4af1f0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9aca4af280>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9aca4af310>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f9aca49b6f0>"}, "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": 1676034039060155343, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/M6kqMFUyYYWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAEAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": 0.999, "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"}}