File size: 13,759 Bytes
9940e5c |
1 |
{"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 0x7e47efabec20>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e47efabecb0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e47efabed40>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e47efabedd0>", "_build": "<function ActorCriticPolicy._build at 0x7e47efabee60>", "forward": "<function ActorCriticPolicy.forward at 0x7e47efabeef0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e47efabef80>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e47efabf010>", "_predict": "<function ActorCriticPolicy._predict at 0x7e47efabf0a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e47efabf130>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e47efabf1c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e47efabf250>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e47efa5fd80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1702039365538876554, "learning_rate": 0.0003, "tensorboard_log": null, "_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, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 372, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_shape": [8], "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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": 6, "clip_range": {":type:": "<class 'function'>", ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |