File size: 10,973 Bytes
97e4abd |
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 0x7dd329948c10>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7dd329948ca0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7dd329948d30>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7dd329948dc0>", "_build": "<function ActorCriticPolicy._build at 0x7dd329948e50>", "forward": "<function ActorCriticPolicy.forward at 0x7dd329948ee0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7dd329948f70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7dd329949000>", "_predict": "<function ActorCriticPolicy._predict at 0x7dd329949090>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7dd329949120>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7dd3299491b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7dd329949240>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7dd329933f80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 35744, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1689715747360084704, "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": 0.67232, "_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": 200, "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": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "system_info": {"OS": "Linux-5.15.109+-x86_64-with-glibc2.31 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |