File size: 13,770 Bytes
a2ee762 |
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 0x7d07ba142710>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d07ba1427a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d07ba142830>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d07ba1428c0>", "_build": "<function ActorCriticPolicy._build at 0x7d07ba142950>", "forward": "<function ActorCriticPolicy.forward at 0x7d07ba1429e0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d07ba142a70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d07ba142b00>", "_predict": "<function ActorCriticPolicy._predict at 0x7d07ba142b90>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d07ba142c20>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d07ba142cb0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d07ba142d40>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d07ba2e1940>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1709919880222575393, "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": 248, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "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:": "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-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu121", "GPU Enabled": "False", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |