File size: 13,785 Bytes
7b23258 |
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 0x7b7565814c10>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b7565814ca0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b7565814d30>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b7565814dc0>", "_build": "<function ActorCriticPolicy._build at 0x7b7565814e50>", "forward": "<function ActorCriticPolicy.forward at 0x7b7565814ee0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b7565814f70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b7565815000>", "_predict": "<function ActorCriticPolicy._predict at 0x7b7565815090>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b7565815120>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b75658151b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b7565815240>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b75659af580>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1708965131919730290, "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:": "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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-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": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |