| {"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 0x7bec2f2480d0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bec2f248160>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bec2f2481f0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bec2f248280>", "_build": "<function ActorCriticPolicy._build at 0x7bec2f248310>", "forward": "<function ActorCriticPolicy.forward at 0x7bec2f2483a0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bec2f248430>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bec2f2484c0>", "_predict": "<function ActorCriticPolicy._predict at 0x7bec2f248550>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bec2f2485e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bec2f248670>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bec2f248700>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7bebd1b9ef80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 3014656, "_total_timesteps": 3000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1733391396406562111, "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": -0.004885333333333408, "_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": 3680, "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": 20, "clip_range": {":type:": "<class 'function'>", ":serialized:": "gAWVrQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUaACMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFowEZnVuY5SMDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.5.1+cu121", "GPU Enabled": "False", "Numpy": "1.26.4", "Cloudpickle": "3.1.0", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |