| {"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 0x7ab8b72bc940>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ab8b72bc9d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ab8b72bca60>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ab8b72bcaf0>", "_build": "<function ActorCriticPolicy._build at 0x7ab8b72bcb80>", "forward": "<function ActorCriticPolicy.forward at 0x7ab8b72bcc10>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ab8b72bcca0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ab8b72bcd30>", "_predict": "<function ActorCriticPolicy._predict at 0x7ab8b72bcdc0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ab8b72bce50>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ab8b72bcee0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ab8b72bcf70>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ab8b725e8c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1714815982132271068, "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:": "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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": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |