| {"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 0x7ef4c85e2e60>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ef4c85e2ef0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ef4c85e2f80>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ef4c85e3010>", "_build": "<function ActorCriticPolicy._build at 0x7ef4c85e30a0>", "forward": "<function ActorCriticPolicy.forward at 0x7ef4c85e3130>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ef4c85e31c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ef4c85e3250>", "_predict": "<function ActorCriticPolicy._predict at 0x7ef4c85e32e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ef4c85e3370>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ef4c85e3400>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ef4c85e3490>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ef4c8580600>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1719566795680064821, "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Tue Jun 18 14:18:04 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |