| {"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 0x7d15bee0f2e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d15bee0f370>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d15bee0f400>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d15bee0f490>", "_build": "<function ActorCriticPolicy._build at 0x7d15bee0f520>", "forward": "<function ActorCriticPolicy.forward at 0x7d15bee0f5b0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d15bee0f640>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d15bee0f6d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7d15bee0f760>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d15bee0f7f0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d15bee0f880>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d15bee0f910>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d15c804cd80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1690562299642453645, "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": 300, "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "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-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.6", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |