| {"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 0x7b484f1cd510>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b484f1cd5a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b484f1cd630>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b484f1cd6c0>", "_build": "<function ActorCriticPolicy._build at 0x7b484f1cd750>", "forward": "<function ActorCriticPolicy.forward at 0x7b484f1cd7e0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b484f1cd870>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b484f1cd900>", "_predict": "<function ActorCriticPolicy._predict at 0x7b484f1cd990>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b484f1cda20>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b484f1cdab0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b484f1cdb40>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b48589b3cc0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1710002339242001898, "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": 310, "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": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |