| {"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 0x7cd03b9b0ee0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7cd03b9b0f70>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7cd03b9b1000>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7cd03b9b1090>", "_build": "<function ActorCriticPolicy._build at 0x7cd03b9b1120>", "forward": "<function ActorCriticPolicy.forward at 0x7cd03b9b11b0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7cd03b9b1240>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7cd03b9b12d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7cd03b9b1360>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7cd03b9b13f0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7cd03b9b1480>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7cd03b9b1510>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7cd03b951840>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1712567742799770576, "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"}} |