| {"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 0x781ffd85cee0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x781ffd85cf70>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x781ffd85d000>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x781ffd85d090>", "_build": "<function ActorCriticPolicy._build at 0x781ffd85d120>", "forward": "<function ActorCriticPolicy.forward at 0x781ffd85d1b0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x781ffd85d240>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x781ffd85d2d0>", "_predict": "<function ActorCriticPolicy._predict at 0x781ffd85d360>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x781ffd85d3f0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x781ffd85d480>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x781ffd85d510>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x781ffd9fafc0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 5013504, "_total_timesteps": 5000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1706893478864354814, "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": -0.0027007999999999477, "_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": 1472, "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": 128, "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": "2.1.0+cu121", "GPU Enabled": "False", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |