{"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 0x7d2474fc8a60>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d2474fc8af0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d2474fc8b80>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d2474fc8c10>", "_build": "<function ActorCriticPolicy._build at 0x7d2474fc8ca0>", "forward": "<function ActorCriticPolicy.forward at 0x7d2474fc8d30>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d2474fc8dc0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d2474fc8e50>", "_predict": "<function ActorCriticPolicy._predict at 0x7d2474fc8ee0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d2474fc8f70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d2474fc9000>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d2474fc9090>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d2474f694c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 136695, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1716035629242745122, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAACs/kb4CWzg/IuSbPcl9k77b+x29+QE5vQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.864832, "_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": 940, "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": 1, "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024", "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"}}