{"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 0x7eb68e9d3a30>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7eb68e9d3ac0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7eb68e9d3b50>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7eb68e9d3be0>", "_build": "<function ActorCriticPolicy._build at 0x7eb68e9d3c70>", "forward": "<function ActorCriticPolicy.forward at 0x7eb68e9d3d00>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7eb68e9d3d90>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7eb68e9d3e20>", "_predict": "<function ActorCriticPolicy._predict at 0x7eb68e9d3eb0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7eb68e9d3f40>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7eb68e9d8040>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7eb68e9d80d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7eb68e9c21c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 10240, "_total_timesteps": 10000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1718988095381196576, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAABqgez4Y560/JPEBP95rwL4q46c9bfKHPgAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": -0.02400000000000002, "_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": 52, "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": "Generator(PCG64)"}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "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", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 1, "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-6.1.85+-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": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}