| {"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 0x7a1f11b1fac0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a1f11b1fb50>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a1f11b1fbe0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a1f11b1fc70>", "_build": "<function ActorCriticPolicy._build at 0x7a1f11b1fd00>", "forward": "<function ActorCriticPolicy.forward at 0x7a1f11b1fd90>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a1f11b1fe20>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a1f11b1feb0>", "_predict": "<function ActorCriticPolicy._predict at 0x7a1f11b1ff40>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a1f11b28040>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a1f11b280d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a1f11b28160>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7a1f11b25180>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1693149151781696447, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAEb2Hr7D7Qs/XigxPu8kz74EyBy9XbbsOQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": -0.00044800000000000395, "_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": 4300, "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-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |