| {"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 0x7d3343d36290>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d3343d36320>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d3343d363b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d3343d36440>", "_build": "<function ActorCriticPolicy._build at 0x7d3343d364d0>", "forward": "<function ActorCriticPolicy.forward at 0x7d3343d36560>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d3343d365f0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d3343d36680>", "_predict": "<function ActorCriticPolicy._predict at 0x7d3343d36710>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d3343d367a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d3343d36830>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d3343d368c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d3343ce2e40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 757296, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1708888543666907800, "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": 0.246336, "_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": 184, "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": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |