| {"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 0x7b4647c7b5b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b4647c7b640>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b4647c7b6d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b4647c7b760>", "_build": "<function ActorCriticPolicy._build at 0x7b4647c7b7f0>", "forward": "<function ActorCriticPolicy.forward at 0x7b4647c7b880>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b4647c7b910>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b4647c7b9a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7b4647c7ba30>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b4647c7bac0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b4647c7bb50>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b4647c7bbe0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b4647c255c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1721225899436722406, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAMatgj76o8s+AtR5viCue75iIjw8p5BBvQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": 3980, "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": 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 Thu Jun 27 21:05:47 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"}} |