{"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 0x7e01ad6f5360>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e01ad6f53f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e01ad6f5480>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e01ad6f5510>", "_build": "<function ActorCriticPolicy._build at 0x7e01ad6f55a0>", "forward": "<function ActorCriticPolicy.forward at 0x7e01ad6f5630>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e01ad6f56c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e01ad6f5750>", "_predict": "<function ActorCriticPolicy._predict at 0x7e01ad6f57e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e01ad6f5870>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e01ad6f5900>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e01ad6f5990>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e01b79c7980>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1715266883684967820, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAM1Zgz3d/bw+9UzqvoIAvb5JzSG+xpeivQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": 3908, "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |