| {"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 0x7e8a675b92d0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e8a675b9360>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e8a675b93f0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e8a675b9480>", "_build": "<function ActorCriticPolicy._build at 0x7e8a675b9510>", "forward": "<function ActorCriticPolicy.forward at 0x7e8a675b95a0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e8a675b9630>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e8a675b96c0>", "_predict": "<function ActorCriticPolicy._predict at 0x7e8a675b9750>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e8a675b97e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e8a675b9870>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e8a675b9900>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e8ac61a5840>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1696316998158841703, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAAAszLslNc4+63iVPT8smr4rtuE8NUz1vAAAAAAAAAAApjarPXswl7oivRS01DOdr6j+7LriobYzAACAPwAAgD9N4Xm9cYYXu76dMT6NC0C+z0/kO/ENk74AAAAAAACAP2ZCyLx13Ro/LFckPHnvkb6qmrG7zdi2vAAAAAAAAAAApmEdvlt9HT/g2js9hLSBvpz0mr14Q4c9AAAAAAAAAAAaMx49rg2XuuXqALSq7wOv6KvaOgqttTMAAIA/AACAPy1VKL4zLZs/Etjkvj7err7DKHO+p98hvgAAAAAAAAAAANSCvK49u7pae3A54JJgNBwtubkS/Yi4AACAPwAAgD+AIeI9uEhjP8axAz2Vy8S+Rjm0PWpEVbsAAAAAAAAAAHOtsj3sYb65peEDOwBRibZ/gyq7lcoqugAAgD8AAIA/syXdPQcuSz+jnV288au/vpG5Gr0d6Ys7AAAAAAAAAADNqOC7n8Onu0gzDjz8Q5U8tHcRPZspfb0AAIA/AACAPwB+4byuYaa6EogLuj429LQ7vZu6xlwgOQAAgD8AAIA/E+x2vlTORj7WOxQ+QdZ9vpsSh7sVKlE8AAAAAAAAAAAafW89sTWwPTIXBL1Kbyu+H2+fPYhzuL0AAAAAAAAAAGb2qz0f/du5wPzvN4nvDLKYZq+7fpoNtwAAgD8AAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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": -0.015808000000000044, "_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": 248, "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "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-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 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"}} |