| {"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 0x7d2fc6d220e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d2fc6d22170>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d2fc6d22200>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d2fc6d22290>", "_build": "<function ActorCriticPolicy._build at 0x7d2fc6d22320>", "forward": "<function ActorCriticPolicy.forward at 0x7d2fc6d223b0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d2fc6d22440>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d2fc6d224d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7d2fc6d22560>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d2fc6d225f0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d2fc6d22680>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d2fc6d22710>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d2fc6ebe840>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 4014080, "_total_timesteps": 4000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1706406864254383789, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAAa2Vj68eZA+oPhXvtS4y75J4uc9kqsjvgAAAAAAAAAAmvMcvR/eHD9d+9k9zoryvi+wgruUEEI9AAAAAAAAAADmpGU9kC+3P1qGqj7WXgG+3/rzPdKwkz4AAAAAAAAAAI0yhz0B8o28CUSzvcqFNTzx2wA+CAIVvQAAgD8AAIA/jSjkPWH3hz6szYC+YRXBvlKsGz0iEPi9AAAAAAAAAACzZQo9C2dPP7bSYjmTZPy+D29BvKCVf70AAAAAAAAAAGbAQD2kwl276wycvNIcojyBT4s802yJvQAAgD8AAIA/ABRDvOFEo7rCcDY07SGCL6Bx9bmr16mzAACAPwAAgD9mlo26j38kvEIXw7vMwo48BE+MPT1ebL0AAIA/AACAPzNZiT0pYFO6m89puzZNurYUXw+5nhErNgAAgD8AAAAAmvVVPYY/lj/7HW4+gscLv4zn1T3DWnc9AAAAAAAAAAAzpBk9B/UZPm/Wmrvz+9q+oq1bPDeQNj0AAAAAAAAAAOaNzj1kDIE/ThM6Pq8ICL+1SWs+CHN1PQAAAAAAAAAAmqq4PCmACbxOliC8hxK8PBKCdz3GFpu9AACAPwAAgD9mhhe9NmsEvE75xbpv5Zs8/oRbPVzQgb0AAIA/AACAPxq5CD0pbAc5YmoUvvOYf75jFTS9leTsPgAAgD8AAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": -0.0035199999999999676, "_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": 980, "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-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": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |