| {"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 0x795ab361d360>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x795ab361d3f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x795ab361d480>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x795ab361d510>", "_build": "<function ActorCriticPolicy._build at 0x795ab361d5a0>", "forward": "<function ActorCriticPolicy.forward at 0x795ab361d630>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x795ab361d6c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x795ab361d750>", "_predict": "<function ActorCriticPolicy._predict at 0x795ab361d7e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x795ab361d870>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x795ab361d900>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x795ab361d990>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x795ab37b2400>"}, "verbose": 0, "policy_kwargs": {}, "num_timesteps": 100464, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1716076567643780414, "learning_rate": 0.0003, "tensorboard_log": "/content/drive/MyDrive/Colab Notebooks/colabdrive/tensorboard_logs/", "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAE21dT1gYqA/oWGaPh0kBL+rlyY+SWWXPgAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": -0.0046399999999999775, "_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": 18400, "n_steps": 1092, "gamma": 0.9978168961118316, "gae_lambda": 0.9849003271703488, "ent_coef": 0.001374961948948233, "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, "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:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 1, "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 Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "False", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |