| {"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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7fbce826b040>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fbce826b0d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fbce826b160>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fbce826b1f0>", "_build": "<function ActorCriticPolicy._build at 0x7fbce826b280>", "forward": "<function ActorCriticPolicy.forward at 0x7fbce826b310>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fbce826b3a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fbce826b430>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fbce826b4c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fbce826b550>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fbce826b5e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fbce8262d80>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu", "log_std_init": -2, "ortho_init": false, "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False]", "bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False]", "_shape": [22], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf]", "low_repr": "-inf", "high_repr": "inf", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVawIAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWBgAAAAAAAAABAQEBAQGUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLBoWUjAFDlHSUUpSMDWJvdW5kZWRfYWJvdmWUaBAolgYAAAAAAAAAAQEBAQEBlGgUSwaFlGgYdJRSlIwGX3NoYXBllEsGhZSMA2xvd5RoECiWGAAAAAAAAAAAAIC/AACAvwAAgL8AAIC/AACAvwAAgL+UaApLBoWUaBh0lFKUjARoaWdolGgQKJYYAAAAAAAAAAAAgD8AAIA/AACAPwAAgD8AAIA/AACAP5RoCksGhZRoGHSUUpSMCGxvd19yZXBylIwELTEuMJSMCWhpZ2hfcmVwcpSMAzEuMJSMCl9ucF9yYW5kb22UjBFneW0udXRpbHMuc2VlZGluZ5SMJVJhbmRvbU51bWJlckdlbmVyYXRvci5fZ2VuZXJhdG9yX2N0b3KUk5SMBVBDRzY0lIWUUpR9lCiMDWJpdF9nZW5lcmF0b3KUjAVQQ0c2NJSMBXN0YXRllH2UKGg6ihF4QbDsu+/aZngVpH47CkmaAIwDaW5jlIoRp/F/Wdkys//QZCzrlccg/QB1jApoYXNfdWludDMylEsAjAh1aW50ZWdlcpRLAHVidWIu", "dtype": "float32", "bounded_below": "[ True True True True True True]", "bounded_above": "[ True True True True True True]", "_shape": [6], "low": "[-1. -1. -1. -1. -1. -1.]", "high": "[1. 1. 1. 1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": "RandomNumberGenerator(PCG64)"}, "n_envs": 4, "num_timesteps": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1658706514.2633166, "learning_rate": 0.00096, "tensorboard_log": "./tensorboard", "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_episode_num": 0, "use_sde": true, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 62500, "n_steps": 8, "gamma": 0.99, "gae_lambda": 0.9, "ent_coef": 0.0, "vf_coef": 0.4, "max_grad_norm": 0.5, "normalize_advantage": false, "system_info": {"OS": "Linux-5.15.0-41-generic-x86_64-with-glibc2.29 #44~20.04.1-Ubuntu SMP Fri Jun 24 13:27:29 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.6.0", "PyTorch": "1.8.2+cu111", "GPU Enabled": "True", "Numpy": "1.23.1", "Gym": "0.24.0"}} |