| {"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 0x7f4072081820>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f40720818b0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4072081940>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f40720819d0>", "_build": "<function ActorCriticPolicy._build at 0x7f4072081a60>", "forward": "<function ActorCriticPolicy.forward at 0x7f4072081af0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f4072081b80>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4072081c10>", "_predict": "<function ActorCriticPolicy._predict at 0x7f4072081ca0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4072081d30>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4072081dc0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4072081e50>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f4072082a40>"}, "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", "_shape": [28], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -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 inf inf inf inf inf inf]", "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 False False\n 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 False False\n False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAIC/AACAvwAAgL8AAIC/AACAvwAAgL8AAIC/AACAv5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIA/AACAPwAAgD8AAIA/AACAPwAAgD8AAIA/AACAP5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAQEBAQEBAQGUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAEBAQEBAQEBlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "dtype": "float32", "_shape": [8], "low": "[-1. -1. -1. -1. -1. -1. -1. -1.]", "high": "[1. 1. 1. 1. 1. 1. 1. 1.]", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_np_random": null}, "n_envs": 4, "num_timesteps": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1678867625926696547, "learning_rate": 0.00096, "tensorboard_log": null, "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:": "gAWVNQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJbAAQAAAAAAAAAAAABKxZ01AACAPwAAAAAAAAAAAAAAAAAAAAAAAACAEGHQvAAAAAD//fu/AAAAACak370AAAAAmXnhPwAAAAD6exY9AAAAADQ0/T8AAAAAiljFvQAAAAADRvG/AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAleSmtQAAgD8AAAAAAAAAAAAAAAAAAAAAAAAAgHH4ijwAAAAA9dPkvwAAAAAGFwg+AAAAAD666D8AAAAAjumNvQAAAAASz+o/AAAAAOxxzD0AAAAAu9EAwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAGplOLUAAIA/AAAAAAAAAAAAAAAAAAAAAAAAAIDbeWQ8AAAAAG5g3L8AAAAAn5f/vQAAAACIxus/AAAAAB2a1DsAAAAAfYXvPwAAAACPDs69AAAAAARq3b8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACNBI80AACAPwAAAAAAAAAAAAAAAAAAAAAAAACAUEQyvQAAAAB//du/AAAAAOeq0z0AAAAAWnT+PwAAAADPeRa8AAAAAAUY/D8AAAAAbFEBPgAAAABE+eK/AAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwRLHIaUjAFDlHSUUpQu"}, "_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-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}} |