| { | |
| "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 0x7f01ad3dbe50>", | |
| "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f01ad3dbee0>", | |
| "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f01ad3dbf70>", | |
| "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f01ad3e2040>", | |
| "_build": "<function ActorCriticPolicy._build at 0x7f01ad3e20d0>", | |
| "forward": "<function ActorCriticPolicy.forward at 0x7f01ad3e2160>", | |
| "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f01ad3e21f0>", | |
| "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f01ad3e2280>", | |
| "_predict": "<function ActorCriticPolicy._predict at 0x7f01ad3e2310>", | |
| "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f01ad3e23a0>", | |
| "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f01ad3e2430>", | |
| "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f01ad3e24c0>", | |
| "__abstractmethods__": "frozenset()", | |
| "_abc_impl": "<_abc_data object at 0x7f01ad3d6b70>" | |
| }, | |
| "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:": "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", | |
| "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": 1675731678184346462, | |
| "learning_rate": 0.0007, | |
| "tensorboard_log": null, | |
| "lr_schedule": { | |
| ":type:": "<class 'function'>", | |
| ":serialized:": "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" | |
| }, | |
| "_last_obs": { | |
| ":type:": "<class 'numpy.ndarray'>", | |
| ":serialized:": "gAWVNQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJbAAQAAAAAAAGm5jj6KYku/0usIPvOQnT//L3C+Si9LPxRUHb2B7I6/V9CXPztatr6/g3s/M1lxv1ffpL93Eng+gW3/vV6vPr/cSJm+W88Ju4CsNj+fEXu/dO4Tv8YfKD9mUSO/h07qPl2AXz+PKMg+zlHFPpLzj7/yuCw9985Zv4Wrpj08xN0/ud+XPkZEEb6C2qg+479xvnGVWT9MARzAlZD5PoTGhL6LarG/juGpPC9LFL+IouU+Y57aPVGc8b9K19o+DC9oP7dTF78+hIK/5+7Pvm/9Lz9dgF8/jyjIPs5RxT6S84+/AEHvvU6wSb+2/g4+PWBcPxIvvL0u8a8+On1bvnPifb9dHCs/WnPOPjacGz94NBw/2qSKvxKPAcCTpRM/Sl1ovy9R8z1H0nO/irsJP9+CkD9r1GO/cBTtPuoAkL6OV+q/XYBfP9a1I8DOUcU+kvOPv9vqUz2Rsxu/xOuQPvQ0sj9s3cI/vrUuP2/UCb19LTq/VEBSP7kBiT9dyCo/aQ9JP51yEj0MAKS/3IEMPzj8jL89QxU/3zphvzAzjz535rE/Jt9Dv36ONj91PLy+mUDcv12AXz+PKMg+zlHFPpLzj7+UjAVudW1weZSMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwRLHIaUjAFDlHSUUpQu" | |
| }, | |
| "_last_episode_starts": { | |
| ":type:": "<class 'numpy.ndarray'>", | |
| ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg==" | |
| }, | |
| "_last_original_obs": { | |
| ":type:": "<class 'numpy.ndarray'>", | |
| ":serialized:": "gAWVNQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJbAAQAAAAAAAAAAAAAcMwQ3AACAPwAAAAAAAAAAAAAAAAAAAAAAAACACW4xvQAAAADekvW/AAAAACnMCz4AAAAAMRbrPwAAAAB/x8s9AAAAAHa3+T8AAAAAgMBwvQAAAAD8Bv6/AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAYDs1tQAAgD8AAAAAAAAAAAAAAAAAAAAAAAAAgP5/HT0AAAAAtv3wvwAAAAA71n87AAAAALz05z8AAAAAkDTMPAAAAABkId4/AAAAAIfulTwAAAAAXT/2vwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAFSfV7YAAIA/AAAAAAAAAAAAAAAAAAAAAAAAAIDkyD49AAAAAHdO2r8AAAAA79OYvQAAAACi7OM/AAAAAA6y/r0AAAAA0gruPwAAAAAZA+i9AAAAAEWy+78AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABnsp+0AACAPwAAAAAAAAAAAAAAAAAAAAAAAACA6ZqIPAAAAABe2++/AAAAACL0PjsAAAAAQE/ePwAAAAAchNY9AAAAAHSw7j8AAAAAgxrGPQAAAABT8/2/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 | |
| } |