| { | |
| "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 0x7ff4a3975dc0>", | |
| "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff4a3975e50>", | |
| "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff4a3975ee0>", | |
| "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff4a3975f70>", | |
| "_build": "<function ActorCriticPolicy._build at 0x7ff4a3978040>", | |
| "forward": "<function ActorCriticPolicy.forward at 0x7ff4a39780d0>", | |
| "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff4a3978160>", | |
| "_predict": "<function ActorCriticPolicy._predict at 0x7ff4a39781f0>", | |
| "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff4a3978280>", | |
| "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff4a3978310>", | |
| "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff4a39783a0>", | |
| "__abstractmethods__": "frozenset()", | |
| "_abc_impl": "<_abc._abc_data object at 0x7ff4a3ab4f40>" | |
| }, | |
| "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": 200064, | |
| "_total_timesteps": 200000, | |
| "_num_timesteps_at_start": 0, | |
| "seed": null, | |
| "action_noise": null, | |
| "start_time": 1659070176.2426794, | |
| "learning_rate": 0.00096, | |
| "tensorboard_log": "work_dirs/AntBulletEnv-v0/tensorboard", | |
| "lr_schedule": { | |
| ":type:": "<class 'function'>", | |
| ":serialized:": "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" | |
| }, | |
| "_last_obs": { | |
| ":type:": "<class 'numpy.ndarray'>", | |
| ":serialized:": "gAWVNQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJbAAQAAAAAAALexDT/Jd+y+Ut7EPoL2i70bncu9WokFPl+Ymb7hy18+EaFgPxTlirzKcyS+H/NKvbHdLj/NQo28lJXCvr7LUT3DOaI/6ANTu+GlrD4sVgE9Qw1AvyMsFbxF3zE+U+eLvLKC4j5QQus+2zncv+9JwD52ffs+5UTLvzZDQL/er4M/0PKEvrUUDj59fIC+NQScPv6oYD/DpoC8y4Aivlw/Gr3loTU/dSvYvcqnBb9c3dE910lSPzl1br4Hcw6/fpVJvVuWnb6eq7u+neA5vhjZGz6yguI+UELrPujKFD/vScA+bmWivfKfOj9R77U+GcjuvWZJmbzY9iI+2A20vUl+Cj45dGA/fiCGvAEnHr5c4Re9s4slv1o+B7o/KUc+6uklPVRkST+fInS6/uSbvVskCz25PTi/V9gcPHCjuL46pEW9soLiPlBC6z7oyhQ/70nAPoYOcb+8tWi+hWzvPvwGqb3er+E6w8ASPgJvEz4FOp+9+xRhP0IkI7zcyyG+KO0ovXr+ib9eD4Q7xWICP072Gz3Zs0y/gqkHOnRsjT6dqBE9PJE/v/OhvzukxGS/b5tuvbKC4j5QQus+6MoUP+9JwD6UjAVudW1weZSMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwRLHIaUjAFDlHSUUpQu" | |
| }, | |
| "_last_episode_starts": { | |
| ":type:": "<class 'numpy.ndarray'>", | |
| ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg==" | |
| }, | |
| "_last_original_obs": { | |
| ":type:": "<class 'numpy.ndarray'>", | |
| ":serialized:": "gAWVNQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJbAAQAAAAAAAAAAAAAyKbE2AACAPwAAAAAAAAAAAAAAAAAAAAAAAACAjUGZvQAAAAB+huW/AAAAABcKbD0AAAAAyp7lPwAAAABdFOM9AAAAADnv6D8AAAAAz7xhPAAAAAAvmADAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAALP2ktQAAgD8AAAAAAAAAAAAAAAAAAAAAAAAAgBuKRb0AAAAAJEEAwAAAAAC+R+U8AAAAAGRX7D8AAAAAieWlOwAAAAD9buY/AAAAAHqpBT4AAAAA1mjmvwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAALLIiTYAAIA/AAAAAAAAAAAAAAAAAAAAAAAAAIDR+O69AAAAAOSb9r8AAAAANLckvQAAAADxOvc/AAAAAOgctj0AAAAAdvnpPwAAAAC13gS8AAAAAEBr8r8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAD4rX+2AACAPwAAAAAAAAAAAAAAAAAAAAAAAACAZJhfPQAAAAACefy/AAAAAKeGf70AAAAAshr0PwAAAAC+dHq8AAAAAI22+D8AAAAA9aQLPQAAAAAgauy/AAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwRLHIaUjAFDlHSUUpQu" | |
| }, | |
| "_episode_num": 0, | |
| "use_sde": true, | |
| "sde_sample_freq": -1, | |
| "_current_progress_remaining": -0.000320000000000098, | |
| "ep_info_buffer": { | |
| ":type:": "<class 'collections.deque'>", | |
| ":serialized:": "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" | |
| }, | |
| "ep_success_buffer": { | |
| ":type:": "<class 'collections.deque'>", | |
| ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg==" | |
| }, | |
| "_n_updates": 1563, | |
| "n_steps": 32, | |
| "gamma": 0.99, | |
| "gae_lambda": 0.9, | |
| "ent_coef": 0.0, | |
| "vf_coef": 0.4, | |
| "max_grad_norm": 0.5, | |
| "normalize_advantage": false | |
| } |