| { | |
| "policy_class": { | |
| ":type:": "<class 'abc.ABCMeta'>", | |
| ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", | |
| "__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 0x7f5ddf981680>", | |
| "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f5ddf981710>", | |
| "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f5ddf9817a0>", | |
| "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f5ddf981830>", | |
| "_build": "<function ActorCriticPolicy._build at 0x7f5ddf9818c0>", | |
| "forward": "<function ActorCriticPolicy.forward at 0x7f5ddf981950>", | |
| "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f5ddf9819e0>", | |
| "_predict": "<function ActorCriticPolicy._predict at 0x7f5ddf981a70>", | |
| "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f5ddf981b00>", | |
| "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f5ddf981b90>", | |
| "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f5ddf981c20>", | |
| "__abstractmethods__": "frozenset()", | |
| "_abc_impl": "<_abc_data object at 0x7f5ddf9d0720>" | |
| }, | |
| "verbose": 1, | |
| "policy_kwargs": { | |
| ":type:": "<class 'dict'>", | |
| ":serialized:": "gASVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/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": 1661339569.9715025, | |
| "learning_rate": 0.00096, | |
| "tensorboard_log": "./tensorboard", | |
| "lr_schedule": { | |
| ":type:": "<class 'function'>", | |
| ":serialized:": "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" | |
| }, | |
| "_last_obs": { | |
| ":type:": "<class 'numpy.ndarray'>", | |
| ":serialized:": "gASVTQIAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwRLHIaUaAOMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiiULAAQAAxTT9PSpPgL/9MDM+4J2+P8JO+r5gpVU9VwoAv5IIh7/yRZ0/31jyu17efT6Sz8Y9jN+BvzbKnz+CxSA/Z3HtPu40kT4M888/AxwrPt23tb8WPIO/nrc0PvBdVD78YypAeateP8fr5D5wodw+hWigv4pgdT5NmgS/jJsCP7GKyz6k6bG/Z5hbP4r7Db/2Ism/CKZtP32QDEDftks/XrnHvs/rhb/4Wr4/klREP0ceOT9EiAa/KtxWPz/tRj+LWpc8SGzgPI7vgD+JMDG/l4QbP3mrXj/H6+Q+cKHcPoVooL+yorM+R0n/vke9BD+dU/E/3q57v9HQsj6OtzW/S0UVPVbqnT+WE7u8K1kovlXLWz0zEde/2gcZO4FDiT4HMxS+/kysPuqE2r8jq1O/ME8EP8gwjr8zqDC/odFlvkzcmb95q14/x+vkPnCh3D6FaKC/i/tsvyJPrr8I6oW+Q+WxPa3MzT4fhHK+OZyCvj8ct73Xx5k/Iu9vPi73vb552os+dvALv2rcpb+FI0Y/IcWHv2/CmD+x8RQ+FgBhPhB9OT8boaI9rfaXP3vEXr+inknA2yiTvx0kD8Bwodw+hWigv5R0lGIu" | |
| }, | |
| "_last_episode_starts": { | |
| ":type:": "<class 'numpy.ndarray'>", | |
| ":serialized:": "gASVjAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwSFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDBAAAAACUdJRiLg==" | |
| }, | |
| "_last_original_obs": { | |
| ":type:": "<class 'numpy.ndarray'>", | |
| ":serialized:": "gASVTQIAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwRLHIaUaAOMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiiULAAQAAAAAAAAK/pLYAAIA/AAAAAAAAAAAAAAAAAAAAAAAAAICOlsg9AAAAALxgAMAAAAAAhUXMvAAAAADkN/o/AAAAABJgZL0AAAAAlCPsPwAAAAA5+xY9AAAAAPbZ8r8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAB3/ZY2AACAPwAAAAAAAAAAAAAAAAAAAAAAAACAdbmmvQAAAADp5eG/AAAAAGtz7z0AAAAA503nPwAAAADzb489AAAAACMD3j8AAAAA6/qdPQAAAADNS+K/AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAZEectgAAgD8AAAAAAAAAAAAAAAAAAAAAAAAAgDXAqz0AAAAAkw3cvwAAAAC8sH09AAAAANHx9T8AAAAA9M0KvgAAAAA2b/Q/AAAAANIlJD0AAAAA6svcvwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABZ8PjYAAIA/AAAAAAAAAAAAAAAAAAAAAAAAAIDnqAU+AAAAALyS778AAAAAu1GQPQAAAABFpeQ/AAAAAJhVlj0AAAAA9jf5PwAAAABn59u9AAAAAOlN5r8AAAAAAAAAAAAAAAAAAAAAAAAAAJR0lGIu" | |
| }, | |
| "_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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg==" | |
| }, | |
| "_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 | |
| } |