| { | |
| "policy_class": { | |
| ":type:": "<class 'abc.ABCMeta'>", | |
| ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLnRkMy5wb2xpY2llc5SMCVREM1BvbGljeZSTlC4=", | |
| "__module__": "stable_baselines3.td3.policies", | |
| "__annotations__": "{'actor': <class 'stable_baselines3.td3.policies.Actor'>, 'actor_target': <class 'stable_baselines3.td3.policies.Actor'>, 'critic': <class 'stable_baselines3.common.policies.ContinuousCritic'>, 'critic_target': <class 'stable_baselines3.common.policies.ContinuousCritic'>}", | |
| "__doc__": "\n Policy class (with both actor and critic) for TD3.\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 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 :param n_critics: Number of critic networks to create.\n :param share_features_extractor: Whether to share or not the features extractor\n between the actor and the critic (this saves computation time)\n ", | |
| "__init__": "<function TD3Policy.__init__ at 0x7ae480dae4d0>", | |
| "_build": "<function TD3Policy._build at 0x7ae480dae560>", | |
| "_get_constructor_parameters": "<function TD3Policy._get_constructor_parameters at 0x7ae480dae5f0>", | |
| "make_actor": "<function TD3Policy.make_actor at 0x7ae480dae680>", | |
| "make_critic": "<function TD3Policy.make_critic at 0x7ae480dae710>", | |
| "forward": "<function TD3Policy.forward at 0x7ae480dae7a0>", | |
| "_predict": "<function TD3Policy._predict at 0x7ae480dae830>", | |
| "set_training_mode": "<function TD3Policy.set_training_mode at 0x7ae480dae8c0>", | |
| "__abstractmethods__": "frozenset()", | |
| "_abc_impl": "<_abc._abc_data object at 0x7ae480db0b40>" | |
| }, | |
| "verbose": 1, | |
| "policy_kwargs": { | |
| "net_arch": [ | |
| 400, | |
| 300 | |
| ] | |
| }, | |
| "num_timesteps": 1000339, | |
| "_total_timesteps": 1000000, | |
| "_num_timesteps_at_start": 0, | |
| "seed": 0, | |
| "action_noise": { | |
| ":type:": "<class 'stable_baselines3.common.noise.NormalActionNoise'>", | |
| ":serialized:": "gAWVOgEAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5ub2lzZZSMEU5vcm1hbEFjdGlvbk5vaXNllJOUKYGUfZQojANfbXWUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWMAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJmOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwaFlIwBQ5R0lFKUjAZfc2lnbWGUaAgoljAAAAAAAAAAmpmZmZmZuT+amZmZmZm5P5qZmZmZmbk/mpmZmZmZuT+amZmZmZm5P5qZmZmZmbk/lGgPSwaFlGgTdJRSlHViLg==", | |
| "_mu": "[0. 0. 0. 0. 0. 0.]", | |
| "_sigma": "[0.1 0.1 0.1 0.1 0.1 0.1]" | |
| }, | |
| "start_time": 1672252945185227909, | |
| "learning_rate": { | |
| ":type:": "<class 'function'>", | |
| ":serialized:": "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" | |
| }, | |
| "tensorboard_log": "runs/Walker2DBulletEnv-v0__td3__1035828328__1672252942/Walker2DBulletEnv-v0", | |
| "_last_obs": null, | |
| "_last_episode_starts": { | |
| ":type:": "<class 'numpy.ndarray'>", | |
| ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg==" | |
| }, | |
| "_last_original_obs": { | |
| ":type:": "<class 'numpy.ndarray'>", | |
| ":serialized:": "gAWVzQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJZYAAAAAAAAAA2MpL4AAAAAAACAPzNdZD8AAAAAlMjeuwAAAAAVNFO/NHf8u/z5Db7DPNY+K7sePnxtAj4V7jS/FgCAPyYZWre4gEm9RluovZkEgD9fXUS6AACAPwAAgD+UjAVudW1weZSMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwFLFoaUjAFDlHSUUpQu" | |
| }, | |
| "_episode_num": 2796, | |
| "use_sde": false, | |
| "sde_sample_freq": -1, | |
| "_current_progress_remaining": -0.00033900000000008923, | |
| "_stats_window_size": 100, | |
| "ep_info_buffer": { | |
| ":type:": "<class 'collections.deque'>", | |
| ":serialized:": "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" | |
| }, | |
| "ep_success_buffer": { | |
| ":type:": "<class 'collections.deque'>", | |
| ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg==" | |
| }, | |
| "_n_updates": 990341, | |
| "observation_space": { | |
| ":type:": "<class 'gymnasium.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 'gymnasium.spaces.box.Box'>", | |
| ":serialized:": "gAWVfgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWBgAAAAAAAAABAQEBAQGUaAiMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLBoWUjAFDlHSUUpSMDWJvdW5kZWRfYWJvdmWUaBEolgYAAAAAAAAAAQEBAQEBlGgVSwaFlGgZdJRSlIwGX3NoYXBllEsGhZSMA2xvd5RoESiWGAAAAAAAAAAAAIC/AACAvwAAgL8AAIC/AACAvwAAgL+UaAtLBoWUaBl0lFKUjARoaWdolGgRKJYYAAAAAAAAAAAAgD8AAIA/AACAPwAAgD8AAIA/AACAP5RoC0sGhZRoGXSUUpSMCGxvd19yZXBylIwELTEuMJSMCWhpZ2hfcmVwcpSMAzEuMJSMCl9ucF9yYW5kb22UjBRudW1weS5yYW5kb20uX3BpY2tsZZSMEF9fZ2VuZXJhdG9yX2N0b3KUk5SMBVBDRzY0lGgyjBRfX2JpdF9nZW5lcmF0b3JfY3RvcpSTlIaUUpR9lCiMDWJpdF9nZW5lcmF0b3KUjAVQQ0c2NJSMBXN0YXRllH2UKGg9ihDjYZWmt15YCS1Fllk0taEajANpbmOUihCpc3hEvDOBWIIa9zrb2o1BdYwKaGFzX3VpbnQzMpRLAIwIdWludGVnZXKUSwB1YnViLg==", | |
| "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": "Generator(PCG64)" | |
| }, | |
| "n_envs": 1, | |
| "buffer_size": 1, | |
| "batch_size": 100, | |
| "learning_starts": 10000, | |
| "tau": 0.005, | |
| "gamma": 0.98, | |
| "gradient_steps": -1, | |
| "optimize_memory_usage": false, | |
| "replay_buffer_class": { | |
| ":type:": "<class 'abc.ABCMeta'>", | |
| ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==", | |
| "__module__": "stable_baselines3.common.buffers", | |
| "__annotations__": "{'observations': <class 'numpy.ndarray'>, 'next_observations': <class 'numpy.ndarray'>, 'actions': <class 'numpy.ndarray'>, 'rewards': <class 'numpy.ndarray'>, 'dones': <class 'numpy.ndarray'>, 'timeouts': <class 'numpy.ndarray'>}", | |
| "__doc__": "\n Replay buffer used in off-policy algorithms like SAC/TD3.\n\n :param buffer_size: Max number of element in the buffer\n :param observation_space: Observation space\n :param action_space: Action space\n :param device: PyTorch device\n :param n_envs: Number of parallel environments\n :param optimize_memory_usage: Enable a memory efficient variant\n of the replay buffer which reduces by almost a factor two the memory used,\n at a cost of more complexity.\n See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n Cannot be used in combination with handle_timeout_termination.\n :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n separately and treat the task as infinite horizon task.\n https://github.com/DLR-RM/stable-baselines3/issues/284\n ", | |
| "__init__": "<function ReplayBuffer.__init__ at 0x7ae480cfa440>", | |
| "add": "<function ReplayBuffer.add at 0x7ae480cfa4d0>", | |
| "sample": "<function ReplayBuffer.sample at 0x7ae480cfa560>", | |
| "_get_samples": "<function ReplayBuffer._get_samples at 0x7ae480cfa5f0>", | |
| "_maybe_cast_dtype": "<staticmethod(<function ReplayBuffer._maybe_cast_dtype at 0x7ae480cfa680>)>", | |
| "__abstractmethods__": "frozenset()", | |
| "_abc_impl": "<_abc._abc_data object at 0x7ae480e70940>" | |
| }, | |
| "replay_buffer_kwargs": {}, | |
| "train_freq": { | |
| ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", | |
| ":serialized:": "gAWVZAAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMB2VwaXNvZGWUhZRSlIaUgZQu" | |
| }, | |
| "use_sde_at_warmup": false, | |
| "policy_delay": 2, | |
| "target_noise_clip": 0.5, | |
| "target_policy_noise": 0.2, | |
| "lr_schedule": { | |
| ":type:": "<class 'function'>", | |
| ":serialized:": "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" | |
| }, | |
| "actor_batch_norm_stats": [], | |
| "critic_batch_norm_stats": [], | |
| "actor_batch_norm_stats_target": [], | |
| "critic_batch_norm_stats_target": [] | |
| } |