| { | |
| "policy_class": { | |
| ":type:": "<class 'abc.ABCMeta'>", | |
| ":serialized:": "gAWVKgAAAAAAAACMGHNiM19jb250cmliLnRxYy5wb2xpY2llc5SMCVRRQ1BvbGljeZSTlC4=", | |
| "__module__": "sb3_contrib.tqc.policies", | |
| "__doc__": "\n Policy class (with both actor and critic) for TQC.\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 use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param use_expln: Use ``expln()`` function instead of ``exp()`` when using gSDE 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 clip_mean: Clip the mean output when using gSDE to avoid numerical instability.\n :param features_extractor_class: Features extractor to use.\n :param features_extractor_kwargs: Keyword arguments\n to pass to the feature 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_quantiles: Number of quantiles for the critic.\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 TQCPolicy.__init__ at 0x7f5d27f66670>", | |
| "_build": "<function TQCPolicy._build at 0x7f5d27f66700>", | |
| "_get_constructor_parameters": "<function TQCPolicy._get_constructor_parameters at 0x7f5d27f66790>", | |
| "reset_noise": "<function TQCPolicy.reset_noise at 0x7f5d27f66820>", | |
| "make_actor": "<function TQCPolicy.make_actor at 0x7f5d27f668b0>", | |
| "make_critic": "<function TQCPolicy.make_critic at 0x7f5d27f66940>", | |
| "forward": "<function TQCPolicy.forward at 0x7f5d27f669d0>", | |
| "_predict": "<function TQCPolicy._predict at 0x7f5d27f66a60>", | |
| "set_training_mode": "<function TQCPolicy.set_training_mode at 0x7f5d27f66af0>", | |
| "__abstractmethods__": "frozenset()", | |
| "_abc_impl": "<_abc._abc_data object at 0x7f5d27f67880>" | |
| }, | |
| "verbose": 1, | |
| "policy_kwargs": { | |
| "use_sde": false | |
| }, | |
| "observation_space": { | |
| ":type:": "<class 'gym.spaces.box.Box'>", | |
| ":serialized:": "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", | |
| "dtype": "float64", | |
| "_shape": [ | |
| 17 | |
| ], | |
| "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf]", | |
| "high": "[inf inf inf inf inf inf inf 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]", | |
| "bounded_above": "[False False False False False False False False False False False False\n False False False False False]", | |
| "_np_random": null | |
| }, | |
| "action_space": { | |
| ":type:": "<class 'gym.spaces.box.Box'>", | |
| ":serialized:": "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", | |
| "dtype": "float32", | |
| "_shape": [ | |
| 6 | |
| ], | |
| "low": "[-1. -1. -1. -1. -1. -1.]", | |
| "high": "[1. 1. 1. 1. 1. 1.]", | |
| "bounded_below": "[ True True True True True True]", | |
| "bounded_above": "[ True True True True True True]", | |
| "_np_random": "RandomState(MT19937)" | |
| }, | |
| "n_envs": 1, | |
| "num_timesteps": 1000000, | |
| "_total_timesteps": 1000000, | |
| "_num_timesteps_at_start": 0, | |
| "seed": 0, | |
| "action_noise": null, | |
| "start_time": 1675944947441087928, | |
| "learning_rate": 0.0003, | |
| "tensorboard_log": "runs/HalfCheetah-v3__tqc__2728733673__1675944942/HalfCheetah-v3", | |
| "lr_schedule": { | |
| ":type:": "<class 'function'>", | |
| ":serialized:": "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" | |
| }, | |
| "_last_obs": null, | |
| "_last_episode_starts": { | |
| ":type:": "<class 'numpy.ndarray'>", | |
| ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg==" | |
| }, | |
| "_last_original_obs": { | |
| ":type:": "<class 'numpy.ndarray'>", | |
| ":serialized:": "gAWV/QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaIAAAAAAAAAL2MpzSflL2/x4Ep7NXBGUCY55DTRFLZv/60G8/A1bY/jm2Qxb2Rxj/JUYNyUxvSP2ByFsMTh+I/+l1dujIq2j8n1QpM56PVvyUenP+94ME/ZoDprGFQ4r8KjqApFvYSwDO6EuOhiCBAeXSH0pSAG0BhgrRcKQIHwPmrvnVfIxZAE9QITq5/47+UjAVudW1weZSMBWR0eXBllJOUjAJmOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwFLEYaUjAFDlHSUUpQu" | |
| }, | |
| "_episode_num": 1000, | |
| "use_sde": false, | |
| "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": 990000, | |
| "buffer_size": 1, | |
| "batch_size": 256, | |
| "learning_starts": 10000, | |
| "tau": 0.005, | |
| "gamma": 0.99, | |
| "gradient_steps": 1, | |
| "optimize_memory_usage": false, | |
| "replay_buffer_class": { | |
| ":type:": "<class 'abc.ABCMeta'>", | |
| ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==", | |
| "__module__": "stable_baselines3.common.buffers", | |
| "__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 0x7f5d283ee5e0>", | |
| "add": "<function ReplayBuffer.add at 0x7f5d283ee670>", | |
| "sample": "<function ReplayBuffer.sample at 0x7f5d283ee700>", | |
| "_get_samples": "<function ReplayBuffer._get_samples at 0x7f5d283ee790>", | |
| "__abstractmethods__": "frozenset()", | |
| "_abc_impl": "<_abc._abc_data object at 0x7f5d283e5bc0>" | |
| }, | |
| "replay_buffer_kwargs": {}, | |
| "train_freq": { | |
| ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", | |
| ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu" | |
| }, | |
| "use_sde_at_warmup": false, | |
| "target_entropy": -6.0, | |
| "ent_coef": "auto", | |
| "target_update_interval": 1, | |
| "top_quantiles_to_drop_per_net": 2, | |
| "batch_norm_stats": [], | |
| "batch_norm_stats_target": [] | |
| } |