File size: 18,814 Bytes
afaac09 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 |
{
"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 0x7ff9203a6670>",
"_build": "<function TQCPolicy._build at 0x7ff9203a6700>",
"_get_constructor_parameters": "<function TQCPolicy._get_constructor_parameters at 0x7ff9203a6790>",
"reset_noise": "<function TQCPolicy.reset_noise at 0x7ff9203a6820>",
"make_actor": "<function TQCPolicy.make_actor at 0x7ff9203a68b0>",
"make_critic": "<function TQCPolicy.make_critic at 0x7ff9203a6940>",
"forward": "<function TQCPolicy.forward at 0x7ff9203a69d0>",
"_predict": "<function TQCPolicy._predict at 0x7ff9203a6a60>",
"set_training_mode": "<function TQCPolicy.set_training_mode at 0x7ff9203a6af0>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc._abc_data object at 0x7ff9203a90c0>"
},
"verbose": 1,
"policy_kwargs": {
"use_sde": false
},
"observation_space": {
":type:": "<class 'gym.spaces.box.Box'>",
":serialized:": "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",
"dtype": "float64",
"_shape": [
8
],
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
"high": "[inf inf inf inf inf inf inf inf]",
"bounded_below": "[False False False False False False False False]",
"bounded_above": "[False False False False False False False False]",
"_np_random": null
},
"action_space": {
":type:": "<class 'gym.spaces.box.Box'>",
":serialized:": "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",
"dtype": "float32",
"_shape": [
2
],
"low": "[-1. -1.]",
"high": "[1. 1.]",
"bounded_below": "[ True True]",
"bounded_above": "[ 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": 1676710084880565805,
"learning_rate": 0.0003,
"tensorboard_log": "runs/Swimmer-v3__tqc__3962785800__1676710082/Swimmer-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:": "gAWVtQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJZAAAAAAAAAAOx7Klbsp+m/LbYKYEck8T81IONgTRnfPzTlgaG78s0/EXRC9zek47+2YubEF0G0P3X/vTX2Pv+/bUJMzhraEUCUjAVudW1weZSMBWR0eXBllJOUjAJmOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwFLCIaUjAFDlHSUUpQu"
},
"_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": 0.9999,
"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 0x7ff92082e5e0>",
"add": "<function ReplayBuffer.add at 0x7ff92082e670>",
"sample": "<function ReplayBuffer.sample at 0x7ff92082e700>",
"_get_samples": "<function ReplayBuffer._get_samples at 0x7ff92082e790>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc._abc_data object at 0x7ff920829300>"
},
"replay_buffer_kwargs": {},
"train_freq": {
":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"
},
"use_sde_at_warmup": false,
"target_entropy": -2.0,
"ent_coef": "auto",
"target_update_interval": 1,
"top_quantiles_to_drop_per_net": 2,
"batch_norm_stats": [],
"batch_norm_stats_target": []
} |