File size: 24,654 Bytes
245902b |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 |
{
"policy_class": {
":type:": "<class 'abc.ABCMeta'>",
":serialized:": "gAWVNwAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLnNhYy5wb2xpY2llc5SMEE11bHRpSW5wdXRQb2xpY3mUk5Qu",
"__module__": "stable_baselines3.sac.policies",
"__doc__": "\n Policy class (with both actor and critic) for SAC.\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 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 MultiInputPolicy.__init__ at 0x7f2ab4c51670>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc._abc_data object at 0x7f2ab4c52280>"
},
"verbose": 1,
"policy_kwargs": {
"net_arch": [
300,
200
],
"use_sde": true
},
"observation_space": {
":type:": "<class 'gym.spaces.dict.Dict'>",
":serialized:": "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",
"spaces": "OrderedDict([('achieved_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('desired_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('observation', Box([-10. -10. -10. -10. -10. -10. -10. -10. -10. -10. -10. -10. -10. -10.\n -10. -10. -10. -10. -10.], [10. 10. 10. 10. 10. 10. 10. 10. 10. 10. 10. 10. 10. 10. 10. 10. 10. 10.\n 10.], (19,), float32))])",
"_shape": null,
"dtype": null,
"_np_random": null
},
"action_space": {
":type:": "<class 'gym.spaces.box.Box'>",
":serialized:": "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",
"dtype": "float32",
"_shape": [
4
],
"low": "[-1. -1. -1. -1.]",
"high": "[1. 1. 1. 1.]",
"bounded_below": "[ True True True True]",
"bounded_above": "[ True True True True]",
"_np_random": "RandomState(MT19937)"
},
"n_envs": 1,
"num_timesteps": 100000,
"_total_timesteps": 100000,
"_num_timesteps_at_start": 0,
"seed": null,
"action_noise": null,
"start_time": 1676852747940045143,
"learning_rate": 0.0005,
"tensorboard_log": null,
"lr_schedule": {
":type:": "<class 'function'>",
":serialized:": "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"
},
"_last_obs": {
":type:": "<class 'collections.OrderedDict'>",
":serialized:": "gAWVXwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QolgwAAAAAAAAAwbECPIkBUT0K16M8lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcolgwAAAAAAAAAKWnDvdXf3T2hdQo+lGgOSwFLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWTAAAAAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAAAAAAAAwbECPIkBUT0K16M8AAAAAAAAAIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlGgOSwFLE4aUaBJ0lFKUdS4=",
"achieved_goal": "[[0.00797695 0.05102685 0.02 ]]",
"desired_goal": "[[-0.09541542 0.10833708 0.13521434]]",
"observation": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00 0.0000000e+00 7.9769501e-03\n 5.1026855e-02 2.0000000e-02 0.0000000e+00 -0.0000000e+00\n 0.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n 0.0000000e+00 0.0000000e+00 0.0000000e+00]]"
},
"_last_episode_starts": {
":type:": "<class 'numpy.ndarray'>",
":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
},
"_last_original_obs": {
":type:": "<class 'collections.OrderedDict'>",
":serialized:": "gAWVXwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QolgwAAAAAAAAAwbECPIkBUT0K16M8lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcolgwAAAAAAAAAKWnDvdXf3T2hdQo+lGgOSwFLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWTAAAAAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAAAAAAAAwbECPIkBUT0K16M8AAAAAAAAAIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlGgOSwFLE4aUaBJ0lFKUdS4=",
"achieved_goal": "[[0.00797695 0.05102685 0.02 ]]",
"desired_goal": "[[-0.09541542 0.10833708 0.13521434]]",
"observation": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00 0.0000000e+00 7.9769501e-03\n 5.1026855e-02 2.0000000e-02 0.0000000e+00 -0.0000000e+00\n 0.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n 0.0000000e+00 0.0000000e+00 0.0000000e+00]]"
},
"_episode_num": 2000,
"use_sde": true,
"sde_sample_freq": 8,
"_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:": "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"
},
"_n_updates": 99900,
"buffer_size": 1000000,
"batch_size": 256,
"learning_starts": 100,
"tau": 0.005,
"gamma": 0.95,
"gradient_steps": 1,
"optimize_memory_usage": false,
"replay_buffer_class": {
":type:": "<class 'abc.ABCMeta'>",
":serialized:": "gAWVOQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwQRGljdFJlcGxheUJ1ZmZlcpSTlC4=",
"__module__": "stable_baselines3.common.buffers",
"__doc__": "\n Dict Replay buffer used in off-policy algorithms like SAC/TD3.\n Extends the ReplayBuffer to use dictionary observations\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 Disabled for now (see https://github.com/DLR-RM/stable-baselines3/pull/243#discussion_r531535702)\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 DictReplayBuffer.__init__ at 0x7f2ab4c9b430>",
"add": "<function DictReplayBuffer.add at 0x7f2ab4c9b4c0>",
"sample": "<function DictReplayBuffer.sample at 0x7f2ab4c9b550>",
"_get_samples": "<function DictReplayBuffer._get_samples at 0x7f2ab4c9b5e0>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc._abc_data object at 0x7f2ab4c9e200>"
},
"replay_buffer_kwargs": {},
"train_freq": {
":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"
},
"use_sde_at_warmup": false,
"target_entropy": {
":type:": "<class 'numpy.float32'>",
":serialized:": "gAWVZQAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMEAACAwJSGlFKULg=="
},
"ent_coef": "auto",
"target_update_interval": 1,
"batch_norm_stats": [],
"batch_norm_stats_target": []
} |