{"policy_class": {":type:": "", ":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__": "", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x794add91df80>"}, "verbose": 1, "policy_kwargs": {"use_sde": false}, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1743231793840632774, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "", ":serialized:": "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", "achieved_goal": "[[-0.86187166 0.7778266 0.08071917]\n [ 0.2357648 -1.188266 0.08069188]\n [-1.3440653 1.1867734 0.08069563]\n [ 2.4413092 -0.8617555 0.08069696]\n [-1.0374739 -0.9328455 0.08070773]\n [ 1.3504641 -0.96156967 0.08069188]\n [ 0.32262817 -0.5205036 0.08070773]\n [ 0.25908566 -0.60874397 0.08070773]\n [ 1.5445291 -0.4206057 0.08069188]\n [-0.98588693 1.4068902 0.08069188]]", "desired_goal": "[[ 0.22436635 0.11953397 1.7353624 ]\n [-0.13767943 1.6895953 -0.5573995 ]\n [-1.3020939 -0.7739395 -1.0841379 ]\n [ 1.4774456 0.33498535 -1.0841379 ]\n [ 1.1740149 -1.2957238 -0.9703703 ]\n [-0.7842453 -0.2660535 -1.0841379 ]\n [-0.38914332 0.4698535 0.91703755]\n [ 0.87104374 -0.4853505 -1.0841379 ]\n [-1.5840505 -0.5404762 1.6905969 ]\n [ 0.8789303 0.13908234 -1.0841379 ]]", "observation": "[[ 9.26254332e-01 -4.68446463e-01 -7.61146188e-01 3.50944817e-01\n 2.11578101e-01 7.53898844e-02 1.25929594e+00 -8.61871660e-01\n 7.77826607e-01 8.07191655e-02 -5.78950997e-03 -1.17445095e-02\n -5.76061616e-03 3.59803438e-03 7.73922948e-04 3.85112241e-02\n -2.47153896e-03 -1.46618439e-02 -5.48237469e-03]\n [ 7.16117442e-01 -1.22270608e+00 -4.97824103e-01 -1.23547629e-01\n -1.12763934e-01 -7.25993752e-01 1.25930321e+00 2.35764802e-01\n -1.18826604e+00 8.06918815e-02 -5.49738947e-03 -1.17001114e-02\n -6.27602078e-03 3.72752664e-03 1.27316322e-04 3.88005115e-02\n 1.07741856e-03 -1.22426888e-02 -5.74179459e-03]\n [ 3.82340610e-01 -3.08258712e-01 7.82692432e-02 -5.51852882e-01\n 2.42538571e-01 -3.13495231e+00 1.22633100e+00 -1.34406531e+00\n 1.18677342e+00 8.06956291e-02 -5.79506019e-03 -1.12875719e-02\n -5.81091503e-03 4.36424743e-03 -4.02831793e-04 3.90768722e-02\n 1.71639060e-03 -1.48725426e-02 -4.71196976e-03]\n [ 5.31303823e-01 7.04990387e-01 1.65961385e+00 1.29947513e-01\n 6.70419276e-01 6.61611617e-01 1.25929546e+00 2.44130921e+00\n -8.61755490e-01 8.06969628e-02 -5.54685853e-03 -1.18791331e-02\n 2.26659656e+00 4.12713829e-03 1.79946204e-04 3.88005115e-02\n 1.07741868e-03 -1.22426888e-02 -5.56749897e-03]\n [ 9.89386797e-01 -4.17079896e-01 -6.64745867e-01 -6.32557422e-02\n -4.18463610e-02 -4.94072050e-01 -9.71602023e-01 -1.03747392e+00\n -9.32845473e-01 8.07077289e-02 -5.93132572e-03 -1.14069441e-02\n -6.45558303e-03 4.14454658e-03 -9.44966061e-09 3.88005115e-02\n 1.07741798e-03 -1.22426888e-02 -5.71824005e-03]\n [ 2.94059336e-01 1.43608618e+00 4.33889419e-01 6.56322911e-02\n 2.85540968e-01 3.89552981e-01 -9.59261060e-01 1.35046411e+00\n -9.61569667e-01 8.06918815e-02 -5.49738901e-03 -1.17001114e-02\n -6.41393429e-03 3.72753874e-03 1.27321327e-04 3.88005115e-02\n 1.07741856e-03 -1.22426888e-02 -5.74183604e-03]\n [ 2.64718175e-01 1.40751517e+00 7.33158469e-01 7.57582247e-01\n -4.76219058e-01 -3.10054243e-01 1.25667739e+00 3.22628170e-01\n -5.20503581e-01 8.07077289e-02 -5.93132572e-03 -1.14069451e-02\n -6.34425273e-03 4.14454937e-03 -1.34478944e-08 3.88005115e-02\n 1.07741798e-03 -1.22426888e-02 -5.71822235e-03]\n [ 9.58167672e-01 -1.26221046e-01 -7.73545444e-01 1.78441480e-01\n -8.36981475e-01 7.42273927e-02 1.25914657e+00 2.59085655e-01\n -6.08743966e-01 8.07077289e-02 -5.93132572e-03 -1.14069469e-02\n -6.20820932e-03 4.14455310e-03 -1.83390672e-08 3.88005115e-02\n 1.07741798e-03 -1.22426888e-02 -5.71820093e-03]\n [ 8.55630159e-01 6.69627905e-01 2.12020844e-01 8.91492605e-01\n -1.58746147e+00 -1.06163941e-01 1.25930607e+00 1.54452908e+00\n -4.20605689e-01 8.06918815e-02 -5.49738761e-03 -1.17001114e-02\n -6.78289076e-03 3.72757134e-03 1.27334701e-04 3.88005115e-02\n 1.07741856e-03 -1.22426888e-02 -5.74194593e-03]\n [-5.69825828e-01 -2.27364445e+00 -7.99067616e-01 -8.09644282e-01\n -3.70152950e-01 -8.02540302e-01 6.39378726e-01 -9.85886931e-01\n 1.40689015e+00 8.06918815e-02 -5.49738901e-03 -1.17001114e-02\n -6.33716490e-03 3.72753199e-03 1.27318533e-04 3.88005115e-02\n 1.07741856e-03 -1.22426888e-02 -5.74181275e-03]]"}, "_last_episode_starts": {":type:": "", ":serialized:": "gAWVfgAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCgAAAAAAAAABAQEBAQEBAQEBlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksKhZSMAUOUdJRSlC4="}, "_last_original_obs": {":type:": "", ":serialized:": "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", "achieved_goal": "[[-0.08201155 0.079809 0.01998976]\n [ 0.02188749 -0.12501666 0.01998892]\n [-0.12765458 0.12241268 0.01998904]\n [ 0.23065783 -0.0910011 0.01998908]\n [-0.09863355 -0.09840719 0.01998941]\n [ 0.12740165 -0.10139965 0.01998892]\n [ 0.03010972 -0.0554498 0.01998941]\n [ 0.02409497 -0.0646426 0.01998941]\n [ 0.14577127 -0.04504254 0.01998892]\n [-0.09375048 0.14534423 0.01998892]]", "desired_goal": "[[ 0.01897507 0.00983629 0.20808423]\n [-0.01246791 0.1456723 0.05513785]\n [-0.11359507 -0.06746379 0.02 ]\n [ 0.1278026 0.02847636 0.02 ]\n [ 0.10145023 -0.11260667 0.02758925]\n [-0.06862092 -0.02352334 0.02 ]\n [-0.03430707 0.04014467 0.15349512]\n [ 0.07513776 -0.04249612 0.02 ]\n [-0.13808247 -0.0472654 0.20509799]\n [ 0.07582269 0.01152755 0.02 ]]", "observation": "[[ 1.85584083e-01 -8.78114775e-02 7.34649645e-03 4.50497977e-02\n 1.07121848e-01 -6.05666311e-04 7.99996331e-02 -8.20115507e-02\n 7.98089951e-02 1.99897643e-02 1.89273287e-05 5.09898928e-06\n 8.63264213e-05 -2.67155337e-05 4.18620511e-05 -2.00828363e-05\n -1.88058650e-03 -1.19296403e-03 1.36410657e-04]\n [ 1.43722594e-01 -3.04382116e-01 4.73696142e-02 -8.59023035e-02\n -2.36320533e-02 -3.22514564e-01 7.99998939e-02 2.18874887e-02\n -1.25016659e-01 1.99889243e-02 6.71599701e-05 9.25230142e-06\n -7.47562226e-05 -2.02290939e-05 -2.26382986e-06 -2.96860800e-12\n 1.86401394e-10 4.98065096e-11 -1.19936602e-04]\n [ 7.72307068e-02 -4.18167561e-02 1.34931788e-01 -2.04107508e-01\n 1.19603120e-01 -1.29017246e+00 7.88175166e-02 -1.27654582e-01\n 1.22412682e-01 1.99890397e-02 1.80109455e-05 4.78446673e-05\n 7.06060891e-05 1.16650735e-05 -3.84423220e-05 1.91853087e-05\n 3.38590413e-04 -1.29686622e-03 8.97690363e-04]\n [ 1.06905758e-01 2.49117538e-01 3.75285149e-01 -1.59418192e-02\n 2.92097181e-01 2.34874561e-01 7.99996182e-02 2.30657831e-01\n -9.10011008e-02 1.99890807e-02 5.89919655e-05 -7.49477886e-06\n 7.10280001e-01 -2.12019231e-07 1.32775062e-06 -6.00685127e-12\n 2.84217594e-10 2.07274295e-10 5.22945702e-05]\n [ 1.98160738e-01 -7.30625913e-02 2.19986662e-02 -6.92627355e-02\n 4.95736115e-03 -2.29353622e-01 8.04334555e-09 -9.86335501e-02\n -9.84071866e-02 1.99894123e-02 -4.48815081e-06 3.66776039e-05\n -1.30875924e-04 6.59965508e-07 -1.09528255e-05 -4.00052907e-12\n -6.76667819e-11 2.51379390e-10 -9.66607986e-05]\n [ 5.96441403e-02 4.59037155e-01 1.88983575e-01 -3.36917602e-02\n 1.36938930e-01 1.25590935e-01 4.42553224e-04 1.27401650e-01\n -1.01399645e-01 1.99889243e-02 6.71600355e-05 9.25231870e-06\n -1.17859156e-04 -2.02284864e-05 -2.26348902e-06 -2.95564961e-12\n 1.86286264e-10 4.97718186e-11 -1.19977311e-04]\n [ 5.37990741e-02 4.50833559e-01 2.34470382e-01 1.57275036e-01\n -1.70153841e-01 -1.55435249e-01 7.99057335e-02 3.01097203e-02\n -5.54498024e-02 1.99894123e-02 -4.48812671e-06 3.66775130e-05\n -9.60811303e-05 6.60121430e-07 -1.09530984e-05 -3.99806230e-12\n -6.74729786e-11 2.51800997e-10 -9.66434818e-05]\n [ 1.91941559e-01 1.04517341e-02 5.46189304e-03 -2.55828188e-03\n -3.15590113e-01 -1.07262982e-03 7.99942762e-02 2.40949728e-02\n -6.46426007e-02 1.99894123e-02 -4.48809715e-06 3.66774002e-05\n -5.35626350e-05 6.60311855e-07 -1.09534321e-05 -4.01434441e-12\n -6.73678682e-11 2.51628579e-10 -9.66223088e-05]\n [ 1.71515003e-01 2.38963917e-01 1.55261099e-01 1.94232091e-01\n -6.18135512e-01 -7.35342726e-02 7.99999982e-02 1.45771265e-01\n -4.50425372e-02 1.99889243e-02 6.71602102e-05 9.25236691e-06\n -2.33171420e-04 -2.02268566e-05 -2.26257634e-06 -2.94866909e-12\n 1.84873825e-10 4.96204709e-11 -1.20086246e-04]\n [-1.12450942e-01 -6.06138110e-01 1.58269797e-03 -2.75253683e-01\n -1.27394795e-01 -3.53262663e-01 5.77695072e-02 -9.37504768e-02\n 1.45344228e-01 1.99889243e-02 6.71599992e-05 9.25230870e-06\n -9.38659359e-05 -2.02288247e-05 -2.26367888e-06 -2.95858130e-12\n 1.86482829e-10 5.00874724e-11 -1.19954653e-04]]"}, "_episode_num": 20665, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "_stats_window_size": 100, "ep_info_buffer": {":type:": "", ":serialized:": "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"}, "ep_success_buffer": {":type:": "", ":serialized:": "gAWVhgAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKImJiYiJiYmJiYmJiImJiYmJiYmIiYmJiYmJiImIiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYiJiYmJiYmJiYmJiImJiYmJiYmJiYllLg=="}, "_n_updates": 99990, "buffer_size": 1000000, "batch_size": 256, "learning_starts": 100, "tau": 0.005, "gamma": 0.99, "gradient_steps": 1, "optimize_memory_usage": false, "replay_buffer_class": {":type:": "", ":serialized:": "gAWVOQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwQRGljdFJlcGxheUJ1ZmZlcpSTlC4=", "__module__": "stable_baselines3.common.buffers", "__annotations__": "{'observation_space': , 'obs_shape': dict[str, tuple[int, ...]], 'observations': dict[str, numpy.ndarray], 'next_observations': dict[str, numpy.ndarray]}", "__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__": "", "add": "", "sample": "", "_get_samples": "", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x794addbc1780>"}, "replay_buffer_kwargs": {}, "train_freq": {":type:": "", ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"}, "use_sde_at_warmup": false, "target_entropy": -4.0, "ent_coef": "auto", "target_update_interval": 1, "observation_space": {":type:": "", ":serialized:": "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", "spaces": "{'achieved_goal': Box(-10.0, 10.0, (3,), float32), 'desired_goal': Box(-10.0, 10.0, (3,), float32), 'observation': Box(-10.0, 10.0, (19,), float32)}", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "", ":serialized:": "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", "dtype": "float32", "_shape": [4], "low": "[-1. -1. -1. -1.]", "bounded_below": "[ True True True True]", "high": "[1. 1. 1. 1.]", "bounded_above": "[ True True True True]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": "Generator(PCG64)"}, "n_envs": 10, "lr_schedule": {":type:": "", ":serialized:": "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"}, "batch_norm_stats": [], "batch_norm_stats_target": [], "system_info": {"OS": "Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.11.11", "Stable-Baselines3": "2.6.0", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "Gymnasium": "1.1.1", "OpenAI Gym": "0.25.2"}}