| {"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVMQAAAAAAAACMGHNiM19jb250cmliLnRxYy5wb2xpY2llc5SMEE11bHRpSW5wdXRQb2xpY3mUk5Qu", "__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 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 MultiInputPolicy.__init__ at 0x7a3d089949a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7a3d08983400>"}, "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": 1760763312620457247, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[-1.22841 0.21497735 0.07748517]\n [-1.0206103 -1.2185386 0.07748652]\n [ 0.72022736 -0.8737733 0.07747305]\n [-0.30107504 0.288914 0.0774821 ]]", "desired_goal": "[[ 0.36112392 0.17634115 1.096211 ]\n [ 0.24654493 0.8519841 -1.0753653 ]\n [ 0.9241863 -0.9614184 0.9792167 ]\n [ 1.4680223 1.1964501 1.6995735 ]]", "observation": "[[ 8.1903350e-01 -1.5916234e+00 -1.0355302e+00 4.8066604e-01\n -5.6455927e-03 -1.9051181e-02 1.0440358e+00 -1.2284100e+00\n 2.1497735e-01 7.7485166e-02 -1.2431941e-03 7.4064187e-03\n -7.3137465e-03 4.9841408e-02 5.3002536e-03 3.5884127e-02\n -2.9878113e-03 -6.0057766e-03 3.6642880e-03]\n [-1.1180477e-01 3.6763445e-02 4.2043820e-01 -7.4854606e-01\n 6.1243820e-01 1.8104994e+00 -1.1248100e+00 -1.0206103e+00\n -1.2185386e+00 7.7486522e-02 -1.3883171e-03 7.1634217e-03\n -8.4401639e-03 4.9815588e-02 4.9523055e-03 3.6471937e-02\n -1.8438983e-03 -7.1523814e-03 3.3158229e-03]\n [ 2.6877752e-01 -1.4341365e-01 -4.5159675e-02 5.1730669e-01\n -2.1579850e+00 2.2839868e+00 1.0466014e+00 7.2022736e-01\n -8.7377328e-01 7.7473052e-02 -1.2136886e-03 7.5690136e-03\n -7.9945559e-03 5.0655846e-02 4.1805613e-03 3.6230877e-02\n 2.4649274e-04 -4.4204802e-03 4.2749229e-03]\n [ 1.0988108e+00 -2.2458230e-01 -1.0394250e+00 4.5175353e-01\n 1.4150310e+00 -6.1593980e-02 -1.1247891e+00 -3.0107504e-01\n 2.8891400e-01 7.7482097e-02 -1.2730256e-03 7.2372453e-03\n -8.8396622e-03 4.9885653e-02 4.3727886e-03 3.6178038e-02\n 1.4142576e-04 -4.0141563e-03 3.1020730e-03]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVeAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWBAAAAAAAAAABAQEBlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksEhZSMAUOUdJRSlC4="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[-0.1362879 0.02174678 0.01998976]\n [-0.11413451 -0.12639943 0.01998981]\n [ 0.07145511 -0.09076978 0.0199894 ]\n [-0.0374253 0.02938773 0.01998967]]", "desired_goal": "[[ 0.03147329 0.01508628 0.16440853]\n [ 0.02153436 0.07355513 0.02 ]\n [ 0.08031504 -0.08337326 0.15662849]\n [ 0.12748905 0.10336456 0.20453179]]", "observation": "[[ 9.1734312e-02 -4.0247214e-01 7.7497778e-03 3.5547987e-02\n 4.6066485e-02 2.3852637e-02 7.9762131e-02 -1.3628790e-01\n 2.1746777e-02 1.9989764e-02 1.8927873e-05 5.0990920e-06\n 3.7329859e-04 -2.6726571e-05 4.1854826e-05 -2.0083484e-05\n -1.8802858e-03 -1.1934903e-03 1.3668372e-04]\n [-2.1340416e-01 1.1896842e-01 3.4815910e-01 -3.7102857e-01\n 3.0056581e-01 8.1123072e-01 1.0653784e-07 -1.1413451e-01\n -1.2639943e-01 1.9989805e-02 -7.4845884e-06 -2.2688648e-05\n -6.8077461e-05 -2.8612207e-05 1.8605071e-05 2.0082765e-05\n -1.1929304e-03 -1.8806076e-03 -2.9793309e-04]\n [-8.8645324e-02 6.1272278e-02 2.3930107e-01 4.7667317e-02\n -8.4017074e-01 1.0150040e+00 7.9856485e-02 7.1455106e-02\n -9.0769775e-02 1.9989397e-02 2.4297900e-05 2.3692506e-05\n 1.0652987e-04 3.2759133e-05 -3.2962533e-05 3.6105332e-06\n 6.3145519e-05 -2.4348134e-04 8.9828676e-04]\n [ 1.8344823e-01 3.5280526e-02 6.8391724e-03 2.5984824e-02\n 6.3103765e-01 5.5436241e-03 8.7081247e-07 -3.7425302e-02\n 2.9387733e-02 1.9989671e-02 1.3498514e-05 -1.4246601e-05\n -2.2461711e-04 -2.3494806e-05 -2.0117981e-05 1.2986452e-11\n 1.2789323e-08 1.3500625e-08 -5.6452869e-04]]"}, "_episode_num": 20694, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVhgAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKImJiYmJiYmJiYmJiYmJiYmJiYmJiYiJiYmJiYmJiYmJiYmJiYmJiYmJiYmIiYmJiYmIiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYllLg=="}, "_n_updates": 249975, "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:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwQRGljdFJlcGxheUJ1ZmZlcpSTlC4=", "__module__": "stable_baselines3.common.buffers", "__annotations__": "{'observation_space': <class 'gymnasium.spaces.dict.Dict'>, '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__": "<function DictReplayBuffer.__init__ at 0x7a3d08da6520>", "add": "<function DictReplayBuffer.add at 0x7a3d08da6660>", "sample": "<function DictReplayBuffer.sample at 0x7a3d08da6700>", "_get_samples": "<function DictReplayBuffer._get_samples at 0x7a3d08da67a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7a3d08d36d00>"}, "replay_buffer_kwargs": {}, "n_steps": 1, "train_freq": {":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"}, "use_sde_at_warmup": false, "target_entropy": -4.0, "ent_coef": "auto", "target_update_interval": 1, "top_quantiles_to_drop_per_net": 2, "observation_space": {":type:": "<class 'gymnasium.spaces.dict.Dict'>", ":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:": "<class 'gymnasium.spaces.box.Box'>", ":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": 4, "lr_schedule": {":type:": "<class 'stable_baselines3.common.utils.FloatSchedule'>", ":serialized:": "gAWVeQAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMDUZsb2F0U2NoZWR1bGWUk5QpgZR9lIwOdmFsdWVfc2NoZWR1bGWUaACMEENvbnN0YW50U2NoZWR1bGWUk5QpgZR9lIwDdmFslEc/M6kqMFUyYXNic2Iu", "value_schedule": "ConstantSchedule(val=0.0003)"}, "batch_norm_stats": [], "batch_norm_stats_target": [], "system_info": {"OS": "Linux-6.6.105+-x86_64-with-glibc2.35 # 1 SMP Thu Oct 2 10:42:05 UTC 2025", "Python": "3.12.12", "Stable-Baselines3": "2.7.0", "PyTorch": "2.8.0+cu126", "GPU Enabled": "False", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "Gymnasium": "1.2.1", "OpenAI Gym": "0.25.2"}} |