TQC upgrade for PandaPickAndPlace-v3

README.md

@@ -16,7 +16,7 @@ model-index:
       type: PandaPickAndPlace-v3
     metrics:
     - type: mean_reward
-      value: -19.60 +/- 19.97
+      value: -28.00 +/- 22.03
       name: mean_reward
       verified: false
 ---

config.json

@@ -1 +1 @@
-{"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 0x7f28cf75f910>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f28cf774cc0>"}, "verbose": 1, "policy_kwargs": {"net_arch": [1024, 1024, 1024], "n_critics": 2, "n_quantiles": 25, "use_sde": false}, "num_timesteps": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1717944480585069177, "learning_rate": 0.0001, "tensorboard_log": "./tqcPandaPickAndPlace-v3/", "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[-1.4549398   3.3413293  -6.7534785 ]\n [ 0.03123146 -0.20729426  0.13861421]\n [-0.79375863  0.34754828  0.13862488]\n [-3.00179     1.0748075   0.13857953]\n [ 0.49535337  1.1658607   0.13863438]\n [ 1.1701452  -0.47840372  0.13861421]\n [ 1.1897067  -0.7095725   0.13861442]\n [ 0.9935007   0.5110239   0.13863245]\n [ 0.10466164 -1.0787054   0.13849108]\n [-0.17814611  0.78164667  0.13863109]\n [ 1.1655018  -0.09805054  0.13862935]\n [-0.76950675 -0.38007873  0.13861421]\n [-2.4268687   0.14078632  0.13863173]\n [-4.199527   -0.28924283  0.1386312 ]\n [ 0.05835515  0.6825569   0.13862853]\n [-0.37344873 -0.93851465  0.13862357]]", "desired_goal": "[[ 1.4240143   0.64559424 -0.28392544]\n [-1.2280788   1.3945915   0.53897196]\n [ 1.4491     -0.13930419  1.2833912 ]\n [-1.4193126   1.4904526  -1.3027195 ]\n [-0.34105226  1.6114326   0.8027069 ]\n [ 1.048339   -0.9171903   0.68209994]\n [ 1.5879475  -0.9338333  -0.5291932 ]\n [-1.2096364  -0.5766205  -1.3027195 ]\n [ 1.3645122  -0.5138829  -0.78762406]\n [-1.1959715  -0.39847597  0.8967377 ]\n [-0.20436266 -1.637488   -0.181961  ]\n [ 1.6287849   1.0943354   0.19662423]\n [-1.026712    0.28791535 -0.01447131]\n [-1.3670185   1.7165357   1.4760537 ]\n [-0.31961107 -1.7143902   0.33784106]\n [-1.2550697   0.8347255   1.06538   ]]", "observation": "[[-9.15125072e-01 -1.65736043e+00  1.12326115e-01 -1.59551013e+00\n   1.67819962e-01 -6.19769692e-01 -1.15261984e+00 -1.45493984e+00\n   3.34132934e+00 -6.75347853e+00 -6.74551344e+00  3.08361602e+00\n   3.44968820e+00 -3.51083465e-02  1.39257789e+00 -2.00000000e+01\n  -1.28194971e+01  1.72322547e+00  5.65504968e-01]\n [ 1.60994112e+00 -9.74363327e-01  1.60138309e-01  1.78993732e-01\n   2.40450859e-01 -5.24225891e-01  9.71102953e-01  3.12314592e-02\n  -2.07294255e-01  1.38614208e-01 -1.22844083e-02 -3.03265871e-03\n  -9.16616432e-03  2.26633251e-02 -6.55136164e-03  6.89767748e-02\n   2.89560342e-03 -2.55976133e-02  4.95342026e-03]\n [-3.20424706e-01 -1.96944964e+00 -7.42913127e-01 -1.04817665e+00\n   2.32896030e-01 -9.06560779e-01 -1.15290523e+00 -7.93758631e-01\n   3.47548276e-01  1.38624877e-01 -1.25888688e-02 -3.18938168e-03\n  -7.13046221e-03  2.25443412e-02 -6.34301500e-03  6.89767748e-02\n   2.89558317e-03 -2.55975928e-02  5.32207591e-03]\n [-2.95669794e+00 -8.60746354e-02 -8.47464085e-01  2.44610384e-01\n  -5.14618773e-03 -4.86297160e-02  1.15558088e+00 -3.00179005e+00\n   1.07480752e+00  1.38579533e-01 -1.26784500e-02 -3.49744619e-03\n   1.24797441e-01  3.32777321e-01  8.83991838e-01  6.99789673e-02\n   4.79589542e-03 -2.22768858e-02  2.26925969e-01]\n [ 1.36291891e-01 -3.82528221e-03 -7.95506895e-01  9.02113259e-01\n  -1.03304839e+00  5.55308796e-02  1.14869893e+00  4.95353371e-01\n   1.16586065e+00  1.38634384e-01 -1.25006447e-02 -3.08538205e-03\n  -8.50459840e-03  2.28008721e-02 -6.53079711e-03  6.89847022e-02\n   2.84396252e-03 -2.56041829e-02  4.99694049e-03]\n [-1.77067256e+00  3.28573972e-01  8.11412632e-02  6.49724960e-01\n  -5.05942218e-02  2.80511945e-01  3.45045477e-01  1.17014515e+00\n  -4.78403717e-01  1.38614208e-01 -1.22844083e-02 -3.03265871e-03\n  -9.15956218e-03  2.26633251e-02 -6.55136164e-03  6.89767748e-02\n   2.89560342e-03 -2.55976133e-02  4.95342165e-03]\n [ 5.00675738e-01  8.19608986e-01  1.20428824e+00  7.60575652e-01\n   1.25063539e+00  4.42473888e-01  8.68872702e-01  1.18970668e+00\n  -7.09572494e-01  1.38614416e-01 -1.22863045e-02 -3.03266011e-03\n  -8.92862957e-03  2.26633083e-02 -6.55445876e-03  6.89727440e-02\n   2.91954493e-03 -2.55976059e-02  4.95347288e-03]\n [ 9.34526324e-01  4.71116096e-01  8.93785596e-01  3.31373483e-01\n   8.55553627e-01 -1.69740617e+00 -1.15312004e+00  9.93500710e-01\n   5.11023879e-01  1.38632447e-01 -1.24630565e-02 -3.11050680e-03\n  -8.91851727e-03  2.28210837e-02 -6.51275972e-03  6.89752996e-02\n   2.90437881e-03 -2.55976133e-02  4.94781137e-03]\n [-2.35395148e-01 -6.50913358e-01 -6.83619022e-01 -2.63517797e-01\n  -9.78884816e-01  7.34277248e-01  1.14840996e+00  1.04661644e-01\n  -1.07870543e+00  1.38491079e-01 -1.33095430e-02 -3.82594974e-03\n   1.73456860e+00  6.63122594e-01  3.25248063e-01  7.15815648e-02\n   8.35940999e-04 -1.37546649e-02  7.56143779e-02]\n [ 4.23440307e-01 -1.57415628e+00 -3.82649809e-01  2.37143695e-01\n   1.17944837e+00 -5.53516686e-01 -1.15311921e+00 -1.78146109e-01\n   7.81646669e-01  1.38631091e-01 -1.25787873e-02 -3.12861847e-03\n  -8.42016563e-03  2.26743687e-02 -6.36196230e-03  6.91372380e-02\n   1.10837433e-03 -2.67880168e-02  5.10517275e-03]\n [ 4.52027410e-01 -6.18742168e-01 -7.84596980e-01 -1.41817316e-01\n  -4.38137382e-01  1.55856550e-01  1.14874566e+00  1.16550183e+00\n  -9.80505422e-02  1.38629347e-01 -1.25191435e-02 -2.96165049e-03\n  -8.98899604e-03  2.28958987e-02 -6.60468312e-03  6.88721910e-02\n   2.89551425e-03 -2.49449331e-02  4.96181520e-03]\n [ 4.96615380e-01 -1.06055665e+00 -7.94026792e-01  1.21404745e-01\n  -1.24783564e+00  1.33100376e-01  1.01769888e+00 -7.69506752e-01\n  -3.80078733e-01  1.38614208e-01 -1.22844083e-02 -3.03265871e-03\n  -9.08643752e-03  2.26633195e-02 -6.55136444e-03  6.89767748e-02\n   2.89560342e-03 -2.55976133e-02  4.95343981e-03]\n [ 2.08958566e-01  9.56504285e-01 -6.63371444e-01  3.28674495e-01\n   1.34292054e+00  1.39268768e+00 -7.53147453e-02 -2.42686868e+00\n   1.40786320e-01  1.38631731e-01 -1.24884918e-02 -3.17337341e-03\n   7.94088602e-01  2.28132978e-02 -6.53241388e-03  6.89767748e-02\n   2.89560342e-03 -2.55976133e-02  5.00185043e-03]\n [-1.22542787e+00  7.58157820e-02 -4.98365551e-01 -5.50103724e-01\n  -1.97653007e-02 -1.85234055e-01 -1.15267563e+00 -4.19952679e+00\n  -2.89242834e-01  1.38631195e-01 -1.24304052e-02 -3.04154004e-03\n   3.41726750e-01  2.29883827e-02 -6.67742733e-03  6.91415146e-02\n   4.37499117e-03 -2.39638705e-02  5.13543282e-03]\n [-2.12050095e-01  4.56996970e-02  1.23824382e+00  9.63500217e-02\n  -4.96173114e-01 -1.03881560e-01  1.14508522e+00  5.83551526e-02\n   6.82556927e-01  1.38628528e-01 -1.25511140e-02 -3.00829322e-03\n  -8.37891549e-03  2.29395386e-02 -6.39335066e-03  6.89767748e-02\n   2.89561623e-03 -2.55976003e-02  5.20157022e-03]\n [-1.23476911e+00 -4.39346552e+00  1.53666162e+00  4.57003027e-01\n  -2.28735611e-01  1.71622664e-01 -1.11039519e+00 -3.73448730e-01\n  -9.38514650e-01  1.38623565e-01 -1.25191538e-02 -2.87541840e-03\n  -9.11733322e-03  2.28063278e-02 -6.60467381e-03  6.89767748e-02\n   2.89560319e-03 -2.55976133e-02  4.96189436e-03]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[-0.1782922   0.4232338  -0.3395143 ]\n [-0.00098672 -0.02483108  0.01998892]\n [-0.09941094  0.04522578  0.01998948]\n [-0.36283687  0.13705274  0.01998712]\n [ 0.05438466  0.14854953  0.01998998]\n [ 0.13488969 -0.05906256  0.01998892]\n [ 0.13722345 -0.08825095  0.01998894]\n [ 0.1138154   0.06586694  0.01998988]\n [ 0.00777376 -0.13485931  0.0199825 ]\n [-0.0259662   0.10003696  0.01998981]\n [ 0.13433574 -0.01103749  0.01998971]\n [-0.09651762 -0.04664762  0.01998892]\n [-0.29424673  0.01911911  0.01998984]\n [-0.5057311  -0.03517827  0.01998981]\n [ 0.00224923  0.08752546  0.01998967]\n [-0.04926649 -0.1171582   0.01998941]]", "desired_goal": "[[ 0.12440702  0.05641818  0.08684007]\n [-0.10671286  0.12162221  0.14082794]\n [ 0.12659314 -0.01191123  0.18966709]\n [-0.12337815  0.12996742  0.02      ]\n [-0.02941185  0.14049934  0.15813081]\n [ 0.09166834 -0.07963019  0.15021814]\n [ 0.13869317 -0.08107904  0.07074878]\n [-0.10510567 -0.04998185  0.02      ]\n [ 0.11922164 -0.04452022  0.05379389]\n [-0.10391482 -0.03447346  0.16429989]\n [-0.01749987 -0.14233577  0.09352966]\n [ 0.142252    0.09548339  0.11836752]\n [-0.08916449  0.02528041  0.10451816]\n [-0.11882091  0.1496491   0.2023071 ]\n [-0.02754333 -0.1490305   0.12763233]\n [-0.109065    0.07288302  0.17536402]]", "observation": "[[-1.29107580e-01 -2.31687814e-01  8.44171345e-02 -6.42910361e-01\n   8.13524872e-02 -3.68709117e-01  1.73545413e-05 -1.78292200e-01\n   4.23233807e-01 -3.39514285e-01 -2.05502224e+00  5.38372517e-01\n   2.51527691e+00 -8.45848396e-03  2.28050575e-01 -2.60314751e+00\n  -1.34901867e+01  1.75330198e+00  1.54594374e+00]\n [ 1.73813328e-01 -1.36331901e-01  8.86319950e-02  1.68297812e-02\n   1.16543561e-01 -3.22358072e-01  7.38268346e-02 -9.86720086e-04\n  -2.48310827e-02  1.99889243e-02  6.71601447e-05  9.25234872e-06\n  -1.89866012e-04 -2.02274696e-05 -2.26291945e-06 -2.94996319e-12\n   1.85425328e-10  4.94362572e-11 -1.20045333e-04]\n [-5.77640347e-02 -2.75259823e-01  9.02393181e-03 -4.39418077e-01\n   1.12883098e-01 -5.07839680e-01  7.43581995e-06 -9.94109437e-02\n   4.52257842e-02  1.99894812e-02 -2.57661650e-05 -1.80827647e-05\n   1.29060727e-03 -3.76064854e-05  3.16968326e-05  5.59358462e-12\n  -2.11798188e-08  2.10141593e-08  8.96748097e-04]\n [-3.74025941e-01 -1.23144118e-02 -1.92708263e-04  4.12252992e-02\n  -2.45294999e-03 -9.16327387e-02  8.02383199e-02 -3.62836868e-01\n   1.37052745e-01  1.99871156e-02 -5.31079095e-05 -7.18143856e-05\n   9.72357467e-02  4.52756993e-02  1.45152956e-01  1.25430801e-04\n   1.99925969e-03  3.32923187e-03  6.12105012e-01]\n [-2.97378632e-03 -8.31255165e-04  4.38755378e-03  2.85677314e-01\n  -5.00491381e-01 -4.11014482e-02  7.99991414e-02  5.43846600e-02\n   1.48549527e-01  1.99899767e-02  1.16111005e-06  5.65165870e-08\n   2.91260716e-04 -1.37252940e-07  1.08900474e-06  9.92363994e-07\n  -5.43302012e-05 -6.58611270e-06 -1.08655351e-08]\n [-2.31743783e-01  4.55763154e-02  8.16680491e-02  1.91842258e-01\n  -2.44733989e-02  6.80433139e-02  5.20683564e-02  1.34889692e-01\n  -5.90625629e-02  1.99889243e-02  6.71601374e-05  9.25234690e-06\n  -1.85064288e-04 -2.02275369e-05 -2.26295742e-06 -2.94225408e-12\n   1.85856636e-10  4.98771233e-11 -1.20040801e-04]\n [ 4.07397151e-02  1.14131652e-01  1.80678532e-01  2.33055264e-01\n   6.05997443e-01  1.46615699e-01  7.02738464e-02  1.37223452e-01\n  -8.82509500e-02  1.99889354e-02  6.65814077e-05  9.25210043e-06\n  -1.71176798e-05 -2.02300089e-05 -2.76773676e-06 -5.03949536e-07\n   2.51884521e-05  7.29574490e-09 -1.19900120e-04]\n [ 9.27868262e-02  6.54771850e-02  1.53306320e-01  7.34828189e-02\n   4.14572716e-01 -8.91501486e-01 -2.65176059e-08  1.13815397e-01\n   6.58669397e-02  1.99898761e-02  1.26337500e-05 -4.32569232e-06\n  -9.76387037e-06  2.81508665e-06  4.02901287e-06 -1.84666106e-07\n   9.23259540e-06 -3.39097445e-10 -1.35514798e-04]\n [-4.75634187e-02 -9.11737755e-02  1.42509760e-02 -1.47690922e-01\n  -4.74248111e-01  2.88177878e-01  7.99890980e-02  7.77375977e-03\n  -1.34859309e-01  1.99825019e-02 -2.45727540e-04 -1.29110937e-04\n   1.26794875e+00  9.35266465e-02  5.40798046e-02  3.26005917e-04\n  -2.16693012e-03  1.18732797e-02  1.94770753e-01]\n [ 3.14741246e-02 -2.20071360e-01  4.07827720e-02  3.84492725e-02\n   5.71505964e-01 -3.36567879e-01  6.71762257e-10 -2.59662028e-02\n   1.00036964e-01  1.99898053e-02 -2.26892898e-05 -7.48466391e-06\n   3.52665054e-04 -1.86145389e-05  2.86084596e-05  2.00834256e-05\n  -1.88030838e-03 -1.19345239e-03  2.98505562e-04]\n [ 3.49035934e-02 -8.66822302e-02  5.34931244e-03 -1.02444082e-01\n  -2.12245539e-01  7.56941177e-03  8.00007656e-02  1.34335741e-01\n  -1.10374894e-02  1.99897140e-02 -4.48502396e-06  2.16373428e-05\n  -6.10193565e-05  1.37427796e-05 -1.09541652e-05 -1.30889894e-05\n  -9.36510247e-08  6.54352247e-04 -9.68912354e-05]\n [ 4.02526110e-02 -1.48365691e-01  4.51803347e-03 -4.58114222e-03\n  -6.04559958e-01 -3.47026507e-03  7.54462630e-02 -9.65176150e-02\n  -4.66476157e-02  1.99889243e-02  6.71600574e-05  9.25232507e-06\n  -1.31884168e-04 -2.02282881e-05 -2.26337806e-06 -2.94811398e-12\n   1.86411470e-10  4.98849954e-11 -1.19990560e-04]\n [ 5.74371032e-03  1.33244142e-01  1.60358883e-02  7.24793747e-02\n   6.50711417e-01  6.07591629e-01  3.74588370e-02 -2.94246733e-01\n   1.91191081e-02  1.99898388e-02  4.87042735e-06 -1.52906596e-05\n   5.83980620e-01  1.67778876e-06  8.25506390e-07 -3.03608874e-12\n   1.06771980e-10 -1.62661593e-10  1.35307946e-05]\n [-1.66333213e-01  1.02877477e-02  3.05819064e-02 -2.54240274e-01\n  -9.53619275e-03 -1.57903418e-01  1.54158733e-05 -5.05731106e-01\n  -3.51782739e-02  1.99898109e-02  2.25995263e-05  7.70329007e-06\n   2.54998535e-01  2.72509933e-05 -2.28111585e-05  2.06188051e-05\n   1.55643479e-03  1.63792796e-03  3.81965772e-04]\n [-4.47628163e-02  6.08312245e-03  1.83671862e-01 -1.38962017e-02\n  -2.40364969e-01 -1.18436992e-01  7.98735470e-02  2.24923203e-03\n   8.75254571e-02  1.99896712e-02 -1.42428235e-05  1.35020846e-05\n   3.82664090e-04  2.01168332e-05  2.34923045e-05  1.34483119e-11\n   1.34856259e-08  1.27520021e-08  5.64380840e-04]\n [-1.67453840e-01 -6.13686264e-01  2.09978744e-01  1.20190449e-01\n  -1.10786341e-01  1.52180064e-02  1.48486358e-03 -4.92664948e-02\n  -1.17158197e-01  1.99894123e-02 -4.48816718e-06  3.66776658e-05\n  -1.54353242e-04  6.59860291e-07 -1.09526418e-05 -3.98735558e-12\n  -6.72317410e-11  2.51768939e-10 -9.66724911e-05]]"}, "_episode_num": 49357, "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:": "gAWVhgAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKImIiImJiYmIiYiIiImIiYmJiYiJiYmIiYmJiYmJiYiJiYmJiImJiIiIiImJiIiJiYmJiYiJiYiJiYiJiYiJiIiIiYmIiIiJiYiIiImIiImIiImIiImJiIiIiYmJiImJiYmJiIhlLg=="}, "_n_updates": 124688, "buffer_size": 1000000, "batch_size": 2048, "learning_starts": 5000, "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", "__annotations__": "{'observation_space': <class 'gymnasium.spaces.dict.Dict'>, 'obs_shape': typing.Dict[str, typing.Tuple[int, ...]], 'observations': typing.Dict[str, numpy.ndarray], 'next_observations': typing.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 0x7f2903c81000>", "add": "<function DictReplayBuffer.add at 0x7f2903c81090>", "sample": "<function DictReplayBuffer.sample at 0x7f2903c81120>", "_get_samples": "<function DictReplayBuffer._get_samples at 0x7f2903c811b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f2903c71cc0>"}, "replay_buffer_kwargs": {}, "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": "OrderedDict([('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", "bounded_below": "[ True  True  True  True]", "bounded_above": "[ True  True  True  True]", "_shape": [4], "low": "[-1. -1. -1. -1.]", "high": "[1. 1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": "Generator(PCG64)"}, "n_envs": 16, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "batch_norm_stats": [], "batch_norm_stats_target": [], "system_info": {"OS": "Linux-5.15.146.1-microsoft-standard-WSL2-x86_64-with-glibc2.35 # 1 SMP Thu Jan 11 04:09:03 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.3.2", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.0.0", "Gymnasium": "0.29.1", "OpenAI Gym": "0.26.2"}}
+{"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 0x7fdae215b880>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fdae2161780>"}, "verbose": 1, "policy_kwargs": {"net_arch": [1024, 1024, 1024], "n_critics": 2, "n_quantiles": 25, "use_sde": false}, "num_timesteps": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1717944480585069177, "learning_rate": 0.0001, "tensorboard_log": "./tqcPandaPickAndPlace-v3/", "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[-1.4549398   3.3413293  -6.7534785 ]\n [ 0.03123146 -0.20729426  0.13861421]\n [-0.79375863  0.34754828  0.13862488]\n [-3.00179     1.0748075   0.13857953]\n [ 0.49535337  1.1658607   0.13863438]\n [ 1.1701452  -0.47840372  0.13861421]\n [ 1.1897067  -0.7095725   0.13861442]\n [ 0.9935007   0.5110239   0.13863245]\n [ 0.10466164 -1.0787054   0.13849108]\n [-0.17814611  0.78164667  0.13863109]\n [ 1.1655018  -0.09805054  0.13862935]\n [-0.76950675 -0.38007873  0.13861421]\n [-2.4268687   0.14078632  0.13863173]\n [-4.199527   -0.28924283  0.1386312 ]\n [ 0.05835515  0.6825569   0.13862853]\n [-0.37344873 -0.93851465  0.13862357]]", "desired_goal": "[[ 1.4240143   0.64559424 -0.28392544]\n [-1.2280788   1.3945915   0.53897196]\n [ 1.4491     -0.13930419  1.2833912 ]\n [-1.4193126   1.4904526  -1.3027195 ]\n [-0.34105226  1.6114326   0.8027069 ]\n [ 1.048339   -0.9171903   0.68209994]\n [ 1.5879475  -0.9338333  -0.5291932 ]\n [-1.2096364  -0.5766205  -1.3027195 ]\n [ 1.3645122  -0.5138829  -0.78762406]\n [-1.1959715  -0.39847597  0.8967377 ]\n [-0.20436266 -1.637488   -0.181961  ]\n [ 1.6287849   1.0943354   0.19662423]\n [-1.026712    0.28791535 -0.01447131]\n [-1.3670185   1.7165357   1.4760537 ]\n [-0.31961107 -1.7143902   0.33784106]\n [-1.2550697   0.8347255   1.06538   ]]", "observation": "[[-9.15125072e-01 -1.65736043e+00  1.12326115e-01 -1.59551013e+00\n   1.67819962e-01 -6.19769692e-01 -1.15261984e+00 -1.45493984e+00\n   3.34132934e+00 -6.75347853e+00 -6.74551344e+00  3.08361602e+00\n   3.44968820e+00 -3.51083465e-02  1.39257789e+00 -2.00000000e+01\n  -1.28194971e+01  1.72322547e+00  5.65504968e-01]\n [ 1.60994112e+00 -9.74363327e-01  1.60138309e-01  1.78993732e-01\n   2.40450859e-01 -5.24225891e-01  9.71102953e-01  3.12314592e-02\n  -2.07294255e-01  1.38614208e-01 -1.22844083e-02 -3.03265871e-03\n  -9.16616432e-03  2.26633251e-02 -6.55136164e-03  6.89767748e-02\n   2.89560342e-03 -2.55976133e-02  4.95342026e-03]\n [-3.20424706e-01 -1.96944964e+00 -7.42913127e-01 -1.04817665e+00\n   2.32896030e-01 -9.06560779e-01 -1.15290523e+00 -7.93758631e-01\n   3.47548276e-01  1.38624877e-01 -1.25888688e-02 -3.18938168e-03\n  -7.13046221e-03  2.25443412e-02 -6.34301500e-03  6.89767748e-02\n   2.89558317e-03 -2.55975928e-02  5.32207591e-03]\n [-2.95669794e+00 -8.60746354e-02 -8.47464085e-01  2.44610384e-01\n  -5.14618773e-03 -4.86297160e-02  1.15558088e+00 -3.00179005e+00\n   1.07480752e+00  1.38579533e-01 -1.26784500e-02 -3.49744619e-03\n   1.24797441e-01  3.32777321e-01  8.83991838e-01  6.99789673e-02\n   4.79589542e-03 -2.22768858e-02  2.26925969e-01]\n [ 1.36291891e-01 -3.82528221e-03 -7.95506895e-01  9.02113259e-01\n  -1.03304839e+00  5.55308796e-02  1.14869893e+00  4.95353371e-01\n   1.16586065e+00  1.38634384e-01 -1.25006447e-02 -3.08538205e-03\n  -8.50459840e-03  2.28008721e-02 -6.53079711e-03  6.89847022e-02\n   2.84396252e-03 -2.56041829e-02  4.99694049e-03]\n [-1.77067256e+00  3.28573972e-01  8.11412632e-02  6.49724960e-01\n  -5.05942218e-02  2.80511945e-01  3.45045477e-01  1.17014515e+00\n  -4.78403717e-01  1.38614208e-01 -1.22844083e-02 -3.03265871e-03\n  -9.15956218e-03  2.26633251e-02 -6.55136164e-03  6.89767748e-02\n   2.89560342e-03 -2.55976133e-02  4.95342165e-03]\n [ 5.00675738e-01  8.19608986e-01  1.20428824e+00  7.60575652e-01\n   1.25063539e+00  4.42473888e-01  8.68872702e-01  1.18970668e+00\n  -7.09572494e-01  1.38614416e-01 -1.22863045e-02 -3.03266011e-03\n  -8.92862957e-03  2.26633083e-02 -6.55445876e-03  6.89727440e-02\n   2.91954493e-03 -2.55976059e-02  4.95347288e-03]\n [ 9.34526324e-01  4.71116096e-01  8.93785596e-01  3.31373483e-01\n   8.55553627e-01 -1.69740617e+00 -1.15312004e+00  9.93500710e-01\n   5.11023879e-01  1.38632447e-01 -1.24630565e-02 -3.11050680e-03\n  -8.91851727e-03  2.28210837e-02 -6.51275972e-03  6.89752996e-02\n   2.90437881e-03 -2.55976133e-02  4.94781137e-03]\n [-2.35395148e-01 -6.50913358e-01 -6.83619022e-01 -2.63517797e-01\n  -9.78884816e-01  7.34277248e-01  1.14840996e+00  1.04661644e-01\n  -1.07870543e+00  1.38491079e-01 -1.33095430e-02 -3.82594974e-03\n   1.73456860e+00  6.63122594e-01  3.25248063e-01  7.15815648e-02\n   8.35940999e-04 -1.37546649e-02  7.56143779e-02]\n [ 4.23440307e-01 -1.57415628e+00 -3.82649809e-01  2.37143695e-01\n   1.17944837e+00 -5.53516686e-01 -1.15311921e+00 -1.78146109e-01\n   7.81646669e-01  1.38631091e-01 -1.25787873e-02 -3.12861847e-03\n  -8.42016563e-03  2.26743687e-02 -6.36196230e-03  6.91372380e-02\n   1.10837433e-03 -2.67880168e-02  5.10517275e-03]\n [ 4.52027410e-01 -6.18742168e-01 -7.84596980e-01 -1.41817316e-01\n  -4.38137382e-01  1.55856550e-01  1.14874566e+00  1.16550183e+00\n  -9.80505422e-02  1.38629347e-01 -1.25191435e-02 -2.96165049e-03\n  -8.98899604e-03  2.28958987e-02 -6.60468312e-03  6.88721910e-02\n   2.89551425e-03 -2.49449331e-02  4.96181520e-03]\n [ 4.96615380e-01 -1.06055665e+00 -7.94026792e-01  1.21404745e-01\n  -1.24783564e+00  1.33100376e-01  1.01769888e+00 -7.69506752e-01\n  -3.80078733e-01  1.38614208e-01 -1.22844083e-02 -3.03265871e-03\n  -9.08643752e-03  2.26633195e-02 -6.55136444e-03  6.89767748e-02\n   2.89560342e-03 -2.55976133e-02  4.95343981e-03]\n [ 2.08958566e-01  9.56504285e-01 -6.63371444e-01  3.28674495e-01\n   1.34292054e+00  1.39268768e+00 -7.53147453e-02 -2.42686868e+00\n   1.40786320e-01  1.38631731e-01 -1.24884918e-02 -3.17337341e-03\n   7.94088602e-01  2.28132978e-02 -6.53241388e-03  6.89767748e-02\n   2.89560342e-03 -2.55976133e-02  5.00185043e-03]\n [-1.22542787e+00  7.58157820e-02 -4.98365551e-01 -5.50103724e-01\n  -1.97653007e-02 -1.85234055e-01 -1.15267563e+00 -4.19952679e+00\n  -2.89242834e-01  1.38631195e-01 -1.24304052e-02 -3.04154004e-03\n   3.41726750e-01  2.29883827e-02 -6.67742733e-03  6.91415146e-02\n   4.37499117e-03 -2.39638705e-02  5.13543282e-03]\n [-2.12050095e-01  4.56996970e-02  1.23824382e+00  9.63500217e-02\n  -4.96173114e-01 -1.03881560e-01  1.14508522e+00  5.83551526e-02\n   6.82556927e-01  1.38628528e-01 -1.25511140e-02 -3.00829322e-03\n  -8.37891549e-03  2.29395386e-02 -6.39335066e-03  6.89767748e-02\n   2.89561623e-03 -2.55976003e-02  5.20157022e-03]\n [-1.23476911e+00 -4.39346552e+00  1.53666162e+00  4.57003027e-01\n  -2.28735611e-01  1.71622664e-01 -1.11039519e+00 -3.73448730e-01\n  -9.38514650e-01  1.38623565e-01 -1.25191538e-02 -2.87541840e-03\n  -9.11733322e-03  2.28063278e-02 -6.60467381e-03  6.89767748e-02\n   2.89560319e-03 -2.55976133e-02  4.96189436e-03]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[-0.1782922   0.4232338  -0.3395143 ]\n [-0.00098672 -0.02483108  0.01998892]\n [-0.09941094  0.04522578  0.01998948]\n [-0.36283687  0.13705274  0.01998712]\n [ 0.05438466  0.14854953  0.01998998]\n [ 0.13488969 -0.05906256  0.01998892]\n [ 0.13722345 -0.08825095  0.01998894]\n [ 0.1138154   0.06586694  0.01998988]\n [ 0.00777376 -0.13485931  0.0199825 ]\n [-0.0259662   0.10003696  0.01998981]\n [ 0.13433574 -0.01103749  0.01998971]\n [-0.09651762 -0.04664762  0.01998892]\n [-0.29424673  0.01911911  0.01998984]\n [-0.5057311  -0.03517827  0.01998981]\n [ 0.00224923  0.08752546  0.01998967]\n [-0.04926649 -0.1171582   0.01998941]]", "desired_goal": "[[ 0.12440702  0.05641818  0.08684007]\n [-0.10671286  0.12162221  0.14082794]\n [ 0.12659314 -0.01191123  0.18966709]\n [-0.12337815  0.12996742  0.02      ]\n [-0.02941185  0.14049934  0.15813081]\n [ 0.09166834 -0.07963019  0.15021814]\n [ 0.13869317 -0.08107904  0.07074878]\n [-0.10510567 -0.04998185  0.02      ]\n [ 0.11922164 -0.04452022  0.05379389]\n [-0.10391482 -0.03447346  0.16429989]\n [-0.01749987 -0.14233577  0.09352966]\n [ 0.142252    0.09548339  0.11836752]\n [-0.08916449  0.02528041  0.10451816]\n [-0.11882091  0.1496491   0.2023071 ]\n [-0.02754333 -0.1490305   0.12763233]\n [-0.109065    0.07288302  0.17536402]]", "observation": "[[-1.29107580e-01 -2.31687814e-01  8.44171345e-02 -6.42910361e-01\n   8.13524872e-02 -3.68709117e-01  1.73545413e-05 -1.78292200e-01\n   4.23233807e-01 -3.39514285e-01 -2.05502224e+00  5.38372517e-01\n   2.51527691e+00 -8.45848396e-03  2.28050575e-01 -2.60314751e+00\n  -1.34901867e+01  1.75330198e+00  1.54594374e+00]\n [ 1.73813328e-01 -1.36331901e-01  8.86319950e-02  1.68297812e-02\n   1.16543561e-01 -3.22358072e-01  7.38268346e-02 -9.86720086e-04\n  -2.48310827e-02  1.99889243e-02  6.71601447e-05  9.25234872e-06\n  -1.89866012e-04 -2.02274696e-05 -2.26291945e-06 -2.94996319e-12\n   1.85425328e-10  4.94362572e-11 -1.20045333e-04]\n [-5.77640347e-02 -2.75259823e-01  9.02393181e-03 -4.39418077e-01\n   1.12883098e-01 -5.07839680e-01  7.43581995e-06 -9.94109437e-02\n   4.52257842e-02  1.99894812e-02 -2.57661650e-05 -1.80827647e-05\n   1.29060727e-03 -3.76064854e-05  3.16968326e-05  5.59358462e-12\n  -2.11798188e-08  2.10141593e-08  8.96748097e-04]\n [-3.74025941e-01 -1.23144118e-02 -1.92708263e-04  4.12252992e-02\n  -2.45294999e-03 -9.16327387e-02  8.02383199e-02 -3.62836868e-01\n   1.37052745e-01  1.99871156e-02 -5.31079095e-05 -7.18143856e-05\n   9.72357467e-02  4.52756993e-02  1.45152956e-01  1.25430801e-04\n   1.99925969e-03  3.32923187e-03  6.12105012e-01]\n [-2.97378632e-03 -8.31255165e-04  4.38755378e-03  2.85677314e-01\n  -5.00491381e-01 -4.11014482e-02  7.99991414e-02  5.43846600e-02\n   1.48549527e-01  1.99899767e-02  1.16111005e-06  5.65165870e-08\n   2.91260716e-04 -1.37252940e-07  1.08900474e-06  9.92363994e-07\n  -5.43302012e-05 -6.58611270e-06 -1.08655351e-08]\n [-2.31743783e-01  4.55763154e-02  8.16680491e-02  1.91842258e-01\n  -2.44733989e-02  6.80433139e-02  5.20683564e-02  1.34889692e-01\n  -5.90625629e-02  1.99889243e-02  6.71601374e-05  9.25234690e-06\n  -1.85064288e-04 -2.02275369e-05 -2.26295742e-06 -2.94225408e-12\n   1.85856636e-10  4.98771233e-11 -1.20040801e-04]\n [ 4.07397151e-02  1.14131652e-01  1.80678532e-01  2.33055264e-01\n   6.05997443e-01  1.46615699e-01  7.02738464e-02  1.37223452e-01\n  -8.82509500e-02  1.99889354e-02  6.65814077e-05  9.25210043e-06\n  -1.71176798e-05 -2.02300089e-05 -2.76773676e-06 -5.03949536e-07\n   2.51884521e-05  7.29574490e-09 -1.19900120e-04]\n [ 9.27868262e-02  6.54771850e-02  1.53306320e-01  7.34828189e-02\n   4.14572716e-01 -8.91501486e-01 -2.65176059e-08  1.13815397e-01\n   6.58669397e-02  1.99898761e-02  1.26337500e-05 -4.32569232e-06\n  -9.76387037e-06  2.81508665e-06  4.02901287e-06 -1.84666106e-07\n   9.23259540e-06 -3.39097445e-10 -1.35514798e-04]\n [-4.75634187e-02 -9.11737755e-02  1.42509760e-02 -1.47690922e-01\n  -4.74248111e-01  2.88177878e-01  7.99890980e-02  7.77375977e-03\n  -1.34859309e-01  1.99825019e-02 -2.45727540e-04 -1.29110937e-04\n   1.26794875e+00  9.35266465e-02  5.40798046e-02  3.26005917e-04\n  -2.16693012e-03  1.18732797e-02  1.94770753e-01]\n [ 3.14741246e-02 -2.20071360e-01  4.07827720e-02  3.84492725e-02\n   5.71505964e-01 -3.36567879e-01  6.71762257e-10 -2.59662028e-02\n   1.00036964e-01  1.99898053e-02 -2.26892898e-05 -7.48466391e-06\n   3.52665054e-04 -1.86145389e-05  2.86084596e-05  2.00834256e-05\n  -1.88030838e-03 -1.19345239e-03  2.98505562e-04]\n [ 3.49035934e-02 -8.66822302e-02  5.34931244e-03 -1.02444082e-01\n  -2.12245539e-01  7.56941177e-03  8.00007656e-02  1.34335741e-01\n  -1.10374894e-02  1.99897140e-02 -4.48502396e-06  2.16373428e-05\n  -6.10193565e-05  1.37427796e-05 -1.09541652e-05 -1.30889894e-05\n  -9.36510247e-08  6.54352247e-04 -9.68912354e-05]\n [ 4.02526110e-02 -1.48365691e-01  4.51803347e-03 -4.58114222e-03\n  -6.04559958e-01 -3.47026507e-03  7.54462630e-02 -9.65176150e-02\n  -4.66476157e-02  1.99889243e-02  6.71600574e-05  9.25232507e-06\n  -1.31884168e-04 -2.02282881e-05 -2.26337806e-06 -2.94811398e-12\n   1.86411470e-10  4.98849954e-11 -1.19990560e-04]\n [ 5.74371032e-03  1.33244142e-01  1.60358883e-02  7.24793747e-02\n   6.50711417e-01  6.07591629e-01  3.74588370e-02 -2.94246733e-01\n   1.91191081e-02  1.99898388e-02  4.87042735e-06 -1.52906596e-05\n   5.83980620e-01  1.67778876e-06  8.25506390e-07 -3.03608874e-12\n   1.06771980e-10 -1.62661593e-10  1.35307946e-05]\n [-1.66333213e-01  1.02877477e-02  3.05819064e-02 -2.54240274e-01\n  -9.53619275e-03 -1.57903418e-01  1.54158733e-05 -5.05731106e-01\n  -3.51782739e-02  1.99898109e-02  2.25995263e-05  7.70329007e-06\n   2.54998535e-01  2.72509933e-05 -2.28111585e-05  2.06188051e-05\n   1.55643479e-03  1.63792796e-03  3.81965772e-04]\n [-4.47628163e-02  6.08312245e-03  1.83671862e-01 -1.38962017e-02\n  -2.40364969e-01 -1.18436992e-01  7.98735470e-02  2.24923203e-03\n   8.75254571e-02  1.99896712e-02 -1.42428235e-05  1.35020846e-05\n   3.82664090e-04  2.01168332e-05  2.34923045e-05  1.34483119e-11\n   1.34856259e-08  1.27520021e-08  5.64380840e-04]\n [-1.67453840e-01 -6.13686264e-01  2.09978744e-01  1.20190449e-01\n  -1.10786341e-01  1.52180064e-02  1.48486358e-03 -4.92664948e-02\n  -1.17158197e-01  1.99894123e-02 -4.48816718e-06  3.66776658e-05\n  -1.54353242e-04  6.59860291e-07 -1.09526418e-05 -3.98735558e-12\n  -6.72317410e-11  2.51768939e-10 -9.66724911e-05]]"}, "_episode_num": 49357, "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:": "gAWVhgAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKImIiImJiYmIiYiIiImIiYmJiYiJiYmIiYmJiYmJiYiJiYmJiImJiIiIiImJiIiJiYmJiYiJiYiJiYiJiYiJiIiIiYmIiIiJiYiIiImIiImIiImIiImJiIiIiYmJiImJiYmJiIhlLg=="}, "_n_updates": 124688, "buffer_size": 1000000, "batch_size": 2048, "learning_starts": 5000, "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", "__annotations__": "{'observation_space': <class 'gymnasium.spaces.dict.Dict'>, 'obs_shape': typing.Dict[str, typing.Tuple[int, ...]], 'observations': typing.Dict[str, numpy.ndarray], 'next_observations': typing.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 0x7fdb16ea4f70>", "add": "<function DictReplayBuffer.add at 0x7fdb16ea5000>", "sample": "<function DictReplayBuffer.sample at 0x7fdb16ea5090>", "_get_samples": "<function DictReplayBuffer._get_samples at 0x7fdb16ea5120>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fdb16e8f280>"}, "replay_buffer_kwargs": {}, "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:": "gAWVMgQAAAAAAACMFWd5bW5hc2l1bS5zcGFjZXMuZGljdJSMBERpY3SUk5QpgZR9lCiMBnNwYWNlc5SMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwUZ3ltbmFzaXVtLnNwYWNlcy5ib3iUjANCb3iUk5QpgZR9lCiMBWR0eXBllIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowNYm91bmRlZF9iZWxvd5SMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYDAAAAAAAAAAEBAZRoE4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksDhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoHCiWAwAAAAAAAAABAQGUaCBLA4WUaCR0lFKUjAZfc2hhcGWUSwOFlIwDbG93lGgcKJYMAAAAAAAAAAAAIMEAACDBAAAgwZRoFksDhZRoJHSUUpSMBGhpZ2iUaBwolgwAAAAAAAAAAAAgQQAAIEEAACBBlGgWSwOFlGgkdJRSlIwIbG93X3JlcHKUjAUtMTAuMJSMCWhpZ2hfcmVwcpSMBDEwLjCUjApfbnBfcmFuZG9tlE51YowMZGVzaXJlZF9nb2FslGgNKYGUfZQoaBBoFmgZaBwolgMAAAAAAAAAAQEBlGggSwOFlGgkdJRSlGgnaBwolgMAAAAAAAAAAQEBlGggSwOFlGgkdJRSlGgsSwOFlGguaBwolgwAAAAAAAAAAAAgwQAAIMEAACDBlGgWSwOFlGgkdJRSlGgzaBwolgwAAAAAAAAAAAAgQQAAIEEAACBBlGgWSwOFlGgkdJRSlGg4jAUtMTAuMJRoOowEMTAuMJRoPE51YowLb2JzZXJ2YXRpb26UaA0pgZR9lChoEGgWaBloHCiWEwAAAAAAAAABAQEBAQEBAQEBAQEBAQEBAQEBlGggSxOFlGgkdJRSlGgnaBwolhMAAAAAAAAAAQEBAQEBAQEBAQEBAQEBAQEBAZRoIEsThZRoJHSUUpRoLEsThZRoLmgcKJZMAAAAAAAAAAAAIMEAACDBAAAgwQAAIMEAACDBAAAgwQAAIMEAACDBAAAgwQAAIMEAACDBAAAgwQAAIMEAACDBAAAgwQAAIMEAACDBAAAgwQAAIMGUaBZLE4WUaCR0lFKUaDNoHCiWTAAAAAAAAAAAACBBAAAgQQAAIEEAACBBAAAgQQAAIEEAACBBAAAgQQAAIEEAACBBAAAgQQAAIEEAACBBAAAgQQAAIEEAACBBAAAgQQAAIEEAACBBlGgWSxOFlGgkdJRSlGg4jAUtMTAuMJRoOowEMTAuMJRoPE51YnVoLE5oEE5oPE51Yi4=", "spaces": "OrderedDict([('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", "bounded_below": "[ True  True  True  True]", "bounded_above": "[ True  True  True  True]", "_shape": [4], "low": "[-1. -1. -1. -1.]", "high": "[1. 1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": "Generator(PCG64)"}, "n_envs": 16, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "batch_norm_stats": [], "batch_norm_stats_target": [], "system_info": {"OS": "Linux-5.15.146.1-microsoft-standard-WSL2-x86_64-with-glibc2.35 # 1 SMP Thu Jan 11 04:09:03 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.3.2", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.0.0", "Gymnasium": "0.29.1", "OpenAI Gym": "0.26.2"}}

results.json

@@ -1 +1 @@
-{"mean_reward": -19.6, "std_reward": 19.96597105076535, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-09T18:35:27.263175"}
+{"mean_reward": -28.0, "std_reward": 22.027255843613386, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-10T13:13:05.050925"}

tqc-PandaPickAndPlace-v3.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b2c3414d83abdcb814ecf0d310ae523aafe60a5e75d86ac661f199daf586599d
+oid sha256:dbca7a8fbfb286fc87eb53dc2ac296ffcea50240f359879f872b966213e92614
 size 94659881

tqc-PandaPickAndPlace-v3/data

@@ -4,9 +4,9 @@
         ":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 0x7f28cf75f910>",
+        "__init__": "<function MultiInputPolicy.__init__ at 0x7fdae215b880>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7f28cf774cc0>"
+        "_abc_impl": "<_abc._abc_data object at 0x7fdae2161780>"
     },
     "verbose": 1,
     "policy_kwargs": {
@@ -72,12 +72,12 @@
         "__module__": "stable_baselines3.common.buffers",
         "__annotations__": "{'observation_space': <class 'gymnasium.spaces.dict.Dict'>, 'obs_shape': typing.Dict[str, typing.Tuple[int, ...]], 'observations': typing.Dict[str, numpy.ndarray], 'next_observations': typing.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 0x7f2903c81000>",
-        "add": "<function DictReplayBuffer.add at 0x7f2903c81090>",
-        "sample": "<function DictReplayBuffer.sample at 0x7f2903c81120>",
-        "_get_samples": "<function DictReplayBuffer._get_samples at 0x7f2903c811b0>",
+        "__init__": "<function DictReplayBuffer.__init__ at 0x7fdb16ea4f70>",
+        "add": "<function DictReplayBuffer.add at 0x7fdb16ea5000>",
+        "sample": "<function DictReplayBuffer.sample at 0x7fdb16ea5090>",
+        "_get_samples": "<function DictReplayBuffer._get_samples at 0x7fdb16ea5120>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7f2903c71cc0>"
+        "_abc_impl": "<_abc._abc_data object at 0x7fdb16e8f280>"
     },
     "replay_buffer_kwargs": {},
     "train_freq": {

vec_normalize.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e750beeee42d68637e0c248b4cd289067f3cedba78ea570d1ccb576c1eaf4ae2
+oid sha256:766dfb33b2df461e7737e4da697264731eebe4859ff6ad749c010a6aba6040be
 size 3317