| # MPMC pretrained pointset |
| # Contains following parameters (refer to QMCPy's MPMC documentation for more details): |
| # 'loss_fn': L2sym |
| # 'lr': 0.001 |
| # 'nlayers': 3 |
| # 'weight_decay': 1e-06 |
| # 'nhid': 32 |
| # 'nbatch': 1 |
| # 'epochs': 200000 |
| # 'start_reduce': 100000 |
| # 'radius': 0.35 |
| # 'weights': None |
| # 'n_projections': 15 |
| 2 #d, the number of dimensions |
| 128 #n, the number of points |
| 1.533618569374084473e-01 5.653718113899230957e-01 |
| 3.647996783256530762e-01 6.506631970405578613e-01 |
| 7.474768161773681641e-01 8.064888119697570801e-01 |
| 8.493774533271789551e-01 9.999821186065673828e-01 |
| 7.227909564971923828e-01 8.622226119041442871e-01 |
| 5.168680548667907715e-01 9.236723184585571289e-01 |
| 8.648897409439086914e-01 8.768599629402160645e-01 |
| 8.970223069190979004e-01 6.405644416809082031e-01 |
| 3.232454061508178711e-01 4.056564271450042725e-01 |
| 7.787152528762817383e-01 7.292232513427734375e-01 |
| 1.603624224662780762e-01 6.826710700988769531e-02 |
| 6.993511319160461426e-01 6.989046335220336914e-01 |
| 5.426034703850746155e-02 7.046132087707519531e-01 |
| 5.168744921684265137e-01 7.996489852666854858e-02 |
| 2.189876139163970947e-02 3.121231198310852051e-01 |
| 9.613341093063354492e-01 3.312217295169830322e-01 |
| 5.399267077445983887e-01 9.630610942840576172e-01 |
| 6.044248938560485840e-01 2.704662382602691650e-01 |
| 2.613097429275512695e-01 2.033302187919616699e-01 |
| 5.873040556907653809e-01 5.724730491638183594e-01 |
| 1.670004129409790039e-01 3.291691839694976807e-01 |
| 8.087418079376220703e-01 2.156673222780227661e-01 |
| 5.820904374122619629e-01 5.521546304225921631e-02 |
| 7.893320322036743164e-01 9.104345440864562988e-01 |
| 3.344226479530334473e-01 1.516087353229522705e-01 |
| 6.780472397804260254e-01 6.191716194152832031e-01 |
| 6.975959241390228271e-02 8.317898511886596680e-01 |
| 7.740171551704406738e-01 3.221674859523773193e-01 |
| 6.585945487022399902e-01 7.873035073280334473e-01 |
| 1.116523519158363342e-01 9.104377627372741699e-01 |
| 8.525239229202270508e-01 5.609046816825866699e-01 |
| 3.682130873203277588e-01 1.322789639234542847e-01 |
| 1.603661626577377319e-01 9.519785046577453613e-01 |
| 7.474675178527832031e-01 1.249485239386558533e-01 |
| 9.054812192916870117e-01 1.736035794019699097e-01 |
| 4.686488509178161621e-01 9.004727005958557129e-01 |
| 7.097132205963134766e-01 4.381002187728881836e-01 |
| 2.154445797204971313e-01 5.877279043197631836e-01 |
| 2.240057885646820068e-01 4.207733646035194397e-02 |
| 7.177029848098754883e-01 9.999279975891113281e-01 |
| 2.485138773918151855e-01 5.225958228111267090e-01 |
| 1.862120479345321655e-01 2.789126932621002197e-01 |
| 7.601977884769439697e-02 4.165437519550323486e-01 |
| 1.384693533182144165e-01 3.598560094833374023e-01 |
| 4.568529725074768066e-01 6.641751527786254883e-01 |
| 7.227921485900878906e-01 2.399687319993972778e-01 |
| 8.831555843353271484e-01 5.877266526222229004e-01 |
| 5.820915699005126953e-01 9.763559103012084961e-01 |
| 8.420328497886657715e-01 1.953463554382324219e-01 |
| 8.352125287055969238e-01 6.716501116752624512e-01 |
| 7.177079319953918457e-01 1.576751237735152245e-04 |
| 9.054813981056213379e-01 9.346394538879394531e-01 |
| 6.430955529212951660e-01 3.771554306149482727e-02 |
| 2.350137531757354736e-01 2.200743108987808228e-01 |
| 1.784965991973876953e-01 6.767098903656005859e-01 |
| 8.387389183044433594e-01 9.999972581863403320e-01 |
| 4.969522655010223389e-01 2.292944937944412231e-01 |
| 6.354699134826660156e-01 1.586610525846481323e-01 |
| 5.615379810333251953e-01 1.867953240871429443e-01 |
| 6.017342805862426758e-01 6.853699684143066406e-01 |
| 4.183777272701263428e-01 1.141652017831802368e-01 |
| 1.980294734239578247e-01 7.607703208923339844e-01 |
| 5.615562200546264648e-01 8.411932587623596191e-01 |
| 8.230199813842773438e-01 3.928221166133880615e-01 |
| 4.788952320814132690e-02 1.952930390834808350e-01 |
| 4.341159462928771973e-01 8.195502161979675293e-01 |
| 5.107623934745788574e-01 4.647067785263061523e-01 |
| 3.937474787235260010e-01 2.856698036193847656e-01 |
| 6.927838325500488281e-01 2.252810448408126831e-02 |
| 9.165846109390258789e-01 4.734814167022705078e-01 |
| 9.759986400604248047e-01 7.953633069992065430e-01 |
| 5.399206876754760742e-01 1.022639125585556030e-02 |
| 7.893323302268981934e-01 6.826510280370712280e-02 |
| 8.387349843978881836e-01 2.840592242137063295e-05 |
| 5.737429857254028320e-01 3.851560652256011963e-01 |
| 3.808656930923461914e-01 4.540986418724060059e-01 |
| 5.254232883453369141e-01 7.417138814926147461e-01 |
| 9.936907142400741577e-02 6.405661106109619141e-01 |
| 1.116506755352020264e-01 1.023130044341087341e-01 |
| 2.863567769527435303e-01 4.352292120456695557e-01 |
| 8.797608017921447754e-01 9.999791383743286133e-01 |
| 9.162174165248870850e-02 3.928175866603851318e-01 |
| 3.892681300640106201e-01 8.878822922706604004e-01 |
| 2.612979710102081299e-01 8.745968341827392578e-01 |
| 8.797734379768371582e-01 7.580385954497614875e-06 |
| 7.982246875762939453e-01 5.422865152359008789e-01 |
| 2.240051180124282837e-01 9.346442818641662598e-01 |
| 4.766981601715087891e-01 5.025759935379028320e-01 |
| 4.914945065975189209e-01 6.310746073722839355e-01 |
| 3.344186246395111084e-01 7.780077457427978516e-01 |
| 4.686420261859893799e-01 9.309047460556030273e-02 |
| 9.773055315017700195e-01 2.856744229793548584e-01 |
| 5.354875326156616211e-01 3.497366011142730713e-01 |
| 8.493856787681579590e-01 2.987800371556659229e-06 |
| 6.208207607269287109e-01 4.205400347709655762e-01 |
| 2.042149901390075684e-01 2.506254315376281738e-01 |
| 2.360146641731262207e-01 7.235793471336364746e-01 |
| 6.975323706865310669e-02 1.412900090217590332e-01 |
| 6.645563244819641113e-01 3.121179342269897461e-01 |
| 4.053254127502441406e-01 5.518143773078918457e-01 |
| 1.206473484635353088e-01 4.734805822372436523e-01 |
| 8.648904561996459961e-01 1.023147404193878174e-01 |
| 8.161608576774597168e-01 8.317776322364807129e-01 |
| 6.927762031555175781e-01 9.478475451469421387e-01 |
| 2.968254983425140381e-01 8.038059473037719727e-01 |
| 6.430953741073608398e-01 9.910538792610168457e-01 |
| 2.968344092369079590e-01 1.735987961292266846e-01 |
| 9.531437754631042480e-01 7.520671486854553223e-01 |
| 4.183708727359771729e-01 7.117725014686584473e-01 |
| 6.463695168495178223e-01 5.298374295234680176e-01 |
| 4.360735416412353516e-01 3.724535107612609863e-01 |
| 3.108879625797271729e-01 6.105770468711853027e-01 |
| 6.875863075256347656e-01 2.569060325622558594e-01 |
| 3.497792780399322510e-01 3.365854322910308838e-01 |
| 3.896060585975646973e-02 5.422875285148620605e-01 |
| 9.432560205459594727e-01 1.412909328937530518e-01 |
| 9.300044178962707520e-01 4.165322482585906982e-01 |
| 7.353945374488830566e-01 5.118947029113769531e-01 |
| 1.327753961086273193e-01 7.520451545715332031e-01 |
| 5.486900806427001953e-01 5.976785421371459961e-01 |
| 2.729308903217315674e-01 4.913450479507446289e-01 |
| 9.396502971649169922e-01 7.046177387237548828e-01 |
| 3.496687412261962891e-01 8.545811772346496582e-01 |
| 4.515268206596374512e-01 2.997101247310638428e-01 |
| 6.290968656539916992e-01 7.653486132621765137e-01 |
| 7.602519392967224121e-01 4.815154075622558594e-01 |
| 2.523193135857582092e-02 7.953626513481140137e-01 |
| 8.745211362838745117e-01 3.598575592041015625e-01 |
|
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