| # MPMC pretrained pointset |
| # Contains following parameters (refer to QMCPy's MPMC documentation for more details): |
| # 'loss_fn': L2ext |
| # '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 |
| 8.588177561759948730e-01 1.816387176513671875e-01 |
| 8.067179918289184570e-01 7.798002362251281738e-01 |
| 7.238276004791259766e-01 4.117000401020050049e-01 |
| 1.706475466489791870e-01 1.799671351909637451e-01 |
| 1.248717755079269409e-01 3.931068778038024902e-01 |
| 2.151023149490356445e-01 7.508050203323364258e-01 |
| 1.362152248620986938e-01 7.212995290756225586e-01 |
| 2.348240464925765991e-01 9.140321612358093262e-01 |
| 6.746941804885864258e-01 8.161216378211975098e-01 |
| 3.457838296890258789e-01 1.609008163213729858e-01 |
| 3.940463960170745850e-01 8.951222896575927734e-01 |
| 2.590649127960205078e-01 3.677228391170501709e-01 |
| 5.691000819206237793e-01 9.984333813190460205e-02 |
| 1.963715702295303345e-01 5.745580792427062988e-01 |
| 7.401229143142700195e-01 6.257956475019454956e-02 |
| 2.819944322109222412e-01 5.137329697608947754e-01 |
| 9.948354214429855347e-03 9.900090694427490234e-01 |
| 4.485177695751190186e-01 1.949138641357421875e-01 |
| 1.693260483443737030e-02 9.989932179450988770e-01 |
| 8.873999714851379395e-01 8.654607534408569336e-01 |
| 5.653901100158691406e-01 9.608898758888244629e-01 |
| 8.136529326438903809e-01 3.189554810523986816e-01 |
| 8.682048320770263672e-01 6.037122011184692383e-01 |
| 5.066686496138572693e-02 6.908753514289855957e-01 |
| 9.977954626083374023e-01 3.185405861586332321e-03 |
| 2.271494120359420776e-01 4.679342210292816162e-01 |
| 4.639739394187927246e-01 8.360841870307922363e-01 |
| 3.361839056015014648e-01 4.222413599491119385e-01 |
| 9.499637037515640259e-02 9.413071274757385254e-01 |
| 6.188964843750000000e-01 7.585938572883605957e-01 |
| 2.946135103702545166e-01 8.055919408798217773e-01 |
| 9.218217134475708008e-01 4.307736158370971680e-01 |
| 9.614081382751464844e-01 2.531606554985046387e-01 |
| 7.697411179542541504e-01 3.872906267642974854e-01 |
| 8.260829448699951172e-01 5.441244244575500488e-01 |
| 8.345544934272766113e-01 8.891696929931640625e-01 |
| 3.054270744323730469e-01 3.263386189937591553e-01 |
| 6.492610573768615723e-01 3.369037806987762451e-01 |
| 9.314963966608047485e-02 2.504654228687286377e-01 |
| 2.755228579044342041e-01 2.217994034290313721e-01 |
| 4.131611883640289307e-01 2.363703250885009766e-01 |
| 2.681577503681182861e-01 8.594430685043334961e-01 |
| 5.962784886360168457e-01 2.081226855516433716e-01 |
| 3.357852622866630554e-02 5.502131581306457520e-01 |
| 1.923434808850288391e-02 4.243998825550079346e-01 |
| 5.560123920440673828e-01 5.650271773338317871e-01 |
| 8.789664506912231445e-01 4.801219999790191650e-01 |
| 6.892364621162414551e-01 1.718737035989761353e-01 |
| 7.092026472091674805e-01 2.441061139106750488e-01 |
| 1.069132536649703979e-01 6.069037318229675293e-01 |
| 1.160434931516647339e-01 8.732728958129882812e-01 |
| 5.298950672149658203e-01 6.599952578544616699e-01 |
| 9.334494471549987793e-01 8.304838538169860840e-01 |
| 7.940327525138854980e-01 5.204943418502807617e-01 |
| 6.668412089347839355e-01 5.065574124455451965e-02 |
| 2.021677941083908081e-01 2.012116648256778717e-02 |
| 4.322195649147033691e-01 8.447994291782379150e-02 |
| 6.575556993484497070e-01 6.263480186462402344e-01 |
| 8.983448147773742676e-01 3.616892993450164795e-01 |
| 4.242451488971710205e-01 5.347565412521362305e-01 |
| 3.693556487560272217e-01 4.082053899765014648e-02 |
| 7.537337541580200195e-01 2.775904238224029541e-01 |
| 9.982520937919616699e-01 2.262408612295985222e-03 |
| 7.304950356483459473e-01 7.425359487533569336e-01 |
| 1.752310991287231445e-01 8.270373940467834473e-01 |
| 6.457971930503845215e-01 9.470579028129577637e-01 |
| 3.913844227790832520e-01 2.899002134799957275e-01 |
| 3.474268615245819092e-01 9.331641197204589844e-01 |
| 9.143344163894653320e-01 7.806141674518585205e-02 |
| 1.613139808177947998e-01 4.476184546947479248e-01 |
| 8.518124222755432129e-01 6.828702092170715332e-01 |
| 2.395066916942596436e-01 1.135418638586997986e-01 |
| 2.479493021965026855e-01 6.383264660835266113e-01 |
| 1.853247880935668945e-01 3.033084571361541748e-01 |
| 3.685371279716491699e-01 6.729919910430908203e-01 |
| 5.458434820175170898e-01 3.091435730457305908e-01 |
| 7.472265958786010742e-01 6.477519273757934570e-01 |
| 8.301816135644912720e-02 5.005412697792053223e-01 |
| 9.859492182731628418e-01 2.907449938356876373e-02 |
| 5.744682550430297852e-01 3.771277964115142822e-01 |
| 6.814934611320495605e-01 4.536852836608886719e-01 |
| 2.109703719615936279e-01 2.701323330402374268e-01 |
| 2.649969235062599182e-02 9.530103802680969238e-01 |
| 7.017231732606887817e-02 7.869927883148193359e-01 |
| 7.078748345375061035e-01 9.248071908950805664e-01 |
| 7.618176341056823730e-01 9.067243337631225586e-01 |
| 5.823977589607238770e-01 6.937569379806518555e-01 |
| 6.278482675552368164e-01 1.497049033641815186e-01 |
| 6.332848966121673584e-02 3.466224372386932373e-01 |
| 4.854869842529296875e-01 6.126756668090820312e-01 |
| 5.237798206508159637e-03 9.995052814483642578e-01 |
| 4.039681255817413330e-01 7.035509347915649414e-01 |
| 5.084528923034667969e-01 2.625024020671844482e-01 |
| 9.814144968986511230e-01 7.225477099418640137e-01 |
| 9.382015466690063477e-01 2.967989146709442139e-01 |
| 6.990102529525756836e-01 5.824998617172241211e-01 |
| 5.972340106964111328e-01 8.484829068183898926e-01 |
| 9.488555788993835449e-01 5.639770627021789551e-01 |
| 4.371511042118072510e-01 7.303499579429626465e-01 |
| 3.805669844150543213e-01 4.031933844089508057e-01 |
| 5.404224395751953125e-01 2.740616537630558014e-02 |
| 9.686371684074401855e-01 6.398410797119140625e-01 |
| 4.734116494655609131e-01 3.540888428688049316e-01 |
| 8.872366547584533691e-01 1.089265942573547363e-01 |
| 6.076033115386962891e-01 4.730514287948608398e-01 |
| 4.459389746189117432e-01 9.729503989219665527e-01 |
| 2.958698570728302002e-01 6.855778396129608154e-02 |
| 3.560162782669067383e-01 5.930588841438293457e-01 |
| 6.349363923072814941e-01 5.062152743339538574e-01 |
| 4.341470450162887573e-02 2.066528350114822388e-01 |
| 4.562553167343139648e-01 4.914864301681518555e-01 |
| 7.855176925659179688e-01 1.251506954431533813e-01 |
| 6.834132131189107895e-03 9.996619224548339844e-01 |
| 3.147247135639190674e-01 5.511440038681030273e-01 |
| 9.934881925582885742e-01 8.946131914854049683e-03 |
| 3.270889520645141602e-01 7.694823741912841797e-01 |
| 4.933090507984161377e-01 1.330203264951705933e-01 |
| 1.411261558532714844e-01 1.390464901924133301e-01 |
| 5.180105566978454590e-01 4.376872181892395020e-01 |
| 7.800667881965637207e-01 7.144446372985839844e-01 |
| 9.089400768280029297e-01 7.973319292068481445e-01 |
| 5.024857521057128906e-01 7.911017537117004395e-01 |
| 2.035298794507980347e-01 9.821164011955261230e-01 |
| 1.528147011995315552e-01 6.556885838508605957e-01 |
| 5.360400676727294922e-01 8.782836794853210449e-01 |
| 1.064601019024848938e-01 9.455060958862304688e-02 |
| 9.843811988830566406e-01 3.828712180256843567e-02 |
| 8.383479118347167969e-01 2.196310609579086304e-01 |
|
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