| # MPMC pretrained pointset |
| # Contains following parameters (refer to QMCPy's MPMC documentation for more details): |
| # 'loss_fn': L2mix |
| # '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 |
| 4.343048334121704102e-01 8.405892252922058105e-01 |
| 7.386500835418701172e-01 7.534428238868713379e-01 |
| 4.180072844028472900e-01 7.328120470046997070e-01 |
| 5.739759206771850586e-01 9.950167536735534668e-01 |
| 9.303340315818786621e-01 3.557892441749572754e-01 |
| 6.051203012466430664e-01 5.434333086013793945e-01 |
| 9.089068770408630371e-01 8.230893611907958984e-01 |
| 3.252354860305786133e-01 5.113156437873840332e-01 |
| 8.642414808273315430e-01 2.150174826383590698e-01 |
| 5.284770205616950989e-02 7.619410753250122070e-01 |
| 2.934436500072479248e-01 6.224815845489501953e-01 |
| 8.385659456253051758e-01 2.936767339706420898e-01 |
| 5.351527929306030273e-01 1.295420974493026733e-01 |
| 9.033445119857788086e-01 1.139608249068260193e-01 |
| 4.879741668701171875e-01 7.228294610977172852e-01 |
| 2.620495259761810303e-01 8.276801556348800659e-02 |
| 6.135107278823852539e-01 7.688229084014892578e-01 |
| 3.703572154045104980e-01 4.020372927188873291e-01 |
| 3.628216087818145752e-01 6.830579042434692383e-01 |
| 1.516359001398086548e-01 4.261297583580017090e-01 |
| 9.489140510559082031e-01 3.946797251701354980e-01 |
| 5.584882497787475586e-01 1.532958596944808960e-01 |
| 8.302513360977172852e-01 7.932114601135253906e-01 |
| 9.629273414611816406e-01 4.952436983585357666e-01 |
| 7.450158596038818359e-01 1.382859051227569580e-01 |
| 7.938980460166931152e-01 4.345427453517913818e-01 |
| 4.953188300132751465e-01 4.191020429134368896e-01 |
| 8.090781569480895996e-01 6.918672323226928711e-01 |
| 6.284161806106567383e-01 4.495856761932373047e-01 |
| 2.155701518058776855e-01 1.912333667278289795e-01 |
| 5.820032358169555664e-01 3.402748405933380127e-01 |
| 4.650012254714965820e-01 6.521633267402648926e-01 |
| 4.728930890560150146e-01 9.856808185577392578e-01 |
| 3.157244026660919189e-01 3.315044641494750977e-01 |
| 2.068706452846527100e-01 5.756324529647827148e-01 |
| 4.014729261398315430e-01 2.154792658984661102e-02 |
| 2.851592004299163818e-01 7.778778672218322754e-01 |
| 1.291698664426803589e-01 9.187121391296386719e-01 |
| 7.690122127532958984e-01 8.547427654266357422e-01 |
| 7.776451706886291504e-01 5.588924288749694824e-01 |
| 9.166545271873474121e-01 2.687409520149230957e-01 |
| 9.555310606956481934e-01 9.244232177734375000e-01 |
| 2.394175082445144653e-01 3.639416992664337158e-01 |
| 9.808341860771179199e-01 6.657133996486663818e-02 |
| 1.982117444276809692e-01 1.752839833498001099e-01 |
| 9.934074878692626953e-01 5.813514590263366699e-01 |
| 8.544359803199768066e-01 4.588206708431243896e-01 |
| 1.927010715007781982e-01 9.020099639892578125e-01 |
| 3.388649523258209229e-01 1.206792816519737244e-01 |
| 4.340997338294982910e-02 2.631201446056365967e-01 |
| 7.088124155998229980e-01 6.299772262573242188e-01 |
| 1.142814308404922485e-01 6.051465272903442383e-01 |
| 6.606611609458923340e-01 5.039657950401306152e-01 |
| 7.540237307548522949e-01 5.982041358947753906e-01 |
| 1.614379435777664185e-01 4.420879781246185303e-01 |
| 4.793263375759124756e-01 2.238439619541168213e-01 |
| 3.329133987426757812e-01 9.417538046836853027e-01 |
| 3.537468910217285156e-01 2.467942535877227783e-01 |
| 8.157213926315307617e-01 2.393212169408798218e-01 |
| 8.009421229362487793e-01 9.622669219970703125e-01 |
| 3.870902359485626221e-01 1.987304389476776123e-01 |
| 2.469837665557861328e-01 9.714010953903198242e-01 |
| 8.932242989540100098e-01 6.604815721511840820e-01 |
| 6.370727419853210449e-01 7.135607600212097168e-01 |
| 1.443075537681579590e-01 6.680271625518798828e-01 |
| 8.868131637573242188e-01 3.477752208709716797e-02 |
| 8.713375329971313477e-01 5.288182497024536133e-01 |
| 1.685161143541336060e-01 4.567557480186223984e-03 |
| 7.230269908905029297e-01 9.775555133819580078e-01 |
| 1.841550320386886597e-01 4.651826918125152588e-01 |
| 7.303977012634277344e-01 3.798566758632659912e-01 |
| 3.802683055400848389e-01 5.901396274566650391e-01 |
| 5.108225345611572266e-01 8.307937383651733398e-01 |
| 1.747393608093261719e-01 8.483263254165649414e-01 |
| 8.291666209697723389e-02 3.874938786029815674e-01 |
| 7.149490118026733398e-01 8.908027410507202148e-02 |
| 1.213323101401329041e-01 1.051518768072128296e-01 |
| 6.523920297622680664e-01 9.106923937797546387e-01 |
| 9.038124233484268188e-02 9.572099447250366211e-01 |
| 2.980248816311359406e-02 5.352855920791625977e-01 |
| 6.757842898368835449e-01 6.748765110969543457e-01 |
| 8.241757154464721680e-01 2.534351497888565063e-02 |
| 1.357479393482208252e-01 2.319309562444686890e-01 |
| 2.687363922595977783e-01 8.161004185676574707e-01 |
| 9.403866529464721680e-01 3.238665461540222168e-01 |
| 5.272365212440490723e-01 3.714818358421325684e-01 |
| 9.719576686620712280e-02 1.605085432529449463e-01 |
| 5.426596403121948242e-01 8.070005178451538086e-01 |
| 9.873352646827697754e-01 7.380747795104980469e-01 |
| 5.995492264628410339e-02 3.091480135917663574e-01 |
| 3.001399636268615723e-01 1.309591159224510193e-02 |
| 6.699429452419281006e-02 5.154206976294517517e-02 |
| 4.783246666193008423e-03 7.075451612472534180e-01 |
| 6.839485168457031250e-01 3.020519614219665527e-01 |
| 8.469507694244384766e-01 7.834016084671020508e-01 |
| 3.637900575995445251e-02 8.799553513526916504e-01 |
| 6.917003393173217773e-01 8.715444207191467285e-01 |
| 1.306459214538335800e-02 4.894867241382598877e-01 |
| 2.546761929988861084e-01 3.486377596855163574e-01 |
| 7.490003854036331177e-02 7.998487353324890137e-01 |
| 4.253227710723876953e-01 2.856316566467285156e-01 |
| 5.035728216171264648e-01 7.377705723047256470e-02 |
| 2.224139869213104248e-01 7.463217377662658691e-01 |
| 5.968589782714843750e-01 2.075434625148773193e-01 |
| 8.787768483161926270e-01 8.860606551170349121e-01 |
| 6.200777888298034668e-01 5.724750459194183350e-02 |
| 5.668546557426452637e-01 4.733005166053771973e-01 |
| 3.086928725242614746e-01 6.991090774536132812e-01 |
| 3.483073413372039795e-01 8.644320964813232422e-01 |
| 3.955803811550140381e-01 9.318722486495971680e-01 |
| 2.317822128534317017e-01 5.509759187698364258e-01 |
| 6.998300552368164062e-01 4.102769494056701660e-01 |
| 4.412782490253448486e-01 3.166291117668151855e-01 |
| 7.619783878326416016e-01 1.680140942335128784e-01 |
| 9.245497584342956543e-01 9.484555125236511230e-01 |
| 1.046741157770156860e-01 6.439906358718872070e-01 |
| 1.985304430127143860e-02 1.436753422021865845e-01 |
| 5.897330641746520996e-01 8.941509723663330078e-01 |
| 2.775531709194183350e-01 2.768622934818267822e-01 |
| 6.445429325103759766e-01 2.558346390724182129e-01 |
| 4.087729156017303467e-01 4.819419980049133301e-01 |
| 4.498734176158905029e-01 5.209955573081970215e-01 |
| 7.854419350624084473e-01 1.837570071220397949e-01 |
| 6.675689816474914551e-01 9.888789802789688110e-02 |
| 9.708532691001892090e-01 6.372217535972595215e-01 |
| 5.189111232757568359e-01 5.676820278167724609e-01 |
| 4.572370052337646484e-01 4.329076781868934631e-02 |
| 5.515107512474060059e-01 6.140639781951904297e-01 |
|
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