| # MPMC pretrained pointset |
| # Contains following parameters (refer to QMCPy's MPMC documentation for more details): |
| # 'loss_fn': L2per |
| # '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 |
| 110 #n, the number of points |
| 2.135705798864364624e-01 2.397741526365280151e-01 |
| 9.378967434167861938e-02 6.396993398666381836e-01 |
| 2.567896544933319092e-01 3.596013784408569336e-01 |
| 4.658238887786865234e-01 6.320238709449768066e-01 |
| 5.842856168746948242e-01 3.486080169677734375e-01 |
| 6.298170089721679688e-01 2.504746913909912109e-01 |
| 6.923749446868896484e-01 7.400346398353576660e-01 |
| 2.248880267143249512e-02 9.864504337310791016e-01 |
| 7.381778955459594727e-01 4.489730000495910645e-01 |
| 1.193273533135652542e-02 3.943653404712677002e-01 |
| 2.182876458391547203e-03 9.991952776908874512e-01 |
| 9.494934082031250000e-01 9.482496976852416992e-02 |
| 9.110466837882995605e-01 8.401969671249389648e-01 |
| 1.110127195715904236e-01 5.045407414436340332e-01 |
| 7.207140326499938965e-01 8.211792707443237305e-01 |
| 8.206221461296081543e-01 4.016831889748573303e-02 |
| 5.874859914183616638e-02 3.047215938568115234e-01 |
| 3.677239418029785156e-01 7.241603136062622070e-01 |
| 3.309828639030456543e-01 6.579996943473815918e-01 |
| 7.305549979209899902e-01 2.238358184695243835e-02 |
| 4.125692546367645264e-01 3.862666785717010498e-01 |
| 2.308766841888427734e-01 4.957190155982971191e-02 |
| 3.748913705348968506e-01 1.864389926195144653e-01 |
| 3.395499289035797119e-01 2.674452364444732666e-01 |
| 7.040570974349975586e-01 6.221327185630798340e-01 |
| 9.848144650459289551e-01 4.861461818218231201e-01 |
| 7.576035261154174805e-01 8.671818971633911133e-01 |
| 2.201557755470275879e-01 6.771783828735351562e-01 |
| 6.393855810165405273e-01 9.576752781867980957e-01 |
| 3.032333850860595703e-01 7.768363356590270996e-01 |
| 8.759346604347229004e-01 5.939711630344390869e-02 |
| 4.392776787281036377e-01 3.225122988224029541e-01 |
| 8.575435280799865723e-01 5.231082439422607422e-01 |
| 7.626064121723175049e-02 8.034858703613281250e-01 |
| 9.215983152389526367e-01 1.494061499834060669e-01 |
| 5.942783355712890625e-01 9.133893251419067383e-01 |
| 1.945945471525192261e-01 4.054349064826965332e-01 |
| 8.929397463798522949e-01 7.045961022377014160e-01 |
| 7.657442688941955566e-01 2.960564196109771729e-01 |
| 9.386115670204162598e-01 7.857228517532348633e-01 |
| 3.940071165561676025e-01 4.940144717693328857e-01 |
| 3.491474092006683350e-01 1.613265601918101311e-03 |
| 6.209086179733276367e-01 6.872214674949645996e-01 |
| 2.936572432518005371e-01 1.408585458993911743e-01 |
| 4.202766716480255127e-01 8.874456882476806641e-01 |
| 4.882118478417396545e-02 6.938573718070983887e-01 |
| 5.486993789672851562e-01 7.956076860427856445e-01 |
| 4.763298630714416504e-01 6.608359515666961670e-02 |
| 5.308136343955993652e-01 5.590753555297851562e-01 |
| 1.483555138111114502e-01 5.855608582496643066e-01 |
| 4.306198060512542725e-01 7.115470170974731445e-01 |
| 5.121064782142639160e-01 2.853700220584869385e-01 |
| 1.761224418878555298e-01 7.496968507766723633e-01 |
| 5.034856796264648438e-01 5.947297215461730957e-01 |
| 1.405570954084396362e-01 9.493645429611206055e-01 |
| 6.862161159515380859e-01 1.942039579153060913e-01 |
| 7.856327891349792480e-01 5.491207242012023926e-01 |
| 3.014324977993965149e-02 5.662208199501037598e-01 |
| 6.037709712982177734e-01 5.130190253257751465e-01 |
| 9.945089221000671387e-01 7.310831546783447266e-01 |
| 2.025611698627471924e-01 8.771384358406066895e-01 |
| 8.670345544815063477e-01 6.501465439796447754e-01 |
| 8.850299715995788574e-01 2.768130004405975342e-01 |
| 3.127998411655426025e-01 4.409809708595275879e-01 |
| 4.495730996131896973e-01 8.583335280418395996e-01 |
| 5.402575135231018066e-01 8.559551090002059937e-02 |
| 1.299341171979904175e-01 3.407933115959167480e-01 |
| 8.124458789825439453e-01 7.584895491600036621e-01 |
| 2.494380027055740356e-01 8.143631219863891602e-01 |
| 8.303194642066955566e-01 4.678473472595214844e-01 |
| 8.398754596710205078e-01 1.771021187305450439e-01 |
| 2.388014793395996094e-01 5.413331389427185059e-01 |
| 5.572884678840637207e-01 4.763153195381164551e-01 |
| 1.212836205959320068e-01 8.498547077178955078e-01 |
| 7.497097849845886230e-01 5.786678791046142578e-01 |
| 5.664613842964172363e-01 1.592317223548889160e-01 |
| 4.843795895576477051e-01 4.231041669845581055e-01 |
| 6.565942168235778809e-01 3.765181303024291992e-01 |
| 9.318486452102661133e-01 4.305672943592071533e-01 |
| 2.676321268081665039e-01 9.396594762802124023e-01 |
| 2.848236262798309326e-01 6.047484874725341797e-01 |
| 7.936806678771972656e-01 8.939607143402099609e-01 |
| 3.850501179695129395e-01 9.230294823646545410e-01 |
| 9.674413800239562988e-01 9.039301872253417969e-01 |
| 5.763751864433288574e-01 7.673611640930175781e-01 |
| 1.579499244689941406e-01 7.731174677610397339e-02 |
| 6.764636635780334473e-01 4.123796820640563965e-01 |
| 3.869911283254623413e-02 2.586497664451599121e-01 |
| 1.845094859600067139e-01 1.678259074687957764e-01 |
| 6.674813628196716309e-01 9.775811433792114258e-01 |
| 4.945109486579895020e-01 8.319054245948791504e-01 |
| 7.754217386245727539e-01 1.126517951488494873e-01 |
| 8.039465546607971191e-01 3.314154148101806641e-01 |
| 8.494463562965393066e-01 9.318343997001647949e-01 |
| 9.041811227798461914e-01 3.671879172325134277e-01 |
| 6.491021513938903809e-01 6.672586202621459961e-01 |
| 6.125119328498840332e-01 1.303230971097946167e-01 |
| 9.757280349731445312e-01 2.219257503747940063e-01 |
| 1.662681251764297485e-01 4.588745236396789551e-01 |
| 1.038088127970695496e-01 1.221981421113014221e-01 |
| 3.203067183494567871e-01 3.114342689514160156e-02 |
| 6.624692678451538086e-02 9.671378135681152344e-01 |
| 9.570127129554748535e-01 6.121420264244079590e-01 |
| 3.575942516326904297e-01 5.304623246192932129e-01 |
| 4.036478400230407715e-01 1.050796657800674438e-01 |
| 4.579197466373443604e-01 2.140476107597351074e-01 |
| 8.532036840915679932e-02 2.031282782554626465e-01 |
| 7.131972908973693848e-01 2.314181029796600342e-01 |
| 5.210528373718261719e-01 1.117774099111557007e-02 |
| 2.763461768627166748e-01 3.116407394409179688e-01 |
|
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