code: def forward(self, *inputs):
      (t_358,) = inputs
      t_359 = t_358.permute(*[0, 3, 1, 2])
      t_359_padded = F.pad(t_359, [2, 3, 2, 3], value=0)
      t_360 = self.n_Conv_0(
          t_359_padded.to(self.n_Conv_0.bias.dtype)
          if devices.unet_needs_upcast
          else t_359_padded
      )
      t_361 = F.relu(t_360)
      t_361 = F.pad(t_361, [0, 1, 0, 1], value=float("-inf"))
      t_362 = self.n_MaxPool_0(t_361)
      t_363 = self.n_Conv_1(t_362)
      t_364 = self.n_Conv_2(t_362)
      t_365 = F.relu(t_364)
      t_365_padded = F.pad(t_365, [1, 1, 1, 1], value=0)
      t_366 = self.n_Conv_3(t_365_padded)
      t_367 = F.relu(t_366)
      t_368 = self.n_Conv_4(t_367)
      t_369 = torch.add(t_368, t_363)
      t_370 = F.relu(t_369)
      t_371 = self.n_Conv_5(t_370)
      t_372 = F.relu(t_371)
      t_372_padded = F.pad(t_372, [1, 1, 1, 1], value=0)
      t_373 = self.n_Conv_6(t_372_padded)
      t_374 = F.relu(t_373)
      t_375 = self.n_Conv_7(t_374)
      t_376 = torch.add(t_375, t_370)
      t_377 = F.relu(t_376)
      t_378 = self.n_Conv_8(t_377)
      t_379 = F.relu(t_378)
      t_379_padded = F.pad(t_379, [1, 1, 1, 1], value=0)
      t_380 = self.n_Conv_9(t_379_padded)
      t_381 = F.relu(t_380)
      t_382 = self.n_Conv_10(t_381)
      t_383 = torch.add(t_382, t_377)
      t_384 = F.relu(t_383)
      t_385 = self.n_Conv_11(t_384)
      t_386 = self.n_Conv_12(t_384)
      t_387 = F.relu(t_386)
      t_387_padded = F.pad(t_387, [0, 1, 0, 1], value=0)
      t_388 = self.n_Conv_13(t_387_padded)
      t_389 = F.relu(t_388)
      t_390 = self.n_Conv_14(t_389)
      t_391 = torch.add(t_390, t_385)
      t_392 = F.relu(t_391)
      t_393 = self.n_Conv_15(t_392)
      t_394 = F.relu(t_393)
      t_394_padded = F.pad(t_394, [1, 1, 1, 1], value=0)
      t_395 = self.n_Conv_16(t_394_padded)
      t_396 = F.relu(t_395)
      t_397 = self.n_Conv_17(t_396)
      t_398 = torch.add(t_397, t_392)
      t_399 = F.relu(t_398)
      t_400 = self.n_Conv_18(t_399)
      t_401 = F.relu(t_400)
      t_401_padded = F.pad(t_401, [1, 1, 1, 1], value=0)
      t_402 = self.n_Conv_19(t_401_padded)
      t_403 = F.relu(t_402)
      t_404 = self.n_Conv_20(t_403)
      t_405 = torch.add(t_404, t_399)
      t_406 = F.relu(t_405)
      t_407 = self.n_Conv_21(t_406)
      t_408 = F.relu(t_407)
      t_408_padded = F.pad(t_408, [1, 1, 1, 1], value=0)
      t_409 = self.n_Conv_22(t_408_padded)
      t_410 = F.relu(t_409)
      t_411 = self.n_Conv_23(t_410)
      t_412 = torch.add(t_411, t_406)
      t_413 = F.relu(t_412)
      t_414 = self.n_Conv_24(t_413)
      t_415 = F.relu(t_414)
      t_415_padded = F.pad(t_415, [1, 1, 1, 1], value=0)
      t_416 = self.n_Conv_25(t_415_padded)
      t_417 = F.relu(t_416)
      t_418 = self.n_Conv_26(t_417)
      t_419 = torch.add(t_418, t_413)
      t_420 = F.relu(t_419)
      t_421 = self.n_Conv_27(t_420)
      t_422 = F.relu(t_421)
      t_422_padded = F.pad(t_422, [1, 1, 1, 1], value=0)
      t_423 = self.n_Conv_28(t_422_padded)
      t_424 = F.relu(t_423)
      t_425 = self.n_Conv_29(t_424)
      t_426 = torch.add(t_425, t_420)
      t_427 = F.relu(t_426)
      t_428 = self.n_Conv_30(t_427)
      t_429 = F.relu(t_428)
      t_429_padded = F.pad(t_429, [1, 1, 1, 1], value=0)
      t_430 = self.n_Conv_31(t_429_padded)
      t_431 = F.relu(t_430)
      t_432 = self.n_Conv_32(t_431)
      t_433 = torch.add(t_432, t_427)
      t_434 = F.relu(t_433)
      t_435 = self.n_Conv_33(t_434)
      t_436 = F.relu(t_435)
      t_436_padded = F.pad(t_436, [1, 1, 1, 1], value=0)
      t_437 = self.n_Conv_34(t_436_padded)
      t_438 = F.relu(t_437)
      t_439 = self.n_Conv_35(t_438)
      t_440 = torch.add(t_439, t_434)
      t_441 = F.relu(t_440)
      t_442 = self.n_Conv_36(t_441)
      t_443 = self.n_Conv_37(t_441)
      t_444 = F.relu(t_443)
      t_444_padded = F.pad(t_444, [0, 1, 0, 1], value=0)
      t_445 = self.n_Conv_38(t_444_padded)
      t_446 = F.relu(t_445)
      t_447 = self.n_Conv_39(t_446)
      t_448 = torch.add(t_447, t_442)
      t_449 = F.relu(t_448)
      t_450 = self.n_Conv_40(t_449)
      t_451 = F.relu(t_450)
      t_451_padded = F.pad(t_451, [1, 1, 1, 1], value=0)
      t_452 = self.n_Conv_41(t_451_padded)
      t_453 = F.relu(t_452)
      t_454 = self.n_Conv_42(t_453)
      t_455 = torch.add(t_454, t_449)
      t_456 = F.relu(t_455)
      t_457 = self.n_Conv_43(t_456)
      t_458 = F.relu(t_457)
      t_458_padded = F.pad(t_458, [1, 1, 1, 1], value=0)
      t_459 = self.n_Conv_44(t_458_padded)
      t_460 = F.relu(t_459)
      t_461 = self.n_Conv_45(t_460)
      t_462 = torch.add(t_461, t_456)
      t_463 = F.relu(t_462)
      t_464 = self.n_Conv_46(t_463)
      t_465 = F.relu(t_464)
      t_465_padded = F.pad(t_465, [1, 1, 1, 1], value=0)
      t_466 = self.n_Conv_47(t_465_padded)
      t_467 = F.relu(t_466)
      t_468 = self.n_Conv_48(t_467)
      t_469 = torch.add(t_468, t_463)
      t_470 = F.relu(t_469)
      t_471 = self.n_Conv_49(t_470)
      t_472 = F.relu(t_471)
      t_472_padded = F.pad(t_472, [1, 1, 1, 1], value=0)
      t_473 = self.n_Conv_50(t_472_padded)
      t_474 = F.relu(t_473)
      t_475 = self.n_Conv_51(t_474)
      t_476 = torch.add(t_475, t_470)
      t_477 = F.relu(t_476)
      t_478 = self.n_Conv_52(t_477)
      t_479 = F.relu(t_478)
      t_479_padded = F.pad(t_479, [1, 1, 1, 1], value=0)
      t_480 = self.n_Conv_53(t_479_padded)
      t_481 = F.relu(t_480)
      t_482 = self.n_Conv_54(t_481)
      t_483 = torch.add(t_482, t_477)
      t_484 = F.relu(t_483)
      t_485 = self.n_Conv_55(t_484)
      t_486 = F.relu(t_485)
      t_486_padded = F.pad(t_486, [1, 1, 1, 1], value=0)
      t_487 = self.n_Conv_56(t_486_padded)
      t_488 = F.relu(t_487)
      t_489 = self.n_Conv_57(t_488)
      t_490 = torch.add(t_489, t_484)
      t_491 = F.relu(t_490)
      t_492 = self.n_Conv_58(t_491)
      t_493 = F.relu(t_492)
      t_493_padded = F.pad(t_493, [1, 1, 1, 1], value=0)
      t_494 = self.n_Conv_59(t_493_padded)
      t_495 = F.relu(t_494)
      t_496 = self.n_Conv_60(t_495)
      t_497 = torch.add(t_496, t_491)
      t_498 = F.relu(t_497)
      t_499 = self.n_Conv_61(t_498)
      t_500 = F.relu(t_499)
      t_500_padded = F.pad(t_500, [1, 1, 1, 1], value=0)
      t_501 = self.n_Conv_62(t_500_padded)
      t_502 = F.relu(t_501)
      t_503 = self.n_Conv_63(t_502)
      t_504 = torch.add(t_503, t_498)
      t_505 = F.relu(t_504)
      t_506 = self.n_Conv_64(t_505)
      t_507 = F.relu(t_506)
      t_507_padded = F.pad(t_507, [1, 1, 1, 1], value=0)
      t_508 = self.n_Conv_65(t_507_padded)
      t_509 = F.relu(t_508)
      t_510 = self.n_Conv_66(t_509)
      t_511 = torch.add(t_510, t_505)
      t_512 = F.relu(t_511)
      t_513 = self.n_Conv_67(t_512)
      t_514 = F.relu(t_513)
      t_514_padded = F.pad(t_514, [1, 1, 1, 1], value=0)
      t_515 = self.n_Conv_68(t_514_padded)
      t_516 = F.relu(t_515)
      t_517 = self.n_Conv_69(t_516)
      t_518 = torch.add(t_517, t_512)
      t_519 = F.relu(t_518)
      t_520 = self.n_Conv_70(t_519)
      t_521 = F.relu(t_520)
      t_521_padded = F.pad(t_521, [1, 1, 1, 1], value=0)
      t_522 = self.n_Conv_71(t_521_padded)
      t_523 = F.relu(t_522)
      t_524 = self.n_Conv_72(t_523)
      t_525 = torch.add(t_524, t_519)
      t_526 = F.relu(t_525)
      t_527 = self.n_Conv_73(t_526)
      t_528 = F.relu(t_527)
      t_528_padded = F.pad(t_528, [1, 1, 1, 1], value=0)
      t_529 = self.n_Conv_74(t_528_padded)
      t_530 = F.relu(t_529)
      t_531 = self.n_Conv_75(t_530)
      t_532 = torch.add(t_531, t_526)
      t_533 = F.relu(t_532)
      t_534 = self.n_Conv_76(t_533)
      t_535 = F.relu(t_534)
      t_535_padded = F.pad(t_535, [1, 1, 1, 1], value=0)
      t_536 = self.n_Conv_77(t_535_padded)
      t_537 = F.relu(t_536)
      t_538 = self.n_Conv_78(t_537)
      t_539 = torch.add(t_538, t_533)
      t_540 = F.relu(t_539)
      t_541 = self.n_Conv_79(t_540)
      t_542 = F.relu(t_541)
      t_542_padded = F.pad(t_542, [1, 1, 1, 1], value=0)
      t_543 = self.n_Conv_80(t_542_padded)
      t_544 = F.relu(t_543)
      t_545 = self.n_Conv_81(t_544)
      t_546 = torch.add(t_545, t_540)
      t_547 = F.relu(t_546)
      t_548 = self.n_Conv_82(t_547)
      t_549 = F.relu(t_548)
      t_549_padded = F.pad(t_549, [1, 1, 1, 1], value=0)
      t_550 = self.n_Conv_83(t_549_padded)
      t_551 = F.relu(t_550)
      t_552 = self.n_Conv_84(t_551)
      t_553 = torch.add(t_552, t_547)
      t_554 = F.relu(t_553)
      t_555 = self.n_Conv_85(t_554)
      t_556 = F.relu(t_555)
      t_556_padded = F.pad(t_556, [1, 1, 1, 1], value=0)
      t_557 = self.n_Conv_86(t_556_padded)
      t_558 = F.relu(t_557)
      t_559 = self.n_Conv_87(t_558)
      t_560 = torch.add(t_559, t_554)
      t_561 = F.relu(t_560)
      t_562 = self.n_Conv_88(t_561)
      t_563 = F.relu(t_562)
      t_563_padded = F.pad(t_563, [1, 1, 1, 1], value=0)
      t_564 = self.n_Conv_89(t_563_padded)
      t_565 = F.relu(t_564)
      t_566 = self.n_Conv_90(t_565)
      t_567 = torch.add(t_566, t_561)
      t_568 = F.relu(t_567)
      t_569 = self.n_Conv_91(t_568)
      t_570 = F.relu(t_569)
      t_570_padded = F.pad(t_570, [1, 1, 1, 1], value=0)
      t_571 = self.n_Conv_92(t_570_padded)
      t_572 = F.relu(t_571)
      t_573 = self.n_Conv_93(t_572)
      t_574 = torch.add(t_573, t_568)
      t_575 = F.relu(t_574)
      t_576 = self.n_Conv_94(t_575)
      t_577 = F.relu(t_576)
      t_577_padded = F.pad(t_577, [1, 1, 1, 1], value=0)
      t_578 = self.n_Conv_95(t_577_padded)
      t_579 = F.relu(t_578)
      t_580 = self.n_Conv_96(t_579)
      t_581 = torch.add(t_580, t_575)
      t_582 = F.relu(t_581)
      t_583 = self.n_Conv_97(t_582)
      t_584 = F.relu(t_583)
      t_584_padded = F.pad(t_584, [0, 1, 0, 1], value=0)
      t_585 = self.n_Conv_98(t_584_padded)
      t_586 = F.relu(t_585)
      t_587 = self.n_Conv_99(t_586)
      t_588 = self.n_Conv_100(t_582)
      t_589 = torch.add(t_587, t_588)
      t_590 = F.relu(t_589)
      t_591 = self.n_Conv_101(t_590)
      t_592 = F.relu(t_591)
      t_592_padded = F.pad(t_592, [1, 1, 1, 1], value=0)
      t_593 = self.n_Conv_102(t_592_padded)
      t_594 = F.relu(t_593)
      t_595 = self.n_Conv_103(t_594)
      t_596 = torch.add(t_595, t_590)
      t_597 = F.relu(t_596)
      t_598 = self.n_Conv_104(t_597)
      t_599 = F.relu(t_598)
      t_599_padded = F.pad(t_599, [1, 1, 1, 1], value=0)
      t_600 = self.n_Conv_105(t_599_padded)
      t_601 = F.relu(t_600)
      t_602 = self.n_Conv_106(t_601)
      t_603 = torch.add(t_602, t_597)
      t_604 = F.relu(t_603)
      t_605 = self.n_Conv_107(t_604)
      t_606 = F.relu(t_605)
      t_606_padded = F.pad(t_606, [1, 1, 1, 1], value=0)
      t_607 = self.n_Conv_108(t_606_padded)
      t_608 = F.relu(t_607)
      t_609 = self.n_Conv_109(t_608)
      t_610 = torch.add(t_609, t_604)
      t_611 = F.relu(t_610)
      t_612 = self.n_Conv_110(t_611)
      t_613 = F.relu(t_612)
      t_613_padded = F.pad(t_613, [1, 1, 1, 1], value=0)
      t_614 = self.n_Conv_111(t_613_padded)
      t_615 = F.relu(t_614)
      t_616 = self.n_Conv_112(t_615)
      t_617 = torch.add(t_616, t_611)
      t_618 = F.relu(t_617)
      t_619 = self.n_Conv_113(t_618)
      t_620 = F.relu(t_619)
      t_620_padded = F.pad(t_620, [1, 1, 1, 1], value=0)
      t_621 = self.n_Conv_114(t_620_padded)
      t_622 = F.relu(t_621)
      t_623 = self.n_Conv_115(t_622)
      t_624 = torch.add(t_623, t_618)
      t_625 = F.relu(t_624)
      t_626 = self.n_Conv_116(t_625)
      t_627 = F.relu(t_626)
      t_627_padded = F.pad(t_627, [1, 1, 1, 1], value=0)
      t_628 = self.n_Conv_117(t_627_padded)
      t_629 = F.relu(t_628)
      t_630 = self.n_Conv_118(t_629)
      t_631 = torch.add(t_630, t_625)
      t_632 = F.relu(t_631)
      t_633 = self.n_Conv_119(t_632)
      t_634 = F.relu(t_633)
      t_634_padded = F.pad(t_634, [1, 1, 1, 1], value=0)
      t_635 = self.n_Conv_120(t_634_padded)
      t_636 = F.relu(t_635)
      t_637 = self.n_Conv_121(t_636)
      t_638 = torch.add(t_637, t_632)
      t_639 = F.relu(t_638)
      t_640 = self.n_Conv_122(t_639)
      t_641 = F.relu(t_640)
      t_641_padded = F.pad(t_641, [1, 1, 1, 1], value=0)
      t_642 = self.n_Conv_123(t_641_padded)
      t_643 = F.relu(t_642)
      t_644 = self.n_Conv_124(t_643)
      t_645 = torch.add(t_644, t_639)
      t_646 = F.relu(t_645)
      t_647 = self.n_Conv_125(t_646)
      t_648 = F.relu(t_647)
      t_648_padded = F.pad(t_648, [1, 1, 1, 1], value=0)
      t_649 = self.n_Conv_126(t_648_padded)
      t_650 = F.relu(t_649)
      t_651 = self.n_Conv_127(t_650)
      t_652 = torch.add(t_651, t_646)
      t_653 = F.relu(t_652)
      t_654 = self.n_Conv_128(t_653)
      t_655 = F.relu(t_654)
      t_655_padded = F.pad(t_655, [1, 1, 1, 1], value=0)
      t_656 = self.n_Conv_129(t_655_padded)
      t_657 = F.relu(t_656)
      t_658 = self.n_Conv_130(t_657)
      t_659 = torch.add(t_658, t_653)
      t_660 = F.relu(t_659)
      t_661 = self.n_Conv_131(t_660)
      t_662 = F.relu(t_661)
      t_662_padded = F.pad(t_662, [1, 1, 1, 1], value=0)
      t_663 = self.n_Conv_132(t_662_padded)
      t_664 = F.relu(t_663)
      t_665 = self.n_Conv_133(t_664)
      t_666 = torch.add(t_665, t_660)
      t_667 = F.relu(t_666)
      t_668 = self.n_Conv_134(t_667)
      t_669 = F.relu(t_668)
      t_669_padded = F.pad(t_669, [1, 1, 1, 1], value=0)
      t_670 = self.n_Conv_135(t_669_padded)
      t_671 = F.relu(t_670)
      t_672 = self.n_Conv_136(t_671)
      t_673 = torch.add(t_672, t_667)
      t_674 = F.relu(t_673)
      t_675 = self.n_Conv_137(t_674)
      t_676 = F.relu(t_675)
      t_676_padded = F.pad(t_676, [1, 1, 1, 1], value=0)
      t_677 = self.n_Conv_138(t_676_padded)
      t_678 = F.relu(t_677)
      t_679 = self.n_Conv_139(t_678)
      t_680 = torch.add(t_679, t_674)
      t_681 = F.relu(t_680)
      t_682 = self.n_Conv_140(t_681)
      t_683 = F.relu(t_682)
      t_683_padded = F.pad(t_683, [1, 1, 1, 1], value=0)
      t_684 = self.n_Conv_141(t_683_padded)
      t_685 = F.relu(t_684)
      t_686 = self.n_Conv_142(t_685)
      t_687 = torch.add(t_686, t_681)
      t_688 = F.relu(t_687)
      t_689 = self.n_Conv_143(t_688)
      t_690 = F.relu(t_689)
      t_690_padded = F.pad(t_690, [1, 1, 1, 1], value=0)
      t_691 = self.n_Conv_144(t_690_padded)
      t_692 = F.relu(t_691)
      t_693 = self.n_Conv_145(t_692)
      t_694 = torch.add(t_693, t_688)
      t_695 = F.relu(t_694)
      t_696 = self.n_Conv_146(t_695)
      t_697 = F.relu(t_696)
      t_697_padded = F.pad(t_697, [1, 1, 1, 1], value=0)
      t_698 = self.n_Conv_147(t_697_padded)
      t_699 = F.relu(t_698)
      t_700 = self.n_Conv_148(t_699)
      t_701 = torch.add(t_700, t_695)
      t_702 = F.relu(t_701)
      t_703 = self.n_Conv_149(t_702)
      t_704 = F.relu(t_703)
      t_704_padded = F.pad(t_704, [1, 1, 1, 1], value=0)
      t_705 = self.n_Conv_150(t_704_padded)
      t_706 = F.relu(t_705)
      t_707 = self.n_Conv_151(t_706)
      t_708 = torch.add(t_707, t_702)
      t_709 = F.relu(t_708)
      t_710 = self.n_Conv_152(t_709)
      t_711 = F.relu(t_710)
      t_711_padded = F.pad(t_711, [1, 1, 1, 1], value=0)
      t_712 = self.n_Conv_153(t_711_padded)
      t_713 = F.relu(t_712)
      t_714 = self.n_Conv_154(t_713)
      t_715 = torch.add(t_714, t_709)
      t_716 = F.relu(t_715)
      t_717 = self.n_Conv_155(t_716)
      t_718 = F.relu(t_717)
      t_718_padded = F.pad(t_718, [1, 1, 1, 1], value=0)
      t_719 = self.n_Conv_156(t_718_padded)
      t_720 = F.relu(t_719)
      t_721 = self.n_Conv_157(t_720)
      t_722 = torch.add(t_721, t_716)
      t_723 = F.relu(t_722)
      t_724 = self.n_Conv_158(t_723)
      t_725 = self.n_Conv_159(t_723)
      t_726 = F.relu(t_725)
      t_726_padded = F.pad(t_726, [0, 1, 0, 1], value=0)
      t_727 = self.n_Conv_160(t_726_padded)
      t_728 = F.relu(t_727)
      t_729 = self.n_Conv_161(t_728)
      t_730 = torch.add(t_729, t_724)
      t_731 = F.relu(t_730)
      t_732 = self.n_Conv_162(t_731)
      t_733 = F.relu(t_732)
      t_733_padded = F.pad(t_733, [1, 1, 1, 1], value=0)
      t_734 = self.n_Conv_163(t_733_padded)
      t_735 = F.relu(t_734)
      t_736 = self.n_Conv_164(t_735)
      t_737 = torch.add(t_736, t_731)
      t_738 = F.relu(t_737)
      t_739 = self.n_Conv_165(t_738)
      t_740 = F.relu(t_739)
      t_740_padded = F.pad(t_740, [1, 1, 1, 1], value=0)
      t_741 = self.n_Conv_166(t_740_padded)
      t_742 = F.relu(t_741)
      t_743 = self.n_Conv_167(t_742)
      t_744 = torch.add(t_743, t_738)
      t_745 = F.relu(t_744)
      t_746 = self.n_Conv_168(t_745)
      t_747 = self.n_Conv_169(t_745)
      t_748 = F.relu(t_747)
      t_748_padded = F.pad(t_748, [0, 1, 0, 1], value=0)
      t_749 = self.n_Conv_170(t_748_padded)
      t_750 = F.relu(t_749)
      t_751 = self.n_Conv_171(t_750)
      t_752 = torch.add(t_751, t_746)
      t_753 = F.relu(t_752)
      t_754 = self.n_Conv_172(t_753)
      t_755 = F.relu(t_754)
      t_755_padded = F.pad(t_755, [1, 1, 1, 1], value=0)
      t_756 = self.n_Conv_173(t_755_padded)
      t_757 = F.relu(t_756)
      t_758 = self.n_Conv_174(t_757)
      t_759 = torch.add(t_758, t_753)
      t_760 = F.relu(t_759)
      t_761 = self.n_Conv_175(t_760)
      t_762 = F.relu(t_761)
      t_762_padded = F.pad(t_762, [1, 1, 1, 1], value=0)
      t_763 = self.n_Conv_176(t_762_padded)
      t_764 = F.relu(t_763)
      t_765 = self.n_Conv_177(t_764)
      t_766 = torch.add(t_765, t_760)
      t_767 = F.relu(t_766)
      t_768 = self.n_Conv_178(t_767)
      t_769 = F.avg_pool2d(t_768, kernel_size=t_768.shape[-2:])
      t_770 = torch.squeeze(t_769, 3)
      t_770 = torch.squeeze(t_770, 2)
      t_771 = torch.sigmoid(t_770)
      return t_771
  
file_path: stable-diffusion-webui/modules/deepbooru_model.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from modules import devices
label_desc: Use image node_id 2 for calling the DeepDanbooruModel obj's underlying member method code with example usage: obj.forward() and returns: t_771