| 494 | |
| 495 | class MappingF(nn.Module): |
| 496 | def __init__(self, in_layer=4, gpu_ids=[], nc=256, patch_num=256, dim=64, init_type='normal', init_gain=0.02): |
| 497 | # hard-coded code. |
| 498 | super().__init__() |
| 499 | self.init_type = init_type |
| 500 | self.nc=nc |
| 501 | self.dim=dim |
| 502 | self.in_layer=in_layer |
| 503 | self.patch_num = patch_num |
| 504 | self.init_type = init_type |
| 505 | self.init_gain = init_gain |
| 506 | self.gpu_ids = gpu_ids |
| 507 | avg = nn.AdaptiveAvgPool2d(1) |
| 508 | conv = nn.Conv2d(in_layer, dim, 3, stride=2) |
| 509 | self.model = nn.Sequential(*[conv, nn.ReLU(), avg, nn.Flatten(), nn.Linear(dim,dim), nn.ReLU(), nn.Linear(dim, dim)]) |
| 510 | init_net(self.model, self.init_type, self.init_gain, self.gpu_ids) |
| 511 | self.l2norm = Normalize(2) |
| 512 | |
| 513 | def forward(self, x): |
| 514 | x = x.view(1, -1, self.patch_num, self.nc) |