resnext with groupnorm

codes/models/networks.py

@@ -13,6 +13,7 @@ import models.archs.StructuredSwitchedGenerator as ssg
 import models.archs.rcan as rcan
 from collections import OrderedDict
 import torchvision
+import functools
 
 logger = logging.getLogger('base')
 
@@ -128,7 +129,9 @@ def define_D_net(opt_net, img_sz=None, wrap=False):
                                                                    number_skips=opt_net['number_skips'], use_bn=True,
                                                                    disable_passthrough=opt_net['disable_passthrough'])
     elif which_model == 'resnext':
-        netD = torchvision.models.resnext50_32x4d(pretrained=True)
+        netD = torchvision.models.resnext50_32x4d(norm_layer=functools.partial(torch.nn.GroupNorm, 8))
+        state_dict = torch.hub.load_state_dict_from_url('https://download.pytorch.org/models/resnext50_32x4d-7cdf4587.pth', progress=True)
+        netD.load_state_dict(state_dict, strict=False)
         netD.fc = torch.nn.Linear(512 * 4, 1)
     elif which_model == 'discriminator_pix':
         netD = SRGAN_arch.Discriminator_VGG_PixLoss(in_nc=opt_net['in_nc'], nf=opt_net['nf'])