Update

2 files changed, 2 insertions, 8 deletions

diff --git a/models/convnext/discriminator.py b/models/convnext/discriminator.py
index 7dbbe3a..571b915 100644
--- a/models/convnext/discriminator.py
+++ b/models/convnext/discriminator.py
@@ -15,13 +15,7 @@ class ConvNeXtDiscriminator():
         self.img_std = torch.tensor(IMAGENET_DEFAULT_STD).view(1, -1, 1, 1)
 
     def get_score(self, img):
-        img_mean = self.img_mean.to(device=img.device, dtype=img.dtype)
-        img_std = self.img_std.to(device=img.device, dtype=img.dtype)
-
-        img = ((img+1.)/2.).sub(img_mean).div(img_std)
-
-        img = F.interpolate(img, size=(self.input_size, self.input_size), mode='bicubic', align_corners=True)
-        pred = self.net(img)
+        pred = self.get_all(img)
         return torch.softmax(pred, dim=-1)[:, 1]
 
     def get_all(self, img):
diff --git a/models/sparse.py b/models/sparse.py
index bcb2897..07b3413 100644
--- a/models/sparse.py
+++ b/models/sparse.py
@@ -15,7 +15,7 @@ class PseudoSparseEmbedding(nn.Module):
         if dropout_p > 0.0:
             self.dropout = nn.Dropout(p=dropout_p)
         else:
-            self.dropout = lambda x: x
+            self.dropout = nn.Identity()
 
         self.register_buffer('mapping', torch.zeros(0, device=device, dtype=torch.long))