fix vqgan-vae for latent diffusion

dalle2_pytorch/vqgan_vae.py

@@ -435,12 +435,12 @@ class VQGanVAE(nn.Module):
         return fmap
 
     def decode(self, fmap):
-        fmap = self.vq(fmap)
+        fmap, indices, commit_loss = self.vq(fmap)
 
         for dec in self.decoders:
             fmap = dec(fmap)
 
-        return fmap
+        return fmap, indices, commit_loss
 
     def forward(
         self,
@@ -453,9 +453,9 @@ class VQGanVAE(nn.Module):
         assert height == self.image_size and width == self.image_size, 'height and width of input image must be equal to {self.image_size}'
         assert channels == self.channels, 'number of channels on image or sketch is not equal to the channels set on this VQGanVAE'
 
-        fmap, indices, commit_loss = self.encode(img)
+        fmap = self.encode(img)
 
-        fmap = self.decode(fmap)
+        fmap, indices, commit_loss = self.decode(fmap)
 
         if not return_loss and not return_discr_loss:
             return fmap

setup.py

@@ -10,7 +10,7 @@ setup(
       'dream = dalle2_pytorch.cli:dream'
     ],
   },
-  version = '0.0.35',
+  version = '0.0.36',
   license='MIT',
   description = 'DALL-E 2',
   author = 'Phil Wang',