use the eval decorator

dalle2_pytorch/dalle2_pytorch.py

@@ -1011,11 +1011,12 @@ class DALLE2(nn.Module):
         super().__init__()
         assert isinstance(prior, DiffusionPrior)
         assert isinstance(decoder, Decoder)
-        self.prior = prior.eval()
+        self.prior = prior
-        self.decoder = decoder.eval()     
+        self.decoder = decoder
         self.prior_num_samples = prior_num_samples
 
     @torch.no_grad()
+    @eval_decorator
     def forward(
         self,
         text,

setup.py

@@ -10,7 +10,7 @@ setup(
       'dream = dalle2_pytorch.cli:dream'
     ],
   },
-  version = '0.0.11',
+  version = '0.0.12',
   license='MIT',
   description = 'DALL-E 2',
   author = 'Phil Wang',