bump to newer package of clip-anytorch that allows for text encodings < maximum context length

dalle2_pytorch/dalle2_pytorch.py

@@ -1124,7 +1124,7 @@ class DiffusionPriorNetwork(nn.Module):
         learned_queries = repeat(self.learned_query, 'd -> b 1 d', b = batch)
 
         if self.self_cond:
-            learned_queries = torch.cat((image_embed, self_cond), dim = -2)
+            learned_queries = torch.cat((self_cond, learned_queries), dim = -2)
 
         tokens = torch.cat((
             text_encodings,

dalle2_pytorch/version.py

@@ -1 +1 @@
-__version__ = '1.12.0'
+__version__ = '1.12.2'

setup.py

@@ -27,7 +27,7 @@ setup(
     'accelerate',
     'click',
     'open-clip-torch>=2.0.0,<3.0.0',
-    'clip-anytorch>=2.4.0',
+    'clip-anytorch>=2.5.2',
     'coca-pytorch>=0.0.5',
     'ema-pytorch>=0.0.7',
     'einops>=0.4',