Update min_dalle/min_dalle.py

min_dalle/min_dalle.py

@@ -241,23 +241,22 @@ class MinDalle:
 
             #torch.cuda.empty_cache() 
             #torch.cpu.empty_cache()                
-            with torch.cpu.amp.autocast(dtype=self.dtype):
-                image_tokens[i + 1], attention_state = self.decoder.forward(
-                    settings=settings,
-                    attention_mask=attention_mask,
-                    encoder_state=encoder_state,
-                    attention_state=attention_state,
-                    prev_tokens=image_tokens[i],
-                    token_index=token_indices[[i]]
-                )
+        
+            image_tokens[i + 1], attention_state = self.decoder.forward(
+                settings=settings,
+                attention_mask=attention_mask,
+                encoder_state=encoder_state,
+                attention_state=attention_state,
+                prev_tokens=image_tokens[i],
+                token_index=token_indices[[i]]
+            )
 
-            with torch.cpu.amp.autocast(dtype=torch.float32):
-                if ((i + 1) % 32 == 0 and progressive_outputs) or i + 1 == 256:
-                    yield self.image_grid_from_tokens(
-                        image_tokens=image_tokens[1:].T,
-                        is_seamless=is_seamless,
-                        is_verbose=is_verbose
-                    )
+            if ((i + 1) % 32 == 0 and progressive_outputs) or i + 1 == 256:
+                yield self.image_grid_from_tokens(
+                    image_tokens=image_tokens[1:].T,
+                    is_seamless=is_seamless,
+                    is_verbose=is_verbose
+                )
 
     def generate_image_stream(self, *args, **kwargs) -> Iterator[Image.Image]:
         image_stream = self.generate_raw_image_stream(*args, **kwargs)