Update autoregressive/models/generate.py

autoregressive/models/generate.py

@@ -140,10 +140,12 @@ def generate(model, cond, max_new_tokens, emb_masks=None, cfg_scale=1.0, cfg_int
     condition = condition.to(torch.float32)
     print(condition)
     if condition is not None:
-        print(model.adapter.model.embeddings.patch_embeddings.projection.weight)
-        condition = model.adapter(condition)
-        condition = model.adapter_mlp(condition)
-    print(condition)
+        with torch.no_grad():
+            print(model.adapter.model.embeddings.patch_embeddings.projection.weight)
+            condition = model.adapter(condition)
+            print(condition)
+            condition = model.adapter_mlp(condition)
+            print(condition)
     if model.model_type == 'c2i':
         if cfg_scale > 1.0:
             cond_null = torch.ones_like(cond) * model.num_classes