Update modeling_minicpmv.py

modeling_minicpmv.py

@@ -300,8 +300,10 @@ class MiniCPMV(MiniCPMVPreTrainedModel):
             for pl in range(tensor.shape[1]):
                 to_add.append(1)
             for pl in range(tensor.shape[1], max_x):
+                print("here")
                 tensor = torch.cat((tensor, vector_reshaped), dim=1)
                 to_add.append(0)
+            print(tensor.shape, "UPDATED_SHAPE")
             attention_mask.append(to_add)
         attention_mask = torch.tensor(attention_mask)
         
@@ -310,7 +312,7 @@ class MiniCPMV(MiniCPMVPreTrainedModel):
         # Step 3: Stack the padded tensors into a single batch
         for stuff in batch:
             print(stuff.shape, "SHAPE")
-        batch = torch.cat(padded_tensors, dim=0)
+        batch = torch.cat(batch, dim=0)
         print(batch.shape)
         print(batch)
         # output_ids = self._decode(input_embeds, tokenizer, **kwargs)