refine

tools/program.py

@@ -210,7 +210,10 @@ def train(config,
             images = batch[0]
             if use_srn:
                 model_average = True
+            if use_srn or model_type == 'table':
                 preds = model(images, data=batch[1:])
+            else:
+                preds = model(images)
             loss = loss_class(preds, batch)
             avg_loss = loss['loss']
             avg_loss.backward()
@@ -356,7 +359,10 @@ def eval(model,
                 break
             images = batch[0]
             start = time.time()
+            if use_srn or model_type == 'table':
                 preds = model(images, data=batch[1:])
+            else:
+                preds = model(images)
             batch = [item.numpy() for item in batch]
             # Obtain usable results from post-processing methods
             total_time += time.time() - start