no numpy

examples/run_classifier.py

@@ -456,7 +456,7 @@ def main():
             preds = np.argmax(preds, axis=1)
         elif output_mode == "regression":
             preds = np.squeeze(preds)
-        result = compute_metrics(task_name, preds, out_label_ids.numpy())
+        result = compute_metrics(task_name, preds, out_label_ids)
 
         if args.local_rank != -1:
             # Average over distributed nodes if needed
@@ -533,7 +533,7 @@ def main():
             eval_loss = eval_loss / nb_eval_steps
             preds = preds[0]
             preds = np.argmax(preds, axis=1)
-            result = compute_metrics(task_name, preds, out_label_ids.numpy())
+            result = compute_metrics(task_name, preds, out_label_ids)
 
             if args.local_rank != -1:
                 # Average over distributed nodes if needed