Fix minor issue that causes batch data in Iterator to be skipped

CONTRIBUTORS.md

@@ -106,3 +106,4 @@ List of Contributors
 * [Max Kuhn](https://github.com/topepo)
 * [Yuqi Li](https://github.com/ziyeqinghan)
 * [Depeng Liang](https://github.com/Ldpe2G)
+* [Kiko Qiu](https://github.com/kikoqiu)

python/mxnet/model.py

@@ -607,9 +607,6 @@ def predict(self, X, num_batch=None, return_data=False, reset=True):
 
         i = 0
         for batch in X:
-            if num_batch is not None and i == num_batch:
-                break
-            i += 1
 
             _load_data(batch, data_arrays)
             self._pred_exec.forward(is_train=False)
@@ -624,6 +621,9 @@ def predict(self, X, num_batch=None, return_data=False, reset=True):
                     data_list[j].append(x[0:real_size].asnumpy())
                 for j, x in enumerate(batch.label):
                     label_list[j].append(x[0:real_size].asnumpy())
+            i += 1
+            if num_batch is not None and i == num_batch:
+                break
 
         outputs = [np.concatenate(x) for x in output_list]
         if len(outputs) == 1: