Fix two issues.

examples/common/dataset/data_processing.py

@@ -105,13 +105,12 @@ def vgg_create_dataset100(data_home, image_size, batch_size, rank_id=0, rank_siz
     data_set = data_set.map(input_columns="label", operations=type_cast_op)
     data_set = data_set.map(input_columns="image", operations=c_trans)
 
-    # apply repeat operations
-    data_set = data_set.repeat(repeat_num)
-
     # apply shuffle operations
-    # data_set = data_set.shuffle(buffer_size=1000)
+    data_set = data_set.shuffle(buffer_size=1000)
 
     # apply batch operations
     data_set = data_set.batch(batch_size=batch_size, drop_remainder=True)
 
+    # apply repeat operations
+    data_set = data_set.repeat(repeat_num)
     return data_set

mindarmour/privacy/evaluation/inversion_attack.py

@@ -107,7 +107,7 @@ class ImageInversionAttack:
         for sub_loss_weight in loss_weights:
             check_value_positive('sub_loss_weight', sub_loss_weight)
         self._loss = InversionLoss(self._network, loss_weights)
-        self._input_shape = check_param_multi_types('input_shape', input_shape, [list, tuple])
+        self._input_shape = check_param_type('input_shape', input_shape, tuple)
         for shape_dim in input_shape:
             check_int_positive('shape_dim', shape_dim)
         self._input_bound = check_param_multi_types('input_bound', input_bound, [list, tuple])