diff --git a/python/paddle/tensor/manipulation.py b/python/paddle/tensor/manipulation.py
index db1222fa421ef61e6f68f0d69ad0fe7f5d80f6d5..9de407841fb461713d00f997afdf33a38a531245 100644
--- a/python/paddle/tensor/manipulation.py
+++ b/python/paddle/tensor/manipulation.py
@@ -21,6 +21,7 @@ from ..fluid.data_feeder import convert_dtype, check_variable_and_dtype, check_t
 from ..fluid.layers.tensor import fill_constant
 from ..fluid.layers import utils
 import numpy as np
+import six
 # TODO: define functions to manipulate a tensor  
 from ..fluid.layers import cast  #DEFINE_ALIAS
 from ..fluid.layers import slice  #DEFINE_ALIAS
@@ -1056,10 +1057,25 @@ def tile(x, repeat_times, name=None):
     """
     if in_dygraph_mode():
         return core.ops.tile(x, 'repeat_times', repeat_times)
+    check_type(repeat_times, 'repeat_times', (list, tuple, Variable), 'tile')
+    if isinstance(repeat_times, Variable):
+        assert len(repeat_times.shape) == 1, (
+            'repeat_times must be an 1-D Tensor.')
+    else:
+        for elem in repeat_times:
+            if isinstance(elem, Variable):
+                assert len(elem.shape) == 1, (
+                    'Elements in repeat_times must be 1-D Tensors or integers.')
+            else:
+                if six.PY3:
+                    type_tuple = (int, np.int32, np.int64)
+                elif six.PY2:
+                    type_tuple = (int, long, np.int32, np.int64)
+                assert isinstance(elem, type_tuple), (
+                    'Elements in repeat_times must be 1-D Tensors or integers.')
 
     check_variable_and_dtype(
         x, 'x', ['bool', 'float32', 'float64', 'int32', 'int64'], 'tile')
-    check_type(repeat_times, 'repeat_times', (list, tuple, Variable), 'tile')
     if convert_dtype(x.dtype) == 'bool' and x.stop_gradient == False:
         raise ValueError(
             "When the date type is bool for the input 'x' of tile op, you "
@@ -1181,18 +1197,33 @@ def expand(x, shape, name=None):
     if in_dygraph_mode():
         return core.ops.expand_v2(x, 'shape', shape)
 
+    if isinstance(shape, Variable):
+        assert len(shape.shape) == 1, ('shape must be an 1-D Tensor.')
+    else:
+        for elem in shape:
+            if isinstance(elem, Variable):
+                assert len(elem.shape) == 1, (
+                    'Elements in shape must be 1-D Tensors or integers.')
+            else:
+                if six.PY3:
+                    type_tuple = (int, np.int32, np.int64)
+                elif six.PY2:
+                    type_tuple = (int, long, np.int32, np.int64)
+                assert isinstance(elem, type_tuple), (
+                    'Elements in shape must be 1-D Tensors or integers.')
+
     check_variable_and_dtype(
         x, 'x', ['bool', 'float32', 'float64', 'int32', 'int64'], 'expand')
     check_type(shape, 'shape', (list, tuple, Variable), 'expand')
-
-    inputs = {"X": [x]}
-    attrs = {}
     if convert_dtype(x.dtype) == 'bool' and x.stop_gradient == False:
         raise ValueError("When the data type of input 'x' for expand is bool, "
                          "you must set its stop_gradient to be False by "
                          "some_var.stop_gradient = True, supporting "
                          "some_var as the input.")
 
+    inputs = {"X": [x]}
+    attrs = {}
+
     helper = LayerHelper('expand', **locals())
 
     def get_attr_expand_shape(list_expand_shape):