diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py
index 8a3a500b8f3a3651fa07825f872d01348a4dc161..c68ecba9718df9196b8f57106731fd22f50cb2e5 100755
--- a/python/paddle/fluid/layers/nn.py
+++ b/python/paddle/fluid/layers/nn.py
@@ -34,6 +34,7 @@ from .. import unique_name
 from functools import reduce
 from .. import core
 from ..dygraph import layers
+from ..data_feeder import convert_dtype
 
 __all__ = [
     'fc',
@@ -2249,6 +2250,15 @@ def softmax(input, use_cudnn=False, name=None, axis=-1):
 
     """
     helper = LayerHelper('softmax', **locals())
+    if not isinstance(input, Variable):
+        raise TypeError(
+            "The type of 'input' in softmax must be Variable, but received %s" %
+            (type(input)))
+    if convert_dtype(input.dtype) not in ['float32', 'float64']:
+        raise TypeError(
+            "The data type of 'input' in softmax must be float32 or float64, but received %s."
+            % (convert_dtype(input.dtype)))
+
     dtype = helper.input_dtype()
     softmax_out = helper.create_variable_for_type_inference(dtype)
     helper.append_op(
diff --git a/python/paddle/fluid/tests/unittests/test_softmax_op.py b/python/paddle/fluid/tests/unittests/test_softmax_op.py
index ea14648e2015da5ac715cb4c74f51b097cf5a3d0..f6770bdd1d4309f4467a75844ce1bf544ee67b9b 100644
--- a/python/paddle/fluid/tests/unittests/test_softmax_op.py
+++ b/python/paddle/fluid/tests/unittests/test_softmax_op.py
@@ -18,6 +18,8 @@ import unittest
 import numpy as np
 from op_test import OpTest
 import paddle.fluid.core as core
+import paddle.fluid as fluid
+from paddle.fluid import compiler, Program, program_guard
 
 
 def stable_softmax(x):
@@ -74,6 +76,18 @@ class TestSoftmaxOp(OpTest):
             self.check_grad(["X"], "Out", max_relative_error=0.01)
 
 
+class TestSoftmaxOpError(OpTest):
+    def test_errors(self):
+        with program_guard(Program(), Program()):
+            # The input type of softmax_op must be Variable.
+            x1 = fluid.create_lod_tensor(
+                np.array([[-1]]), [[1]], fluid.CPUPlace())
+            self.assertRaises(TypeError, fluid.layers.softmax, x1)
+            # The input dtype of softmax_op must be float32 or float64.
+            x2 = fluid.layers.data(name='x2', shape=[4], dtype="int32")
+            self.assertRaises(TypeError, fluid.layers.softmax, x2)
+
+
 class TestSoftmaxOp2(TestSoftmaxOp):
     def get_x_shape(self):
         return [2, 3, 4, 5]