diff --git a/python/paddle/fluid/dygraph/nn.py b/python/paddle/fluid/dygraph/nn.py
index bd03f27065b952538d8d107c367a87dc68230759..736c5fe3005f28002960245c550bc8ce93cf1ab8 100644
--- a/python/paddle/fluid/dygraph/nn.py
+++ b/python/paddle/fluid/dygraph/nn.py
@@ -939,6 +939,10 @@ class Linear(layers.Layer):
 
             return dygraph_utils._append_activation_in_dygraph(pre_act,
                                                                self._act)
+
+        check_variable_and_dtype(input, 'input',
+                                 ['float16', 'float32', 'float64'], "Linear")
+
         attrs = {
             "x_num_col_dims": len(input.shape) - 1,
             "y_num_col_dims": 1,
diff --git a/python/paddle/fluid/tests/unittests/test_layers.py b/python/paddle/fluid/tests/unittests/test_layers.py
index 543264be31ec457e343f7ddf86beb876de5746f9..f919ddd72efd0e50563db455ac73d8930dc2d167 100644
--- a/python/paddle/fluid/tests/unittests/test_layers.py
+++ b/python/paddle/fluid/tests/unittests/test_layers.py
@@ -155,6 +155,31 @@ class TestLayer(LayerTest):
 
         self.assertTrue(np.array_equal(static_ret, dy_ret_value))
 
+        with self.static_graph():
+
+            # the input of Linear must be Variable.
+            def test_Variable():
+                inp = np.ones([3, 32, 32], dtype='float32')
+                linear = nn.Linear(
+                    32,
+                    4,
+                    bias_attr=fluid.initializer.ConstantInitializer(value=1))
+                linear_ret1 = linear(inp)
+
+            self.assertRaises(TypeError, test_Variable)
+
+            # the input dtype of Linear must be float16 or float32 or float64
+            # float16 only can be set on GPU place
+            def test_type():
+                inp = np.ones([3, 32, 32], dtype='int32')
+                linear = nn.Linear(
+                    32,
+                    4,
+                    bias_attr=fluid.initializer.ConstantInitializer(value=1))
+                linear_ret2 = linear(inp)
+
+            self.assertRaises(TypeError, test_type)
+
     def test_layer_norm(self):
         inp = np.ones([3, 32, 32], dtype='float32')
         with self.static_graph():