diff --git a/python/paddle/fluid/imperative/nn.py b/python/paddle/fluid/imperative/nn.py
index 8754e5d4d0c8c829303f1fe9cd39ead36619ac3b..ef1d28e59e0815628967eef2459a8555b4af621c 100644
--- a/python/paddle/fluid/imperative/nn.py
+++ b/python/paddle/fluid/imperative/nn.py
@@ -248,3 +248,35 @@ class FC(layers.Layer):
             outputs={"Out": out},
             attrs={"use_mkldnn": False})
         return out
+
+
+class SimpleRNNCell(layers.Layer):
+    def __init__(self, step_input_size, hidden_size, output_size, param_attr):
+        self.input_size = step_input_size
+        self.hidden_size = hidden_size
+        self.output_size = output_size
+        from ..layer_helper import LayerHelper
+        self._helper = LayerHelper('SimpleRNNCell', param_attr=param_attr)
+
+    def _build_once(self, inputs):
+        i2h_param_shape = [self.step_input_size, self.hidden_size]
+        h2h_param_shape = [self.hidden_size, self.hidden_size]
+        h2o_param_shape = [self.output_size, self.hidden_size]
+        self._i2h_w = self._helper.create_parameter(
+            attr=self._helper.param_attr,
+            shape=i2h_param_shape,
+            dtype=self._dtype,
+            is_bias=False)
+        self._h2h_w = self._helper.create_parameter(
+            attr=self._helper.param_attr,
+            shape=h2h_param_shape,
+            dtype=self._dtype,
+            is_bias=False)
+        self._h2o_w = self._helper.create_parameter(
+            attr=self._helper.param_attr,
+            shape=h2o_param_shape,
+            dtype=self._dtype,
+            is_bias=False)
+
+    def forward(self, inputs):
+        return 1
diff --git a/python/paddle/fluid/tests/unittests/test_imperative.py b/python/paddle/fluid/tests/unittests/test_imperative.py
index 86baff3c589d7b8a14938886b3e2104b0beb1cc9..915b2921d7935e9fa8c608a0674654b5dd13bc5e 100644
--- a/python/paddle/fluid/tests/unittests/test_imperative.py
+++ b/python/paddle/fluid/tests/unittests/test_imperative.py
@@ -80,6 +80,19 @@ class MLP(fluid.imperative.Layer):
         return x
 
 
+class SimpleRNN(fluid.imperative.Layer):
+    def __init__(self, inputs):
+        super(SimpleRNN, self).__init__()
+        self.seq_len = input.shape[0]
+        self._fc1 = FC(3,
+                       fluid.ParamAttr(
+                           initializer=fluid.initializer.Constant(value=0.1)))
+
+    def forward(self, inputs):
+        for i in range(self.seq_len):
+            x = self._fc1(inputs[i])
+
+
 class TestImperative(unittest.TestCase):
     def test_layer(self):
         with fluid.imperative.guard():
@@ -210,6 +223,9 @@ class TestImperative(unittest.TestCase):
         self.assertTrue(np.allclose(dy_out, static_out))
         self.assertTrue(np.allclose(dy_grad, static_grad))
 
+    def test_rnn_ptb(self):
+        np_inp = np.arrary([])
+
 
 if __name__ == '__main__':
     unittest.main()