1 files changed, 0 insertions, 44 deletions
diff --git a/tensorflow/contrib/rnn/python/kernel_tests/rnn_cell_test.py b/tensorflow/contrib/rnn/python/kernel_tests/rnn_cell_test.py
index b4a5f2d7eb..ebd4564f12 100644
--- a/tensorflow/contrib/rnn/python/kernel_tests/rnn_cell_test.py
+++ b/tensorflow/contrib/rnn/python/kernel_tests/rnn_cell_test.py
@@ -37,7 +37,6 @@ from tensorflow.python.ops import math_ops
 from tensorflow.python.ops import random_ops
 from tensorflow.python.ops import rnn
 from tensorflow.python.ops import rnn_cell
-from tensorflow.python.ops import rnn_cell_impl
 from tensorflow.python.ops import variable_scope
 from tensorflow.python.ops import variables
 from tensorflow.python.platform import test
@@ -1276,49 +1275,6 @@ class LayerNormBasicLSTMCellTest(test.TestCase):
         self.assertAllClose(res[2].c, expected_c1, 1e-5)
         self.assertAllClose(res[2].h, expected_h1, 1e-5)
 
-
-  def testBasicLSTMCellWithStateTupleLayerNorm(self):
-    """The results of LSTMCell and LayerNormBasicLSTMCell 
-    should be same. """
-    with self.test_session() as sess:
-      with variable_scope.variable_scope(
-          "root", initializer=init_ops.constant_initializer(0.5)):
-        x = array_ops.zeros([1, 2])
-        c0 = array_ops.zeros([1, 2])
-        h0 = array_ops.zeros([1, 2])
-        state0 = rnn_cell_impl.LSTMStateTuple(c0, h0)
-        c1 = array_ops.zeros([1, 2])
-        h1 = array_ops.zeros([1, 2])
-        state1 = rnn_cell_impl.LSTMStateTuple(c1, h1)
-        cell = rnn_cell_impl.MultiRNNCell(
-          [contrib_rnn_cell.LayerNormLSTMCell(
-              2,
-              layer_norm=True,
-              norm_gain=1.0,
-              norm_shift=0.0) for _ in range(2)])
-        h, (s0, s1) = cell(x, (state0, state1))
-        sess.run([variables.global_variables_initializer()])
-        res = sess.run([h, s0, s1], {
-          x.name: np.array([[1., 1.]]),
-          c0.name: 0.1 * np.asarray([[0, 1]]),
-          h0.name: 0.1 * np.asarray([[2, 3]]),
-          c1.name: 0.1 * np.asarray([[4, 5]]),
-          h1.name: 0.1 * np.asarray([[6, 7]]),
-        })
-
-        expected_h = np.array([[-0.38079708, 0.38079708]])
-        expected_h0 = np.array([[-0.38079708, 0.38079708]])
-        expected_c0 = np.array([[-1.0, 1.0]])
-        expected_h1 = np.array([[-0.38079708, 0.38079708]])
-        expected_c1 = np.array([[-1.0, 1.0]])
-
-        self.assertEqual(len(res), 3)
-        self.assertAllClose(res[0], expected_h, 1e-5)
-        self.assertAllClose(res[1].c, expected_c0, 1e-5)
-        self.assertAllClose(res[1].h, expected_h0, 1e-5)
-        self.assertAllClose(res[2].c, expected_c1, 1e-5)
-        self.assertAllClose(res[2].h, expected_h1, 1e-5)
-
   def testBasicLSTMCellWithDropout(self):
 
     def _is_close(x, y, digits=4):