Improve errors raised when an object does not match the RNNCell interface.

PiperOrigin-RevId: 188651070

3 files changed, 8 insertions, 13 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 7de55a0bb3..69f7b8e107 100644
--- a/tensorflow/contrib/rnn/python/kernel_tests/rnn_cell_test.py
+++ b/tensorflow/contrib/rnn/python/kernel_tests/rnn_cell_test.py
@@ -455,8 +455,8 @@ class RNNCellTest(test.TestCase):
         self.assertAllClose(np.concatenate(res[1], axis=1), expected_state)
 
   def testAttentionCellWrapperFailures(self):
-    with self.assertRaisesRegexp(TypeError,
-                                 "The parameter cell is not RNNCell."):
+    with self.assertRaisesRegexp(
+        TypeError, rnn_cell_impl.ASSERT_LIKE_RNNCELL_ERROR_REGEXP):
       contrib_rnn_cell.AttentionCellWrapper(None, 0)
 
     num_units = 8
@@ -1203,7 +1203,7 @@ class LayerNormBasicLSTMCellTest(test.TestCase):
         h1 = array_ops.zeros([1, 2])
         state1 = rnn_cell.LSTMStateTuple(c1, h1)
         state = (state0, state1)
-        single_cell = lambda: contrib_rnn_cell.LayerNormBasicLSTMCell(2, layer_norm=False)
+        single_cell = lambda: contrib_rnn_cell.LayerNormBasicLSTMCell(2, layer_norm=False)  # pylint: disable=line-too-long
         cell = rnn_cell.MultiRNNCell([single_cell() for _ in range(2)])
         g, out_m = cell(x, state)
         sess.run([variables.global_variables_initializer()])
@@ -1235,7 +1235,7 @@ class LayerNormBasicLSTMCellTest(test.TestCase):
         self.assertAllClose(expected_state1_h, actual_state1_h, 1e-5)
 
       with variable_scope.variable_scope(
-          "other", initializer=init_ops.constant_initializer(0.5)) as vs:
+          "other", initializer=init_ops.constant_initializer(0.5)):
         x = array_ops.zeros(
             [1, 3])  # Test BasicLSTMCell with input_size != num_units.
         c = array_ops.zeros([1, 2])
diff --git a/tensorflow/contrib/rnn/python/ops/core_rnn_cell.py b/tensorflow/contrib/rnn/python/ops/core_rnn_cell.py
index 8109ebc718..645f82624b 100644
--- a/tensorflow/contrib/rnn/python/ops/core_rnn_cell.py
+++ b/tensorflow/contrib/rnn/python/ops/core_rnn_cell.py
@@ -40,7 +40,6 @@ from tensorflow.python.util import nest
 
 # pylint: disable=protected-access,invalid-name
 RNNCell = rnn_cell_impl.RNNCell
-_like_rnncell = rnn_cell_impl._like_rnncell
 _WEIGHTS_VARIABLE_NAME = rnn_cell_impl._WEIGHTS_VARIABLE_NAME
 _BIAS_VARIABLE_NAME = rnn_cell_impl._BIAS_VARIABLE_NAME
 # pylint: enable=protected-access,invalid-name
@@ -221,8 +220,7 @@ class EmbeddingWrapper(RNNCell):
       ValueError: if embedding_classes is not positive.
     """
     super(EmbeddingWrapper, self).__init__(_reuse=reuse)
-    if not _like_rnncell(cell):
-      raise TypeError("The parameter cell is not RNNCell.")
+    rnn_cell_impl.assert_like_rnncell("cell", cell)
     if embedding_classes <= 0 or embedding_size <= 0:
       raise ValueError("Both embedding_classes and embedding_size must be > 0: "
                        "%d, %d." % (embedding_classes, embedding_size))
@@ -301,8 +299,7 @@ class InputProjectionWrapper(RNNCell):
     super(InputProjectionWrapper, self).__init__(_reuse=reuse)
     if input_size is not None:
       logging.warn("%s: The input_size parameter is deprecated.", self)
-    if not _like_rnncell(cell):
-      raise TypeError("The parameter cell is not RNNCell.")
+    rnn_cell_impl.assert_like_rnncell("cell", cell)
     self._cell = cell
     self._num_proj = num_proj
     self._activation = activation
@@ -356,8 +353,7 @@ class OutputProjectionWrapper(RNNCell):
       ValueError: if output_size is not positive.
     """
     super(OutputProjectionWrapper, self).__init__(_reuse=reuse)
-    if not _like_rnncell(cell):
-      raise TypeError("The parameter cell is not RNNCell.")
+    rnn_cell_impl.assert_like_rnncell("cell", cell)
     if output_size < 1:
       raise ValueError("Parameter output_size must be > 0: %d." % output_size)
     self._cell = cell
diff --git a/tensorflow/contrib/rnn/python/ops/rnn_cell.py b/tensorflow/contrib/rnn/python/ops/rnn_cell.py
index 6bea8d4a21..3028edad1b 100644
--- a/tensorflow/contrib/rnn/python/ops/rnn_cell.py
+++ b/tensorflow/contrib/rnn/python/ops/rnn_cell.py
@@ -1143,8 +1143,7 @@ class AttentionCellWrapper(rnn_cell_impl.RNNCell):
           `state_is_tuple` is `False` or if attn_length is zero or less.
     """
     super(AttentionCellWrapper, self).__init__(_reuse=reuse)
-    if not rnn_cell_impl._like_rnncell(cell):  # pylint: disable=protected-access
-      raise TypeError("The parameter cell is not RNNCell.")
+    rnn_cell_impl.assert_like_rnncell("cell", cell)
     if nest.is_sequence(cell.state_size) and not state_is_tuple:
       raise ValueError(
           "Cell returns tuple of states, but the flag "