Merge commit for internal changes

1 files changed, 6 insertions, 6 deletions

diff --git a/tensorflow/contrib/seq2seq/python/kernel_tests/attention_wrapper_test.py b/tensorflow/contrib/seq2seq/python/kernel_tests/attention_wrapper_test.py
index 6781433a1f..cd162bae25 100644
--- a/tensorflow/contrib/seq2seq/python/kernel_tests/attention_wrapper_test.py
+++ b/tensorflow/contrib/seq2seq/python/kernel_tests/attention_wrapper_test.py
@@ -411,11 +411,11 @@ class AttentionWrapperTest(test.TestCase):
 
   def testLuongScaledDType(self):
     # Test case for GitHub issue 18099
-    for dtype in [np.float16, np.float32, np.float64]:
+    for dt in [np.float16, np.float32, np.float64]:
       num_units = 128
-      encoder_outputs = array_ops.placeholder(dtype, shape=[64, None, 256])
+      encoder_outputs = array_ops.placeholder(dt, shape=[64, None, 256])
       encoder_sequence_length = array_ops.placeholder(dtypes.int32, shape=[64])
-      decoder_inputs = array_ops.placeholder(dtype, shape=[64, None, 128])
+      decoder_inputs = array_ops.placeholder(dt, shape=[64, None, 128])
       decoder_sequence_length = array_ops.placeholder(dtypes.int32, shape=[64])
       batch_size = 64
       attention_mechanism = wrapper.LuongAttention(
@@ -423,7 +423,7 @@ class AttentionWrapperTest(test.TestCase):
           memory=encoder_outputs,
           memory_sequence_length=encoder_sequence_length,
           scale=True,
-          dtype=dtype,
+          dtype=dt,
       )
       cell = rnn_cell.LSTMCell(num_units)
       cell = wrapper.AttentionWrapper(cell, attention_mechanism)
@@ -434,12 +434,12 @@ class AttentionWrapperTest(test.TestCase):
           cell=cell,
           helper=helper,
           initial_state=cell.zero_state(
-              dtype=dtype, batch_size=batch_size))
+              dtype=dt, batch_size=batch_size))
 
       final_outputs, final_state, _ = decoder.dynamic_decode(my_decoder)
       self.assertTrue(
           isinstance(final_outputs, basic_decoder.BasicDecoderOutput))
-      self.assertEqual(final_outputs.rnn_output.dtype, dtype)
+      self.assertEqual(final_outputs.rnn_output.dtype, dt)
       self.assertTrue(
           isinstance(final_state, wrapper.AttentionWrapperState))
       self.assertTrue(