diff --git a/python/paddle/fluid/tests/book/high-level-api/machine_translation/test_machine_translation.py b/python/paddle/fluid/tests/book/high-level-api/machine_translation/test_machine_translation.py
index 1f85221a9d0ad805705045ce3245ae7f1b37d6f5..d4b723d3e6b619709ab3dc76a32ae87f1cdec274 100644
--- a/python/paddle/fluid/tests/book/high-level-api/machine_translation/test_machine_translation.py
+++ b/python/paddle/fluid/tests/book/high-level-api/machine_translation/test_machine_translation.py
@@ -53,7 +53,7 @@ def encoder(is_sparse):
     return encoder_out
 
 
-def decoder_train(context, is_sparse):
+def train_decoder(context, is_sparse):
     # decoder
     trg_language_word = pd.data(
         name="target_language_word", shape=[1], dtype='int64', lod_level=1)
@@ -81,7 +81,7 @@ def decoder_train(context, is_sparse):
     return rnn()
 
 
-def decoder_decode(context, is_sparse):
+def decode(context, is_sparse):
     init_state = context
     array_len = pd.fill_constant(shape=[1], dtype='int64', value=max_length)
     counter = pd.zeros(shape=[1], dtype='int64', force_cpu=True)
@@ -150,7 +150,7 @@ def decoder_decode(context, is_sparse):
 
 def train_program(is_sparse):
     context = encoder(is_sparse)
-    rnn_out = decoder_train(context, is_sparse)
+    rnn_out = train_decoder(context, is_sparse)
     label = pd.data(
         name="target_language_next_word", shape=[1], dtype='int64', lod_level=1)
     cost = pd.cross_entropy(input=rnn_out, label=label)
@@ -201,7 +201,7 @@ def decode_main(use_cuda, is_sparse):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
 
     context = encoder(is_sparse)
-    translation_ids, translation_scores = decoder_decode(context, is_sparse)
+    translation_ids, translation_scores = decode(context, is_sparse)
 
     exe = Executor(place)
     exe.run(framework.default_startup_program())