diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py
index fdf4136aa512b09ab9a1a6d9cf387229d7984804..2bd274fad2ab7eed0902ffe944c6e0670f963233 100644
--- a/python/paddle/trainer_config_helpers/layers.py
+++ b/python/paddle/trainer_config_helpers/layers.py
@@ -137,7 +137,7 @@ __all__ = [
     'clip_layer',
     'slice_projection',
     'seq_slice_layer',
-    'kmax_sequence_score_layer',
+    'kmax_seq_score_layer',
     'img_pool3d_layer',
     'scale_shift_layer',
     'img_conv3d_layer',
@@ -5994,7 +5994,7 @@ def cross_entropy_over_beam(input, name=None):
     Note that, if gold falls off the beam at search step t, then the cost is
     calculated over the beam at step t.
 
-    This cost layer always works together with kmax_sequence_score_layer,
+    This cost layer always works together with kmax_seq_score_layer,
     sub_nested_seq_layer, and sequence_slice_layer to trim the input to form a
     sub-search space.
 
@@ -6597,14 +6597,14 @@ def seq_slice_layer(input, starts, ends, name=None):
 
 @wrap_name_default()
 @layer_support()
-def kmax_sequence_score_layer(input, name=None, beam_size=1):
+def kmax_seq_score_layer(input, name=None, beam_size=1):
     """
     This layer accepts one input which are scores over a sequence or a nested
     sequence, and returns indices of beam_size sequences with highest scores.
 
     .. code-block:: python
 
-        kmax_indices = kmax_sequence_score_layer(input=input_layer, beam_size)
+        kmax_indices = kmax_seq_score_layer(input=input_layer, beam_size)
 
 
     :param name: The Layer Name.
@@ -6617,10 +6617,10 @@ def kmax_sequence_score_layer(input, name=None, beam_size=1):
     :return: LayerOutput object.
     :rtype: LayerOutput
     """
-    assert isinstance(input, LayerOutput), ("kmax_sequence_score_layer "
+    assert isinstance(input, LayerOutput), ("kmax_seq_score_layer "
                                             "accepts only one input.")
     assert input.size == 1, (
-        "input of kmax_sequence_score_layer is a score"
+        "input of kmax_seq_score_layer is a score "
         "over a sequence or a nested sequence, so its width must be 1.")
 
     Layer(
diff --git a/python/paddle/trainer_config_helpers/tests/configs/file_list.sh b/python/paddle/trainer_config_helpers/tests/configs/file_list.sh
index 7b132c23d68d66bc2430839533f04f1b80b50977..df872a90ff388f0d96cef44763dbd076bc768ab9 100755
--- a/python/paddle/trainer_config_helpers/tests/configs/file_list.sh
+++ b/python/paddle/trainer_config_helpers/tests/configs/file_list.sh
@@ -8,7 +8,7 @@ test_spp_layer test_bilinear_interp test_maxout test_bi_grumemory math_ops
 test_seq_concat_reshape test_pad test_smooth_l1 test_multiplex_layer
 test_prelu_layer test_row_conv test_detection_output_layer test_multibox_loss_layer
 test_recursive_topology test_gated_unit_layer test_clip_layer test_row_l2_norm_layer
-test_kmax_seq_socre_layer test_seq_select_layers test_scale_shift_layer
+test_kmax_seq_socre_layer test_sub_nested_seq_select_layer test_scale_shift_layer
 test_seq_slice_layer test_cross_entropy_over_beam test_pooling3D_layer
 test_conv3d_layer test_deconv3d_layer)
 
diff --git a/python/paddle/trainer_config_helpers/tests/configs/protostr/test_cross_entropy_over_beam.protostr b/python/paddle/trainer_config_helpers/tests/configs/protostr/test_cross_entropy_over_beam.protostr
index c43fc48e222044b65d83b6162e7dc3954e119887..a602569697e91b11b8d421ac359c2e523a00fa98 100644
--- a/python/paddle/trainer_config_helpers/tests/configs/protostr/test_cross_entropy_over_beam.protostr
+++ b/python/paddle/trainer_config_helpers/tests/configs/protostr/test_cross_entropy_over_beam.protostr
@@ -12,7 +12,7 @@ layers {
   active_type: ""
 }
 layers {
-  name: "__kmax_sequence_score_layer_0__"
+  name: "__kmax_seq_score_layer_0__"
   type: "kmax_seq_score"
   active_type: ""
   inputs {
@@ -29,7 +29,7 @@ layers {
     input_layer_name: "sentence_states"
   }
   inputs {
-    input_layer_name: "__kmax_sequence_score_layer_0__"
+    input_layer_name: "__kmax_seq_score_layer_0__"
   }
 }
 layers {
@@ -44,7 +44,7 @@ layers {
   bias_parameter_name: "___fc_layer_0__.wbias"
 }
 layers {
-  name: "__kmax_sequence_score_layer_1__"
+  name: "__kmax_seq_score_layer_1__"
   type: "kmax_seq_score"
   active_type: ""
   inputs {
@@ -61,7 +61,7 @@ layers {
     input_layer_name: "__sub_nested_seq_layer_0__"
   }
   inputs {
-    input_layer_name: "__kmax_sequence_score_layer_1__"
+    input_layer_name: "__kmax_seq_score_layer_1__"
   }
   select_first: true
 }
@@ -77,7 +77,7 @@ layers {
   bias_parameter_name: "___fc_layer_1__.wbias"
 }
 layers {
-  name: "__kmax_sequence_score_layer_2__"
+  name: "__kmax_seq_score_layer_2__"
   type: "kmax_seq_score"
   active_type: ""
   inputs {
@@ -111,7 +111,7 @@ layers {
     input_layer_name: "sentence_scores"
   }
   inputs {
-    input_layer_name: "__kmax_sequence_score_layer_0__"
+    input_layer_name: "__kmax_seq_score_layer_0__"
   }
   inputs {
     input_layer_name: "sentences_ids"
@@ -120,7 +120,7 @@ layers {
     input_layer_name: "__fc_layer_0__"
   }
   inputs {
-    input_layer_name: "__kmax_sequence_score_layer_1__"
+    input_layer_name: "__kmax_seq_score_layer_1__"
   }
   inputs {
     input_layer_name: "start_ids"
@@ -129,7 +129,7 @@ layers {
     input_layer_name: "__fc_layer_1__"
   }
   inputs {
-    input_layer_name: "__kmax_sequence_score_layer_2__"
+    input_layer_name: "__kmax_seq_score_layer_2__"
   }
   inputs {
     input_layer_name: "end_ids"
@@ -185,13 +185,13 @@ sub_models {
   name: "root"
   layer_names: "sentence_states"
   layer_names: "sentence_scores"
-  layer_names: "__kmax_sequence_score_layer_0__"
+  layer_names: "__kmax_seq_score_layer_0__"
   layer_names: "__sub_nested_seq_layer_0__"
   layer_names: "__fc_layer_0__"
-  layer_names: "__kmax_sequence_score_layer_1__"
+  layer_names: "__kmax_seq_score_layer_1__"
   layer_names: "__seq_slice_layer_0__"
   layer_names: "__fc_layer_1__"
-  layer_names: "__kmax_sequence_score_layer_2__"
+  layer_names: "__kmax_seq_score_layer_2__"
   layer_names: "sentences_ids"
   layer_names: "start_ids"
   layer_names: "end_ids"
diff --git a/python/paddle/trainer_config_helpers/tests/configs/protostr/test_kmax_seq_socre_layer.protostr b/python/paddle/trainer_config_helpers/tests/configs/protostr/test_kmax_seq_socre_layer.protostr
index 3d32220bfbf5f4c67f88303cb9773ecfa484da4b..f93d368c8687573db80106b9cc4defa56a881e46 100644
--- a/python/paddle/trainer_config_helpers/tests/configs/protostr/test_kmax_seq_socre_layer.protostr
+++ b/python/paddle/trainer_config_helpers/tests/configs/protostr/test_kmax_seq_socre_layer.protostr
@@ -17,7 +17,7 @@ layers {
   bias_parameter_name: "___fc_layer_0__.wbias"
 }
 layers {
-  name: "__kmax_sequence_score_layer_0__"
+  name: "__kmax_seq_score_layer_0__"
   type: "kmax_seq_score"
   active_type: ""
   inputs {
@@ -46,14 +46,14 @@ parameters {
   initial_smart: false
 }
 input_layer_names: "input_seq"
-output_layer_names: "__kmax_sequence_score_layer_0__"
+output_layer_names: "__kmax_seq_score_layer_0__"
 sub_models {
   name: "root"
   layer_names: "input_seq"
   layer_names: "__fc_layer_0__"
-  layer_names: "__kmax_sequence_score_layer_0__"
+  layer_names: "__kmax_seq_score_layer_0__"
   input_layer_names: "input_seq"
-  output_layer_names: "__kmax_sequence_score_layer_0__"
+  output_layer_names: "__kmax_seq_score_layer_0__"
   is_recurrent_layer_group: false
 }
 
diff --git a/python/paddle/trainer_config_helpers/tests/configs/test_cross_entropy_over_beam.py b/python/paddle/trainer_config_helpers/tests/configs/test_cross_entropy_over_beam.py
index 240e703dc904e718c2c1ddaf2b6d7dccb4dabf41..4a5bdf1181dc4538418a8b89b41a1ff713e423c8 100644
--- a/python/paddle/trainer_config_helpers/tests/configs/test_cross_entropy_over_beam.py
+++ b/python/paddle/trainer_config_helpers/tests/configs/test_cross_entropy_over_beam.py
@@ -7,14 +7,14 @@ beam_size = 5
 # the first beam expansion.
 sentence_states = data_layer(name="sentence_states", size=32)
 sentence_scores = data_layer(name="sentence_scores", size=1)
-topk_sentence_ids = kmax_sequence_score_layer(
+topk_sentence_ids = kmax_seq_score_layer(
     input=sentence_scores, beam_size=beam_size)
 
 # the second beam expansion.
 topk_sen = sub_nested_seq_layer(
     input=sentence_states, selected_indices=topk_sentence_ids)
 start_pos_scores = fc_layer(input=topk_sen, size=1, act=LinearActivation())
-topk_start_pos_ids = kmax_sequence_score_layer(
+topk_start_pos_ids = kmax_seq_score_layer(
     input=sentence_scores, beam_size=beam_size)
 
 # the final beam expansion.
@@ -22,7 +22,7 @@ topk_start_spans = seq_slice_layer(
     input=topk_sen, starts=topk_start_pos_ids, ends=None)
 end_pos_scores = fc_layer(
     input=topk_start_spans, size=1, act=LinearActivation())
-topk_end_pos_ids = kmax_sequence_score_layer(
+topk_end_pos_ids = kmax_seq_score_layer(
     input=end_pos_scores, beam_size=beam_size)
 
 # define the cost
diff --git a/python/paddle/trainer_config_helpers/tests/configs/test_kmax_seq_socre_layer.py b/python/paddle/trainer_config_helpers/tests/configs/test_kmax_seq_socre_layer.py
index 48d0cd55da2481743de66ea95190c0856e7ddc39..171da10f75dae03eed7e110d0efd07d6a18e1ecf 100644
--- a/python/paddle/trainer_config_helpers/tests/configs/test_kmax_seq_socre_layer.py
+++ b/python/paddle/trainer_config_helpers/tests/configs/test_kmax_seq_socre_layer.py
@@ -4,6 +4,6 @@ from paddle.trainer_config_helpers import *
 
 data = data_layer(name="input_seq", size=128)
 scores = fc_layer(input=data, size=1, act=ExpActivation())
-kmax_seq_id = kmax_sequence_score_layer(input=scores, beam_size=5)
+kmax_seq_id = kmax_seq_score_layer(input=scores, beam_size=5)
 
 outputs(kmax_seq_id)
diff --git a/python/paddle/trainer_config_helpers/tests/configs/test_seq_select_layers.py b/python/paddle/trainer_config_helpers/tests/configs/test_sub_nested_seq_select_layer.py
similarity index 100%
rename from python/paddle/trainer_config_helpers/tests/configs/test_seq_select_layers.py
rename to python/paddle/trainer_config_helpers/tests/configs/test_sub_nested_seq_select_layer.py