add unittest.

paddle/gserver/tests/CMakeLists.txt

@@ -66,6 +66,16 @@ add_unittest_without_exec(test_BatchNorm
 
 add_test(NAME test_BatchNorm
     COMMAND test_BatchNorm)
+
+
+################# test_KmaxSeqScore #######################
+add_unittest_without_exec(test_KmaxSeqScore
+    test_KmaxSeqScore.cpp
+    LayerGradUtil.cpp)
+
+add_test(NAME test_KmaxSeqScore
+    COMMAND test_KmaxSeqScore)
+
 ################## test_Evaluator #######################
 add_unittest(test_Evaluator
     test_Evaluator.cpp)

paddle/gserver/tests/test_KmaxSeqScore.cpp

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include <gtest/gtest.h>
+#include <string>
+#include <vector>
+#include "ModelConfig.pb.h"
+#include "paddle/gserver/layers/DataLayer.h"
+#include "paddle/trainer/Trainer.h"
+#include "paddle/utils/GlobalConstants.h"
+
+#include "LayerGradUtil.h"
+#include "paddle/testing/TestUtil.h"
+
+using namespace paddle;  // NOLINT
+using namespace std;     // NOLINT
+
+DECLARE_bool(use_gpu);
+DECLARE_int32(gpu_id);
+DECLARE_bool(thread_local_rand_use_global_seed);
+
+// Test that the batchNormLayer can be followed by a ConvLayer
+TEST(Layer, kmaxSeqScoreLayer) {
+  for (auto hasSubseq : {true, false}) {
+    for (auto useGpu : {true, false}) {
+      TestConfig config;
+      config.layerConfig.set_type("kmax_seq_score");
+      config.inputDefs.push_back(
+          {hasSubseq ? INPUT_HASSUB_SEQUENCE_DATA : INPUT_SEQUENCE_DATA,
+           "layer_0",
+           1,
+           0});
+      config.layerConfig.add_inputs();
+
+      // data layer initialize
+      std::vector<DataLayerPtr> dataLayers;
+      LayerMap layerMap;
+      vector<Argument> datas;
+      initDataLayer(config,
+                    &dataLayers,
+                    &datas,
+                    &layerMap,
+                    "kmax_seq_score",
+                    100,
+                    false,
+                    useGpu);
+      // test layer initialize
+      std::vector<ParameterPtr> parameters;
+      LayerPtr kmaxSeqScoreLayer;
+      initTestLayer(config, &layerMap, &parameters, &kmaxSeqScoreLayer);
+      kmaxSeqScoreLayer->forward(PASS_TRAIN);
+    }
+  }
+}
+
+int main(int argc, char** argv) {
+  testing::InitGoogleTest(&argc, argv);
+  initMain(argc, argv);
+  FLAGS_thread_local_rand_use_global_seed = true;
+  srand(1);
+  return RUN_ALL_TESTS();
+}

python/paddle/trainer_config_helpers/tests/configs/test_kmax_seq_socre_layer.py

+#!/usr/bin/env python
+#coding=utf-8
+from paddle.trainer_config_helpers import *
+
+data = data_layer(name='input', size=300)
+
+data = data_layer(name="data", size=128)
+scores = fc_layer(input=data, size=1, act=ExpActivation())
+kmax_seq_id = kmax_sequence_score_layer(input=scores, beam_size=5)
+
+outputs(kmax_seq_id)