Merge pull request #3296 from luotao1/test_TrainerOnePass

reduce time of test_TrainerOnePass

paddle/trainer/tests/simple_sparse_neural_network.py

 from paddle.trainer_config_helpers import *
 
-settings(batch_size=128, learning_method=AdaGradOptimizer(), learning_rate=1e-4)
+settings(batch_size=17, learning_method=AdaGradOptimizer(), learning_rate=1e-4)
 
 file_list = 'trainer/tests/fake_file_list.list'
 
@@ -12,7 +12,7 @@ define_py_data_sources2(
 
 embedding = embedding_layer(
     input=data_layer(
-        name="word_ids", size=65536),
+        name="word_ids", size=8191),
     size=128,
     param_attr=ParamAttr(sparse_update=True))
 prediction = fc_layer(input=embedding, size=10, act=SoftmaxActivation())

paddle/trainer/tests/simple_sparse_neural_network_dp.py

@@ -7,15 +7,15 @@ def init_hook(settings, is_train, **kwargs):
 
 
 @provider(
-    input_types={'word_ids': integer_value(65536),
+    input_types={'word_ids': integer_value(8191),
                  'label': integer_value(10)},
     min_pool_size=0,
     init_hook=init_hook)
 def process(settings, filename):
     if settings.is_train:
-        data_size = 2**20
-    else:
         data_size = 2**10
+    else:
+        data_size = 2**5
 
     for _ in xrange(data_size):
-        yield random.randint(0, 65535), random.randint(0, 9)
+        yield random.randint(0, 8190), random.randint(0, 9)

paddle/trainer/tests/test_TrainerOnePass.cpp

@@ -100,25 +100,25 @@ TEST(average_window, gpu) {
 }
 
 TEST(average_window, gpu2) {
-  FLAGS_num_passes = 100;
+  FLAGS_num_passes = 20;
   trainerOnePassTest(configFile1, true, false, 2, 0.01);
   FLAGS_num_passes = 1;
 }
 
 TEST(average_window, gpu4) {
-  FLAGS_num_passes = 100;
+  FLAGS_num_passes = 20;
   trainerOnePassTest(configFile1, true, false, 4, 0.01);
   FLAGS_num_passes = 1;
 }
 
 TEST(average_window_cpu, gpu2) {
-  FLAGS_num_passes = 100;
+  FLAGS_num_passes = 20;
   trainerOnePassTest(configFile1, true, false, 2, 0.01, true);
   FLAGS_num_passes = 1;
 }
 
 TEST(average_window_cpu, gpu4) {
-  FLAGS_num_passes = 100;
+  FLAGS_num_passes = 20;
   trainerOnePassTest(configFile1, true, false, 4, 0.01, true);
   FLAGS_num_passes = 1;
 }