add batchnorm layer in simple test and branch test

paddle/trainer/tests/sample_trainer_config_branch_net.conf

@@ -89,6 +89,36 @@ tmp = img_pool_layer(input=tmp,
             padding=1,
             pool_type=MaxPooling())
 
+tmp = img_conv_layer(input=tmp,
+            filter_size=3,
+            num_filters=32,
+            padding=1,
+            shared_biases=True,
+            act=LinearActivation(),
+            bias_attr=False)
+
+tmp = batch_norm_layer(input=tmp,
+            use_global_stats=False,
+            act=ReluActivation())
+
+c1 = img_conv_layer(input=tmp,
+            filter_size=1,
+            num_filters=32,
+            padding=0,
+            shared_biases=True,
+            act=ReluActivation())
+
+c2 = img_conv_layer(input=tmp,
+            filter_size=3,
+            num_filters=32,
+            padding=1,
+            shared_biases=True,
+            act=ReluActivation())
+
+tmp = addto_layer(input=[c1, c2],
+            act=ReluActivation(),
+            bias_attr=False)
+
 tmp = fc_layer(input=tmp, size=64,
             bias_attr=False,
             act=TanhActivation())

paddle/trainer/tests/sample_trainer_config_simple_net.conf

@@ -38,9 +38,14 @@ tmp = img_pool_layer(input=tmp,
             
 tmp = img_conv_layer(input=tmp,
             filter_size=3,
-            num_filters=64,
+            num_filters=32,
             padding=1,
             shared_biases=True,
+            act=LinearActivation(),
+            bias_attr=False)
+
+tmp = batch_norm_layer(input=tmp,
+            use_global_stats=False,
             act=ReluActivation())
 
 tmp = img_pool_layer(input=tmp,