Make weight normalization adapt to the up-to-date code

python/paddle/v2/fluid/layer_helper.py

@@ -226,8 +226,8 @@ class LayerHelper(object):
             scale = elementwise_div(
                 x=g, y=norm)  # The shapes of g and norm are the same.
             # Currently, elementwise_mul only support broadcast when the shape
-            # of y is a subset of x. Thus, we should reshape y to squeeze to
-            # achive it.
+            # of y is a subset of the shape of x. Thus, we reshape y to squeeze
+            # to achive the subset.
             w = elementwise_mul(
                 x=v,
                 y=scale if dim is None else reshape(

python/paddle/v2/fluid/param_attr.py

@@ -15,7 +15,10 @@
 from initializer import Initializer, Xavier, Constant
 from regularizer import WeightDecayRegularizer
 
-__all__ = ['ParamAttr']
+__all__ = [
+    'ParamAttr',
+    'WeightNormParamAttr',
+]
 
 
 class ParamAttr(object):
@@ -92,7 +95,7 @@ class WeightNormParamAttr(ParamAttr):
     """
     # List to record the parameters reparameterized by weight normalization.
     # If these parameters are treated as Variable rather than Parameter,
-    # it can be used to discriminate these parameters and help to serialize 
+    # it can be used to discriminate these parameters and help to serialize
     # these paramters for inference.
     params_with_weight_norm = []
 

python/paddle/v2/fluid/tests/test_weight_normalization.py

@@ -52,7 +52,7 @@ class TestWeightNormalization(unittest.TestCase):
     def run_program(self):
         outputs = []
         places = [core.CPUPlace()]
-        if core.is_compile_gpu():
+        if core.is_compiled_with_cuda():
             places.append(core.CUDAPlace(0))
         for place in places:
             self.set_inputs(place)