diff --git a/python/paddle/fluid/dygraph/nn.py b/python/paddle/fluid/dygraph/nn.py
index 8b9fea3fc934f8b2469c25c517692826ae10893c..8d6eae60be46ea1e06763f9a337e61f8b7edfe1f 100644
--- a/python/paddle/fluid/dygraph/nn.py
+++ b/python/paddle/fluid/dygraph/nn.py
@@ -2610,9 +2610,9 @@ class GroupNorm(layers.Layer):
 
     def forward(self, input):
         inputs = {'X': input}
-        if self.bias:
+        if self.bias is not None:
             inputs['Bias'] = self.bias
-        if self.weight:
+        if self.weight is not None:
             inputs['Scale'] = self.weight
 
         # create output
diff --git a/python/paddle/fluid/tests/unittests/test_layers.py b/python/paddle/fluid/tests/unittests/test_layers.py
index 666e7c86bb297c44fb8caeb646a0abcc6da2f3d4..7c0e020948e3e87ac339d86c2c3c767b5280a80f 100644
--- a/python/paddle/fluid/tests/unittests/test_layers.py
+++ b/python/paddle/fluid/tests/unittests/test_layers.py
@@ -1114,7 +1114,12 @@ class TestLayer(LayerTest):
                 dtype='float32',
                 lod_level=1,
                 append_batch_size=False)
-            ret = layers.group_norm(input=X, groups=2)
+            ret = layers.group_norm(
+                input=X,
+                groups=2,
+                param_attr=fluid.initializer.Uniform(
+                    low=-0.5, high=0.5),
+                bias_attr=fluid.initializer.ConstantInitializer(value=1))
             static_ret = self.get_static_graph_result(
                 feed={
                     'X': fluid.create_lod_tensor(
@@ -1130,7 +1135,12 @@ class TestLayer(LayerTest):
                 dtype='float32',
                 lod_level=1,
                 append_batch_size=False)
-            groupNorm = nn.GroupNorm(channels=shape[1], groups=2)
+            groupNorm = nn.GroupNorm(
+                channels=shape[1],
+                groups=2,
+                param_attr=fluid.initializer.Uniform(
+                    low=-0.5, high=0.5),
+                bias_attr=fluid.initializer.ConstantInitializer(value=1))
             ret = groupNorm(X)
             static_ret2 = self.get_static_graph_result(
                 feed={
@@ -1141,7 +1151,12 @@ class TestLayer(LayerTest):
                 with_lod=True)[0]
 
         with self.dynamic_graph():
-            groupNorm = nn.GroupNorm(channels=shape[1], groups=2)
+            groupNorm = nn.GroupNorm(
+                channels=shape[1],
+                groups=2,
+                param_attr=fluid.initializer.Uniform(
+                    low=-0.5, high=0.5),
+                bias_attr=fluid.initializer.ConstantInitializer(value=1))
             dy_ret = groupNorm(base.to_variable(input))
             dy_rlt_value = dy_ret.numpy()