diff --git a/python/paddle/fluid/dygraph/nn.py b/python/paddle/fluid/dygraph/nn.py
index b38e405ff62d91f29ba31978fbd9187e695cae51..5c28617b6e7fbcc7ccfdec1ea3df2bbe0066c122 100644
--- a/python/paddle/fluid/dygraph/nn.py
+++ b/python/paddle/fluid/dygraph/nn.py
@@ -1898,8 +1898,12 @@ class PRelu(layers.Layer):
           and element. all: all elements share same weight
           channel:elements in a channel share same weight
           element:each element has a weight
+        channel (int, optional): The number of channels.
+          This argument is required when mode is "channel".
+          Default: None.
         input_shape (list or tuple, optional): The shape of input.
-          This parameter is required when mode is not "all". Default: None.
+          This argument is required when mode is "element".
+          Default: None.
         param_attr(ParamAttr, optional): The parameter attribute for the learnable
           weight (alpha). Default: None.
         dtype (str, optional): Data type, it can be "float32" or "float64". Default: "float32".
@@ -1921,31 +1925,47 @@ class PRelu(layers.Layer):
           inp_np = np.ones([5, 200, 100, 100]).astype('float32')
           with fluid.dygraph.guard():
               inp_np = to_variable(inp_np)
-              mode = 'channel'
-              prelu = fluid.PRelu(
-                 mode=mode,
+              prelu0 = fluid.PRelu(
+                 mode='all',
+                 param_attr=fluid.ParamAttr(initializer=fluid.initializer.Constant(1.0)))
+              dy_rlt0 = prelu0(inp_np)
+              prelu1 = fluid.PRelu(
+                 mode='channel',
+                 channel=200,
+                 param_attr=fluid.ParamAttr(initializer=fluid.initializer.Constant(1.0)))
+              dy_rlt1 = prelu1(inp_np)
+              prelu2 = fluid.PRelu(
+                 mode='element',
                  input_shape=inp_np.shape,
                  param_attr=fluid.ParamAttr(initializer=fluid.initializer.Constant(1.0)))
-              dy_rlt = prelu(inp_np)
+              dy_rlt2 = prelu2(inp_np)
 
     """
 
-    def __init__(self, mode, input_shape=None, param_attr=None,
+    def __init__(self,
+                 mode,
+                 channel=None,
+                 input_shape=None,
+                 param_attr=None,
                  dtype='float32'):
         super(PRelu, self).__init__()
         self._mode = mode
         self._param_attr = param_attr
-        if self._mode not in ['all', 'channel', 'element']:
-            raise ValueError('mode should be one of all, channel, element.')
         self._dtype = dtype
-        self._alpha_shape = [1]
-        if mode is not 'all':
-            assert input_shape is not None
-            input_shape = list(input_shape)
-            if self._mode == 'channel':
-                self._alpha_shape = [1, input_shape[1], 1, 1]
-            elif self._mode == 'element':
-                self._alpha_shape = input_shape
+        if mode == 'all':
+            self._alpha_shape = [1]
+        elif mode == 'channel':
+            assert isinstance(
+                channel,
+                int), "channel argument is required when mode is 'channel'."
+            self._alpha_shape = [1, channel, 1, 1]
+        elif mode == 'element':
+            assert isinstance(input_shape, (
+                list, tuple
+            )), "input_shape argument is required when mode is 'element'."
+            self._alpha_shape = [1] + list(input_shape)[1:]
+        else:
+            raise ValueError('mode should be one of all, channel, element.')
         self.weight = self.create_parameter(
             attr=self._param_attr,
             shape=self._alpha_shape,
diff --git a/python/paddle/fluid/tests/unittests/test_imperative_load_static_param.py b/python/paddle/fluid/tests/unittests/test_imperative_load_static_param.py
index d25e3a76cb7f31cbf97db8e82d3b43be3e9c4c46..30bf44d88b7f656664f2bd17062572971eeeeed8 100644
--- a/python/paddle/fluid/tests/unittests/test_imperative_load_static_param.py
+++ b/python/paddle/fluid/tests/unittests/test_imperative_load_static_param.py
@@ -179,8 +179,8 @@ class TestDygraphLoadStatic(unittest.TestCase):
                     self.nce1 = NCE(10000, 100)
                     self.nce2 = NCE(10000, 100)
 
-                    self.prelu1 = PRelu("channel", [-1, 5, 10, 10])
-                    self.prelu2 = PRelu("channel", [-1, 5, 10, 10])
+                    self.prelu1 = PRelu("channel", channel=5)
+                    self.prelu2 = PRelu("channel", channel=5)
 
                     self.group_norm1 = GroupNorm(8, 4)
                     self.gourp_norm2 = GroupNorm(8, 4)
diff --git a/python/paddle/fluid/tests/unittests/test_layers.py b/python/paddle/fluid/tests/unittests/test_layers.py
index fa345be1ff06359fa9016d4660d9689235c4d7ca..cde4264ff14c2a65d8316285bfafbe569f52c8e8 100644
--- a/python/paddle/fluid/tests/unittests/test_layers.py
+++ b/python/paddle/fluid/tests/unittests/test_layers.py
@@ -676,6 +676,7 @@ class TestLayer(LayerTest):
                 append_batch_size=False)
             prelu = nn.PRelu(
                 mode=mode,
+                channel=inp_np.shape[1],
                 input_shape=data_t.shape,
                 param_attr=ParamAttr(initializer=Constant(1.0)))
             out = prelu(data_t)
@@ -685,6 +686,7 @@ class TestLayer(LayerTest):
         with self.dynamic_graph():
             prelu = nn.PRelu(
                 mode=mode,
+                channel=inp_np.shape[1],
                 input_shape=inp_np.shape,
                 param_attr=ParamAttr(initializer=Constant(1.0)))
             dy_rlt = prelu(base.to_variable(inp_np))
@@ -698,10 +700,12 @@ class TestLayer(LayerTest):
             inp = base.to_variable(inp_np)
             prelu1 = nn.PRelu(
                 mode=mode,
+                channel=inp_np.shape[1],
                 input_shape=inp_np.shape,
                 param_attr=ParamAttr(initializer=Constant(2.0)))
             prelu2 = nn.PRelu(
                 mode=mode,
+                channel=inp_np.shape[1],
                 input_shape=inp_np.shape,
                 param_attr=ParamAttr(initializer=Constant(1.0)))
             dy_rlt1 = prelu1(inp)