diff --git a/paddle/phi/api/yaml/legacy_backward.yaml b/paddle/phi/api/yaml/legacy_backward.yaml
index 50640d313ef33445a4c4db93cdcafd6bfa81a418..3ef309656735de646ffdda08ddc0d9489bc20ab4 100755
--- a/paddle/phi/api/yaml/legacy_backward.yaml
+++ b/paddle/phi/api/yaml/legacy_backward.yaml
@@ -194,6 +194,15 @@
   invoke : cast (out_grad, x.dtype())
   no_need_buffer : x
 
+- backward_op : channel_shuffle_grad
+  forward : channel_shuffle (Tensor x, int groups, str data_format="NCHW") -> Tensor(out)
+  args : (Tensor out_grad, int groups, str data_format="NCHW")
+  output : Tensor(x_grad)
+  infer_meta :
+    func : ChannelShuffleGradInferMeta
+  kernel :
+    func : channel_shuffle_grad
+
 - backward_op : concat_double_grad
   forward : concat_grad (Tensor[] x, Tensor grad_out, Scalar axis) -> Tensor[](grad_x)
   args : (Tensor[] grad_x_grad, Scalar axis = 0)
diff --git a/paddle/phi/api/yaml/legacy_ops.yaml b/paddle/phi/api/yaml/legacy_ops.yaml
index 3be9cdf371d317a1d671b2bb606d1f1b76f52cba..52db798aecc8f97026417d21ada3ca9345415ec6 100755
--- a/paddle/phi/api/yaml/legacy_ops.yaml
+++ b/paddle/phi/api/yaml/legacy_ops.yaml
@@ -338,6 +338,15 @@
     data_type : x
   backward : cast_grad
 
+- op : channel_shuffle
+  args : (Tensor x, int groups, str data_format="NCHW")
+  output : Tensor(out)
+  infer_meta :
+    func : ChannelShuffleInferMeta
+  kernel :
+    func : channel_shuffle
+  backward : channel_shuffle_grad
+
 - op : check_finite_and_unscale_
   args : (Tensor[] x, Tensor scale, Tensor input_found_infinite)
   output : Tensor[](out){x.size()}, Tensor(output_found_infinite)
diff --git a/python/paddle/fluid/tests/unittests/test_channel_shuffle.py b/python/paddle/fluid/tests/unittests/test_channel_shuffle.py
index bfad2bd94d3e6dc7363d0bf5b92a944e4ecd1226..99e52d18ca5709d01edf707dfc19809904a20eb0 100644
--- a/python/paddle/fluid/tests/unittests/test_channel_shuffle.py
+++ b/python/paddle/fluid/tests/unittests/test_channel_shuffle.py
@@ -47,6 +47,7 @@ class TestChannelShuffleOp(OpTest):
         self.op_type = "channel_shuffle"
         self.init_data_format()
         n, c, h, w = 2, 9, 4, 4
+        self.python_api = paddle.nn.functional.channel_shuffle
 
         if self.format == "NCHW":
             shape = [n, c, h, w]
@@ -66,10 +67,10 @@ class TestChannelShuffleOp(OpTest):
         self.format = "NCHW"
 
     def test_check_output(self):
-        self.check_output()
+        self.check_output(check_eager=True)
 
     def test_check_grad(self):
-        self.check_grad(['X'], 'Out')
+        self.check_grad(['X'], 'Out', check_eager=True)
 
 
 class TestChannelLast(TestChannelShuffleOp):
diff --git a/python/paddle/nn/functional/vision.py b/python/paddle/nn/functional/vision.py
index fc9e030c3ea9751173ec884467a796d1f538b978..4f164e991f3280af801d35ba881cfa564aa188ae 100644
--- a/python/paddle/nn/functional/vision.py
+++ b/python/paddle/nn/functional/vision.py
@@ -516,9 +516,7 @@ def channel_shuffle(x, groups, data_format="NCHW", name=None):
         )
 
     if in_dygraph_mode():
-        return _legacy_C_ops.channel_shuffle(
-            x, "groups", groups, "data_format", data_format
-        )
+        return _C_ops.channel_shuffle(x, groups, data_format)
 
     helper = LayerHelper("channel_shuffle", **locals())
     check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'channel_shuffle')