diff --git a/python/paddle/fluid/tests/unittests/test_lrn_op.py b/python/paddle/fluid/tests/unittests/test_lrn_op.py
index 36aab4fb5adf24842f8dc633210249b8c2fa5417..25d90c07838df53c361b403e3bd128c86e6f302e 100644
--- a/python/paddle/fluid/tests/unittests/test_lrn_op.py
+++ b/python/paddle/fluid/tests/unittests/test_lrn_op.py
@@ -328,6 +328,32 @@ class TestLocalResponseNormCAPI(unittest.TestCase):
                 res2_tran = np.transpose(res2.numpy(), (0, 3, 1, 2))
                 np.testing.assert_allclose(res1.numpy(), res2_tran, rtol=1e-05)
 
+    def test_static_fp16_gpu(self):
+        if paddle.fluid.core.is_compiled_with_cuda():
+            place = paddle.CUDAPlace(0)
+            with paddle.static.program_guard(
+                paddle.static.Program(), paddle.static.Program()
+            ):
+                input = np.random.random([3, 3, 112, 112]).astype("float16")
+
+                x = paddle.static.data(
+                    name="x", shape=[3, 3, 112, 112], dtype="float16"
+                )
+
+                m = paddle.nn.LocalResponseNorm(size=5)
+                y = m(x)
+
+                exe = paddle.static.Executor(place)
+                res = exe.run(
+                    paddle.static.default_main_program(),
+                    feed={
+                        "x": input,
+                    },
+                    fetch_list=[y],
+                )
+
+                assert np.array_equal(res[0].shape, input.shape)
+
 
 if __name__ == "__main__":
     unittest.main()
diff --git a/python/paddle/nn/functional/norm.py b/python/paddle/nn/functional/norm.py
index 0c194d45ed8d3e0d9b8e585963231ff61cc11444..6a2404f588c86bfee3d12f6b9a430762aea1385b 100644
--- a/python/paddle/nn/functional/norm.py
+++ b/python/paddle/nn/functional/norm.py
@@ -478,7 +478,7 @@ def local_response_norm(
 
 
     Args:
-        x (Tensor): The input 3-D/4-D/5-D tensor. The data type is float32.
+        x (Tensor): The input 3-D/4-D/5-D tensor. The data type is float16 or float32.
         size (int): The number of channels to sum over.
         alpha (float, optional): The scaling parameter, positive. Default:1e-4
         beta (float, optional): The exponent, positive. Default:0.75
@@ -509,7 +509,9 @@ def local_response_norm(
         print(y.shape)  # [3, 3, 112, 112]
     """
     if not in_dynamic_mode():
-        check_variable_and_dtype(x, 'x', ['float32'], 'local_response_norm')
+        check_variable_and_dtype(
+            x, 'x', ['float16', 'float32'], 'local_response_norm'
+        )
     if data_format not in ['NCL', 'NLC', 'NCHW', 'NHWC', 'NCDHW', 'NDHWC']:
         raise ValueError(
             "data_format should be in one of [NCL, NCHW, NCDHW, NLC, NHWC, NDHWC], "
diff --git a/python/paddle/nn/layer/pooling.py b/python/paddle/nn/layer/pooling.py
index 09714e18b494eb5b8876691a8d4b895705204902..451d532b26d320ae5eb9721df6fec13a0a9a94fe 100755
--- a/python/paddle/nn/layer/pooling.py
+++ b/python/paddle/nn/layer/pooling.py
@@ -261,7 +261,7 @@ class AvgPool3D(Layer):
 
     Shape:
         - x(Tensor): The input tensor of avg pool3d operator, which is a 5-D tensor.
-          The data type can be float32, float64.
+          The data type can be float16, float32, float64.
         - output(Tensor): The output tensor of avg pool3d  operator, which is a 5-D tensor.
           The data type is same as input x.