diff --git a/fastNLP/core/optimizer.py b/fastNLP/core/optimizer.py
index b534a72a..4d76c24e 100644
--- a/fastNLP/core/optimizer.py
+++ b/fastNLP/core/optimizer.py
@@ -33,8 +33,9 @@ class Optimizer(object):
     
     def construct_from_pytorch(self, model_params):
         raise NotImplementedError
-    
-    def _get_require_grads_param(self, params):
+
+    @staticmethod
+    def _get_require_grads_param(params):
         """
         将params中不需要gradient的删除
         
@@ -43,6 +44,7 @@ class Optimizer(object):
         """
         return [param for param in params if param.requires_grad]
 
+
 class NullOptimizer(Optimizer):
     """
     当不希望Trainer更新optimizer时，传入本optimizer，但请确保通过callback的方式对参数进行了更新。
@@ -113,7 +115,8 @@ class Adam(Optimizer):
 
 class AdamW(TorchOptimizer):
     r"""
-    对AdamW的实现，该实现应该会在pytorch更高版本中出现，https://github.com/pytorch/pytorch/pull/21250。这里提前加入
+    对AdamW的实现，该实现在pytorch 1.2.0版本中已经出现，https://github.com/pytorch/pytorch/pull/21250。
+    这里加入以适配低版本的pytorch
     
     .. todo::
         翻译成中文
diff --git a/test/core/test_optimizer.py b/test/core/test_optimizer.py
index b9a1c271..2f2487c7 100644
--- a/test/core/test_optimizer.py
+++ b/test/core/test_optimizer.py
@@ -2,7 +2,7 @@ import unittest
 
 import torch
 
-from fastNLP import SGD, Adam
+from fastNLP import SGD, Adam, AdamW
 
 
 class TestOptim(unittest.TestCase):
@@ -52,3 +52,12 @@ class TestOptim(unittest.TestCase):
         self.assertEqual(optim.__dict__["settings"]["lr"], 0.001)
         res = optim.construct_from_pytorch(torch.nn.Linear(10, 3).parameters())
         self.assertTrue(isinstance(res, torch.optim.Adam))
+
+    def test_AdamW(self):
+        optim = AdamW(params=torch.nn.Linear(10, 3).parameters())
+        self.assertTrue('lr' in optim.defaults)
+        self.assertTrue('weight_decay' in optim.defaults)
+
+        optim = AdamW(params=torch.nn.Linear(10, 3).parameters(), lr=0.002, weight_decay=0.989)
+        self.assertEqual(optim.defaults['lr'], 0.002)
+        self.assertTrue(optim.defaults['weight_decay'], 0.989)