diff --git a/mindspore/common/initializer.py b/mindspore/common/initializer.py
index f78147b1fb..90211c8e93 100644
--- a/mindspore/common/initializer.py
+++ b/mindspore/common/initializer.py
@@ -366,25 +366,27 @@ class Uniform(Initializer):
 @_register()
 class Normal(Initializer):
     """
-    Initialize a normal array, and obtain values N(0, sigma) from the uniform distribution
+    Initialize a normal array, and obtain values N(sigma, mean) from the normal distribution
     to fill the input tensor.
 
     Args:
         sigma (float): The sigma of the array. Default: 0.01.
+        mean (float): The mean of the array. Default: 0.0.
 
     Returns:
         Array, normal array.
     """
-    def __init__(self, sigma=0.01):
-        super(Normal, self).__init__(sigma=sigma)
+    def __init__(self, sigma=0.01, mean=0.0):
+        super(Normal, self).__init__(sigma=sigma, mean=mean)
         self.sigma = sigma
+        self.mean = mean
 
     def _initialize(self, arr):
         seed, seed2 = self.seed
         output_tensor = Tensor(np.zeros(arr.shape, dtype=np.float32))
         random_normal(0, self.sigma, arr.shape, seed, seed2, output_tensor)
         output_data = output_tensor.asnumpy()
-        output_data *= self.sigma
+        output_data = output_data * self.sigma + self.mean
         _assignment(arr, output_data)
 
 @_register()