diff --git a/doc/fluid/api/nn/functional.rst b/doc/fluid/api/nn/functional.rst
index 551924348e956066edf7affedb78a60e7adf2df4..598b76a479602a53a4d7073bc31c65ba3eddbe53 100644
--- a/doc/fluid/api/nn/functional.rst
+++ b/doc/fluid/api/nn/functional.rst
@@ -7,3 +7,4 @@ functional
 
     functional/l1_loss.rst
     functional/nll_loss.rst
+    functional/mse_loss.rst
diff --git a/doc/fluid/api/nn/functional/mse_loss.rst b/doc/fluid/api/nn/functional/mse_loss.rst
new file mode 100644
index 0000000000000000000000000000000000000000..b5ec8c58b5a10c206e85184f36e414396fc7d9b9
--- /dev/null
+++ b/doc/fluid/api/nn/functional/mse_loss.rst
@@ -0,0 +1,10 @@
+.. _api_nn_functional_mse_loss:
+
+mse_loss
+------
+
+..  autoclass:: paddle.nn.functional.mse_loss
+    :members:
+    :inherited-members:
+    :noindex:
+
diff --git a/doc/fluid/api_cn/nn_cn/functional_cn.rst b/doc/fluid/api_cn/nn_cn/functional_cn.rst
index b314bbe0ef25f09151745db0d91bdc8404eb540f..b492a51cccc1c67188fd6a733a260215a46be97f 100644
--- a/doc/fluid/api_cn/nn_cn/functional_cn.rst
+++ b/doc/fluid/api_cn/nn_cn/functional_cn.rst
@@ -11,3 +11,4 @@ functional
     functional_cn/l1_loss_cn.rst
     functional_cn/nll_loss_cn.rst
     functional_cn/margin_ranking_loss_cn.rst
+    functional_cn/mse_loss_cn.rst
diff --git a/doc/fluid/api_cn/nn_cn/functional_cn/mse_loss_cn.rst b/doc/fluid/api_cn/nn_cn/functional_cn/mse_loss_cn.rst
new file mode 100644
index 0000000000000000000000000000000000000000..99041e8ac0bf5c0f5558c096d6e152b8b62b9094
--- /dev/null
+++ b/doc/fluid/api_cn/nn_cn/functional_cn/mse_loss_cn.rst
@@ -0,0 +1,66 @@
+mse_loss
+-------------------------------
+
+.. py:function:: paddle.nn.functional.mse_loss(input, label, reduction='mean', name=None)
+
+该OP用于计算预测值和目标值的均方差误差。
+
+对于预测值input和目标值label，公式为：
+
+当 `reduction` 设置为 ``'none'`` 时，
+    
+    .. math::
+        Out = (input - label)^2
+
+当 `reduction` 设置为 ``'mean'`` 时，
+
+    .. math::
+       Out = \operatorname{mean}((input - label)^2)
+
+当 `reduction` 设置为 ``'sum'`` 时，
+    
+    .. math::
+       Out = \operatorname{sum}((input - label)^2)
+
+
+参数：
+:::::::::
+    - **input** (Tensor) - 预测值，维度为 :math:`[N_1, N_2, ..., N_k]` 的多维Tensor。数据类型为float32或float64。
+    - **label** (Tensor) - 目标值，维度为 :math:`[N_1, N_2, ..., N_k]` 的多维Tensor。数据类型为float32或float64。
+
+返回
+:::::::::
+``Tensor``, 输入 ``input`` 和标签 ``label`` 间的 `mse loss` 损失。
+
+**代码示例**：
+
+.. code-block:: python
+
+    import numpy as np
+    import paddle
+    # static graph mode
+    paddle.enable_static()
+    mse_loss = paddle.nn.loss.MSELoss()
+    input = paddle.data(name="input", shape=[1])
+    label = paddle.data(name="label", shape=[1])
+    place = paddle.CPUPlace()
+    input_data = np.array([1.5]).astype("float32")
+    label_data = np.array([1.7]).astype("float32")
+    output = mse_loss(input,label)
+    exe = paddle.static.Executor(place)
+    exe.run(paddle.static.default_startup_program())
+    output_data = exe.run(
+        paddle.static.default_main_program(),
+        feed={"input":input_data, "label":label_data},
+        fetch_list=[output],
+        return_numpy=True)
+    print(output_data)
+    # [array([0.04000002], dtype=float32)]
+    # dynamic graph mode
+    paddle.disable_static()
+    input = paddle.to_variable(input_data)
+    label = paddle.to_variable(label_data)
+    output = mse_loss(input, label)
+    print(output.numpy())
+    # [0.04000002]
+