diff --git a/MindFlow/mindflow/core/optimizers.py b/MindFlow/mindflow/core/optimizers.py
index 58793c689f29adbf14a2acc664e4dc8d80982ff5..e98ccc12f52828aa11a531a8b05bae3cf1f76aad 100644
--- a/MindFlow/mindflow/core/optimizers.py
+++ b/MindFlow/mindflow/core/optimizers.py
@@ -19,19 +19,25 @@ from mindspore import nn, ops
 
 
 class AdaHessian(nn.Adam):
-    """Implements Adahessian algorithm.
-    It has been proposed in `ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning`.
-    See the (Torch implementation)[https://github.com/amirgholami/adahessian/blob/master/instruction/adahessian.py]
-    for reference.
+    r"""
+    The Adahessian optimizer.
+    It has been proposed in `ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning
+    <https://arxiv.org/abs/2006.00719>`_ .
+    See the `Torch implementation
+    <https://github.com/amirgholami/adahessian/blob/master/instruction/adahessian.py>`_  for reference.
     The Hessian power here is fixed to 1, and the way of spatially averaging the Hessian traces follows the default
     behavior in the Torch implementation, that is
-        - for 1D: no spatial average
-        - for 2D: use the entire row as the spatial average
-        - for 3D (assume 1D Conv, can be customized): use the last dimension as spatial average
-        - for 4D (assume 2D Conv, can be customized): use the last 2 dimensions as spatial average
-    Arguments:
-        params (iterable): iterable of parameters to optimize
-        others: other arguments same to Adam
+
+    - for 1D: no spatial average.
+    - for 2D: use the entire row as the spatial average.
+    - for 3D (assume 1D Conv, can be customized): use the last dimension as spatial average.
+    - for 4D (assume 2D Conv, can be customized): use the last 2 dimensions as spatial average.
+
+    Args see `mindspore.nn.Adam <https://www.mindspore.cn/docs/en/master/api_python/nn/mindspore.nn.Adam.html>`_ .
+
+    Supported Platforms:
+        ``Ascend``
+
     Examples:
         >>> import numpy as np
         >>> import mindspore as ms
@@ -48,6 +54,7 @@ class AdaHessian(nn.Adam):
         >>> print(optimizer.moment2[0].shape)
         (4, 2, 3, 3)
     """
+
     def gen_rand_vecs(self, grads):
         return [(2 * ops.randint(0, 2, p.shape) - 1).astype(ms.float32) for p in grads]
 
diff --git a/docs/api_python/mindflow/core/mindflow.core.AdaHessian.rst b/docs/api_python/mindflow/core/mindflow.core.AdaHessian.rst
new file mode 100644
index 0000000000000000000000000000000000000000..6b75f82c073431e5c8c3a856e702c8e0c5ba71cc
--- /dev/null
+++ b/docs/api_python/mindflow/core/mindflow.core.AdaHessian.rst
@@ -0,0 +1,16 @@
+mindflow.core.AdaHessian
+=========================
+
+.. py:class:: mindflow.core.AdaHessian(*args, **kwargs)
+
+    二阶优化器 AdaHessian，利用 Hessian 矩阵对角元信息进行二阶优化求解。
+    有关更多详细信息，请参考论文 `ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning <https://arxiv.org/abs/2006.00719>`_ 。
+    相关 Torch 版本实现可参考 `Torch 版代码 <https://github.com/amirgholami/adahessian/blob/master/instruction/adahessian.py>`_ 。
+    此处 Hessian power 固定为 1，且对 Hessian 对角元做空间平均的方法与 Torch 实现的默认行为一致，描述如下：
+
+    - 对于 1D 张量：不做空间平均；
+    - 对于 2D 张量：做行平均；
+    - 对于 3D 张量（假设为 1D 卷积）：对最后一个维度做平均；
+    - 对于 4D 张量（假设为 2D 卷积）：对最后两个维度做平均。
+
+    参数说明详见 `mindspore.nn.Adam <https://www.mindspore.cn/docs/zh-CN/master/api_python/nn/mindspore.nn.Adam.html>`_ 。
\ No newline at end of file
diff --git a/docs/api_python/mindflow/mindflow.core.rst b/docs/api_python/mindflow/mindflow.core.rst
index 3bf67302f0723330de842543640ced431f087d1c..0a50ae493e20874c8e5c10a48d786e159905f691 100644
--- a/docs/api_python/mindflow/mindflow.core.rst
+++ b/docs/api_python/mindflow/mindflow.core.rst
@@ -6,6 +6,7 @@ mindflow.core
     :nosignatures:
     :template: classtemplate.rst
 
+    mindflow.core.AdaHessian
     mindflow.core.get_multi_step_lr
     mindflow.core.get_poly_lr
     mindflow.core.get_warmup_cosine_annealing_lr
diff --git a/docs/api_python_en/mindflow/mindflow.core.rst b/docs/api_python_en/mindflow/mindflow.core.rst
index 3d4d207df1fce039a7c2edc60d685c852261b353..17ef48a00ca72e9d1f2df8b5be6b526f6b561a23 100644
--- a/docs/api_python_en/mindflow/mindflow.core.rst
+++ b/docs/api_python_en/mindflow/mindflow.core.rst
@@ -6,6 +6,7 @@ mindflow.core
     :nosignatures:
     :template: classtemplate.rst
 
+    mindflow.core.AdaHessian
     mindflow.core.get_multi_step_lr
     mindflow.core.get_poly_lr
     mindflow.core.get_warmup_cosine_annealing_lr