diff --git a/imperative/python/megengine/module/batchnorm.py b/imperative/python/megengine/module/batchnorm.py
index a4479077..993ccfa7 100644
--- a/imperative/python/megengine/module/batchnorm.py
+++ b/imperative/python/megengine/module/batchnorm.py
@@ -280,6 +280,17 @@ class BatchNorm2d(_BatchNorm):
     statistics on `(N, H, W)` slices, it's common terminology to call this
     Spatial Batch Normalization.
 
+    .. note::
+
+        The update formula for ``running_mean`` and ``running_var`` (taking ``running_mean`` as an example) is
+
+        .. math::
+
+            \textrm{running_mean} = \textrm{momentum} \times \textrm{running_mean} + (1 - \textrm{momentum}) \times \textrm{batch_mean}
+
+        which could be defined differently in other frameworks. Most notably, ``momentum`` of 0.1 in PyTorch
+        is equivalent to ``mementum`` of 0.9 here.
+
     Args:
         num_features: usually :math:`C` from an input of shape
             :math:`(N, C, H, W)` or the highest ranked dimension of an input