diff --git a/flax/struct.py b/flax/struct.py
index b677df145d..b4da6847a2 100644
--- a/flax/struct.py
+++ b/flax/struct.py
@@ -58,7 +58,7 @@ def dataclass(clz: _T) -> _T:
     from flax import struct
 
     @struct.dataclass
-    class Model():
+    class Model:
       params: Any
       # use pytree_node=False to indicate an attribute should not be touched
       # by Jax transformations.
@@ -77,6 +77,30 @@ def __apply__(self, *args):
     model = Model(params, apply_fn)
     model_grad = jax.grad(some_loss_fn)(model)
 
+  Note that dataclasses have an auto-generated ``__init__`` where
+  the arguments of the constructor and the attributed of the created
+  instance match 1:1. This correspondance is what makes these objects
+  valid containers that work with JAX transformations and
+  more generally the `jax.tree_util` library.
+
+  Sometimes a "smart constructor" is desired, for example because
+  some of the attributes can be (optionally) derived from others.
+  The way to do this with Flax dataclasses is to make a static or
+  class method that provides the smart constructor.
+  This way the simple constructor used by `jax.tree_util` is
+  preserved. Consider the following example::
+
+    @struct.dataclass
+    class DirectionAndScaleKernel:
+      direction: Array
+      scale: Array
+
+      @classmethod
+      def create(cls, kernel):
+        scale = jax.numpy.linalg.norm(kernel, axis=0, keepdims=True)
+        directin = direction / scale
+        return cls(direction, scale)
+
   Args:
     clz: the class that will be transformed by the decorator.
   Returns: