diff --git a/torch/nn/modules/module.py b/torch/nn/modules/module.py
index 32dfb524298d..2ca5d1e72d3b 100644
--- a/torch/nn/modules/module.py
+++ b/torch/nn/modules/module.py
@@ -132,6 +132,34 @@ def _apply(self, fn):
         return self
 
     def apply(self, fn):
+        """Applies ``fn`` recursively to every submodule (as returned by ``.children()``)
+        as well as self. Typical use includes initializing the parameters of a model
+        (see also :ref:`torch-nn-init`).
+
+        Example:
+            >>> def init_weights(m):
+            >>>     print(m)
+            >>>     if type(m) == nn.Linear:
+            >>>         m.weight.data.fill_(1.0)
+            >>>         print(m.weight)
+            >>>
+            >>> net = nn.Sequential(nn.Linear(2, 2), nn.Linear(2, 2))
+            >>> net.apply(init_weights)
+            Linear (2 -> 2)
+            Parameter containing:
+             1  1
+             1  1
+            [torch.FloatTensor of size 2x2]
+            Linear (2 -> 2)
+            Parameter containing:
+             1  1
+             1  1
+            [torch.FloatTensor of size 2x2]
+            Sequential (
+              (0): Linear (2 -> 2)
+              (1): Linear (2 -> 2)
+            )
+        """
         for module in self.children():
             module.apply(fn)
         fn(self)