Fixed: saving.md

docs/src/saving.md

@@ -118,4 +118,13 @@ revert to an older copy of the model if it starts to overfit.
 @save "model-$(now()).bson" model loss = testloss()
 ```
 
-Note that to resume a model's training, you might need to restore other stateful parts of your training loop. Possible examples are stateful optimizers (which usually utilize an `IdDict` to store their state, which is not automatically handled by `BSON`), and the randomness used to partition the original data into the training and validation sets.
+Note that to resume a model's training, you might need to restore other stateful parts of your training loop. Possible examples are stateful optimizers (which usually utilize an `IdDict` to store their state), and the randomness used to partition the original data into the training and validation sets.
+
+You can store the optimiser state alongside the model, to resume training
+exactly where you left off; BSON is smart enough to cache values and insert links when saving, but only only if it knows everything to be saved up front. (See [here](https://github.com/JuliaIO/BSON.jl/blob/3b4a2cebda0afae11aab310f0a4d12b6a5234160/src/write.jl#L71).) So models and optimizers must be saved together to have the latter work when restoring.
+
+```julia
+opt = ADAM()
+@save "model-$(now()).bson" model opt
+```
+