model saving docs

docs/make.jl

@@ -17,6 +17,7 @@ makedocs(modules=[Flux, NNlib],
                      "Training" => "training/training.md"],
                   "One-Hot Encoding" => "data/onehot.md",
                   "GPU Support" => "gpu.md",
+                  "Saving & Loading" => "saving.md",
                   "Community" => "community.md"])
 
 deploydocs(

docs/src/saving.md

@@ -0,0 +1,78 @@
+# Saving and Loading Models
+
+You may wish to save models so that they can be loaded and run in a later
+session. The easiest way to do this is via
+[BSON.jl](https://github.com/MikeInnes/BSON.jl).
+
+Save a model:
+
+```julia
+julia> using Flux
+
+julia> model = Chain(Dense(10,5,relu),Dense(5,2),softmax)
+Chain(Dense(10, 5, NNlib.relu), Dense(5, 2), NNlib.softmax)
+
+julia> using BSON: @save
+
+julia> @save "mymodel.bson" model
+```
+
+Load it again:
+
+```julia
+julia> using Flux
+
+julia> using BSON: @load
+
+julia> @load "mymodel.bson" model
+
+julia> model
+Chain(Dense(10, 5, NNlib.relu), Dense(5, 2), NNlib.softmax)
+```
+
+Models are just normal Julia structs, so it's fine to use any Julia storage
+format for this purpose. BSON.jl is particularly well supported and most likely
+to be forwards compatible (that is, models saved now will load in future
+versions of Flux).
+
+!!! note
+
+    If a saved model's weights are stored on the GPU, the model will not load
+    later on if there is no GPU support available. It's best to [move your model
+    to the CPU](gpu.md) with `cpu(model)` before saving it.
+
+## Saving Model Weights
+
+In some cases it may be useful to save only the model parameters themselves, and
+rebuild the model architecture in your code. You can use `params(model)` to get
+model parameters. You can also use `data.(params)` to remove tracking.
+
+```Julia
+julia> using Flux
+
+julia> model = Chain(Dense(10,5,relu),Dense(5,2),softmax)
+Chain(Dense(10, 5, NNlib.relu), Dense(5, 2), NNlib.softmax)
+
+julia> weights = Tracker.data.(params(model));
+
+julia> using BSON: @save
+
+julia> @save "mymodel.bson" weights
+```
+
+You can easily load parameters back into a model with `Flux.loadparams!`.
+
+```julia
+julia> using Flux
+
+julia> using BSON: @load
+
+julia> model = Chain(Dense(10,5,relu),Dense(5,2),softmax)
+Chain(Dense(10, 5, NNlib.relu), Dense(5, 2), NNlib.softmax)
+
+julia> @load "mymodel.bson" weights
+
+julia> Flux.loadparams!(model, weights)
+```
+
+The new `model` we created will now be identical to the one we saved parameters for.