Merge pull request #590 from SciML/callbackdocsup

Update solve docstring with new callback syntax

src/solve.jl

@@ -51,15 +51,17 @@ The callback function `callback` is a function which is called after every optim
 step. Its signature is:
 
 ```julia
-callback = (u, loss_val, other_args) -> false
+callback = (state, loss_val, other_args) -> false
 ```
 
-where `u` and `loss_val` are the current optimization variables and loss/objective value
-in the optimization loop and `other_args` can be the extra things returned from
-the optimization `f`. This allows for saving values from the optimization and
+where `state` is a `OptimizationState` and stores information for the current 
+iteration of the solver and `loss_val` is loss/objective value. For more 
+information about the fields of the `state` look at the `OptimizationState` 
+documentation. The `other_args` can be the extra things returned from the 
+optimization `f`. This allows for saving values from the optimization and
 using them for plotting and display without recalculating. The callback should
-return a Boolean value, and the default should be `false`, such that the optimization
-gets stopped if it returns `true`.
+return a Boolean value, and the default should be `false`, such that the 
+optimization gets stopped if it returns `true`.
 
 ### Callback Example
 
@@ -76,7 +78,7 @@ function loss(u, p)
     sum(abs2, batch .- pred), pred
 end
 
-callback = function (p, l, pred; doplot = false) #callback function to observe training
+callback = function (state, l, pred; doplot = false) #callback function to observe training
     display(l)
     # plot current prediction against data
     if doplot