added GradientResult example

examples/gradient.jl

@@ -17,6 +17,7 @@ const compiled_f_tape = compile(f_tape)
 a, b = rand(100, 100), rand(100, 100)
 inputs = (a, b)
 results = (similar(a), similar(b))
+all_results = map(DiffBase.GradientResult, results)
 cfg = GradientConfig(inputs)
 
 ####################
@@ -29,6 +30,10 @@ cfg = GradientConfig(inputs)
 # this should be the fastest method, and non-allocating
 gradient!(results, compiled_f_tape, inputs)
 
+# the same as the above, but in addition to calculating the gradients, the value `f(a, b)`
+# is loaded into the the provided `DiffResult` instances (see DiffBase.jl documentation).
+gradient!(all_results, compiled_f_tape, inputs)
+
 # this should be the second fastest method, and also non-allocating
 gradient!(results, f_tape, inputs)