Fix doctest (#219)

Author: gdalle

DifferentiationInterface/docs/src/backends.md

@@ -70,14 +70,15 @@ You can check this compatibility using [`check_twoarg`](@ref).
 Only some backends are able to compute Hessians.
 You can use [`check_hessian`](@ref) to check this feature.
 
-
-## API Reference
+## API reference
 
 !!! warning
     The following documentation has been re-exported from [ADTypes.jl](https://github.com/SciML/ADTypes.jl).
     Refer to the ADTypes documentation for more information.
 
 ```@docs
+ADTypes
+ADTypes.AbstractADType
 AutoChainRules
 AutoDiffractor
 AutoEnzyme
@@ -92,4 +93,4 @@ AutoTapir
 AutoTracker
 AutoZygote
 AutoSparse
-```
+```

DifferentiationInterface/docs/src/overview.md

@@ -123,7 +123,7 @@ We make this available for all backends with the following operators:
 | :--------------------------------- | :---------------------------------- |
 | [`value_and_pullback_split`](@ref) | [`value_and_pullback!_split`](@ref) |
 
-## Translation
+### Translation
 
 The wrapper [`DifferentiateWith`](@ref) allows you to take a function and specify that it should be differentiated with the backend of your choice.
 In other words, when you try to differentiate `dw = DifferentiateWith(f, backend1)` with `backend2`, then `backend1` steps in and `backend2` does nothing.

DifferentiationInterface/src/translation/differentiate_with.jl

@@ -20,7 +20,7 @@ This works by defining new rules overriding the behavior of the outer backend th
 
 # Example
 
-```@repl
+```jldoctest
 using DifferentiationInterface
 import ForwardDiff, Zygote
 
@@ -32,8 +32,12 @@ end
 
 dw = DifferentiateWith(f, AutoForwardDiff());
 
-gradient(dw, AutoZygote(), [1.0, 2.0])  # works because it calls ForwardDiff instead
-gradient(f, AutoZygote(), [1.0, 2.0])  # fails
+gradient(dw, AutoZygote(), [2.0])  # calls ForwardDiff instead
+
+# output
+
+1-element Vector{Float64}:
+ 1.0
 ```
 """
 struct DifferentiateWith{F,B<:AbstractADType}