write => for OptimiserChain

src/rules.jl

@@ -621,23 +621,26 @@ function apply!(o::ClipNorm, state, x, dx)
 end
 
 """
-    OptimiserChain(opts...)
+    OptimiserChain(o1, o2, o34...)
+    o1 => o2 => o3
 
-Compose a sequence of optimisers so that each `opt` in `opts`
+Compose a sequence of optimisers so that each `opt` in `(o1, o2, o34...)`
 updates the gradient, in the order specified.
+May be entered using `Pair` syntax with several `AbstractRule`s.
 
 With an empty sequence, `OptimiserChain()` is the identity,
 so `update!` will subtract the full gradient from the parameters.
 This is equivalent to `Descent(1)`.
 
 # Example
 ```jldoctest
-julia> o = OptimiserChain(ClipGrad(1.0), Descent(0.1));
+julia> o = ClipGrad(1.0) => Descent(0.1)
+OptimiserChain(ClipGrad{Float64}(1.0), Descent{Float64}(0.1))
 
 julia> m = (zeros(3),);
 
 julia> s = Optimisers.setup(o, m)
-(Leaf(OptimiserChain(ClipGrad{Float64}(1.0), Descent{Float64}(0.1)), (nothing, nothing)),)
+(Leaf(ClipGrad{Float64}(1.0) => Descent{Float64}(0.1), (nothing, nothing)),)
 
 julia> Optimisers.update(s, m, ([0.3, 1, 7],))[2]  # clips before discounting
 ([-0.03, -0.1, -0.1],)
@@ -648,6 +651,9 @@ struct OptimiserChain{O<:Tuple} <: AbstractRule
 end
 OptimiserChain(opts...) = OptimiserChain(opts)
 
+Base.Pair(a::AbstractRule, b::AbstractRule) = OptimiserChain(a, b)
+Base.Pair(a::AbstractRule, bc::OptimiserChain) = OptimiserChain(a, bc.opts...)
+
 @functor OptimiserChain
 
 init(o::OptimiserChain, x::AbstractArray) = map(opt -> init(opt, x), o.opts)
@@ -659,7 +665,14 @@ function apply!(o::OptimiserChain, states, x, dx, dxs...)
   end
 end
 
-function Base.show(io::IO, c::OptimiserChain)
+function Base.show(io::IO, c::OptimiserChain)  # compact show
+  if length(c.opts) > 1
+    join(io, c.opts, " => ")
+  else
+    show(io, MIME"text/plain"(), c)
+  end
+end
+function Base.show(io::IO, ::MIME"text/plain", c::OptimiserChain)
   print(io, "OptimiserChain(")
   join(io, c.opts, ", ")
   print(io, ")")