Scheduler{T, O, F}(schedule::AbstractSchedule, opt, update_func)
Scheduler(schedule, opt; update_func = (o, s) -> (o.eta = s))

Wrap a schedule and opt together with a Scheduler. The schedule is iterated on every call to Flux.apply!. The Scheduler can be used anywhere a Flux optimizer is used.

By default, the learning rate (i.e. opt.eta) is scheduled. Set update_func = (opt, schedule_val) -> ... to schedule an alternate field. If opt does not have a field eta, then there is no default behavior (you must manually set update_func).

Arguments

• schedule: the schedule to use
• opt: a Flux optimizer
• update_func: a mutating function of with inputs (optim, param) that mutates optim’s fields based on the current param value

Examples

# cosine annealing schedule for Descent
julia> s = Cos(λ0 = 0.1, λ1 = 0.8, period = 10);

julia> opt = Scheduler(s, Descent())
Scheduler(Cos{Float64,Int64}(0.1, 0.8, 10), Descent(0.1))

# schedule the momentum term of Momentum
julia> opt = Scheduler(s, Momentum(); update_func = (o, s) -> o.rho = s)
Scheduler(Cos{Float64,Int64}(0.1, 0.8, 10), Momentum(0.01, 0.9, IdDict{Any,Any}()))