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Update for latest ParameterSchedulers.jl release #1513

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Feb 23, 2021
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Update for latest ParameterSchedulers.jl release #1513

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681376f
Update for latest ParameterSchedulers.jl release
darsnack Feb 21, 2021
f3b5b13
Rephrase Stateful description in docs
darsnack Feb 22, 2021
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20 changes: 10 additions & 10 deletions docs/src/training/optimisers.md
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Original file line number Diff line number Diff line change
Expand Up @@ -145,22 +145,22 @@ First, we import ParameterSchedulers.jl and initalize a cosine annealing schedul
```julia
using ParameterSchedulers

schedule = ScheduleIterator(Cos(λ0 = 1e-4, λ1 = 1e-2, period = 10))
opt = Momentum()
```

Next, you can use your schedule directly in a `for`-loop:
```julia
for epoch in 1:100
opt.eta = next!(schedule)
schedule = Cos(λ0 = 1e-4, λ1 = 1e-2, period = 10)
for (eta, epoch) in zip(schedule, 1:100)
opt.eta = eta
# your training code here
end
```
`schedule` can also be indexed (e.g. `schedule(100)`) or iterated like any iterator in Julia.

`schedule` can also be indexed (e.g. `schedule[100]`) or iterated like any iterator in Julia:
ParameterSchedulers.jl schedules are stateless (they don't store their iteration state). If you want a _stateful_ schedule, you can use `ParameterSchedulers.Stateful`:
```julia
for (eta, epoch) in zip(schedule, 1:100)
opt.eta = eta
using ParameterSchedulers: Stateful, next!

schedule = Stateful(Cos(λ0 = 1e-4, λ1 = 1e-2, period = 10))
for epoch in 1:100
opt.eta = next!(schedule)
# your training code here
end
```
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