discussionenhancementhelp wanted
Métriques du dépôt
- Stars
- (4 725 étoiles)
- Métriques de merge PR
- (Métriques PR en attente)
Description
It'd be nice to be able to write something like
model = @Chain(
Input(28^2),
Dense(32, relu),
Dense(10),
softmax)
It's a relatively minor convenience but it does avoid some redundancy when specifying chains, which is tedious to correct and easy to get wrong when trying different layer sizes.
Here's roughly how I imagine this working. The @Chain would expand to something like
shape = nothing
layer1, shape = fromshape(Input, shape, 10)
layer2, shape = fromshape(Dense, shape, 32, relu)
...
Chain(layer1, layer2, ...)
fromshape can then forward to an appropriate constructor or error for non-supported layers. Hopefully this strikes the right balance of simplicity/generality and we don't end up having to turn it into a full shape inference system.