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Support for MultiRNNCell about lux.jl HOT 5 CLOSED

mchitre avatar mchitre commented on June 3, 2024
Support for MultiRNNCell

from lux.jl.

Comments (5)

mchitre avatar mchitre commented on June 3, 2024 1

Yes, I just tested that. I only need the stack at the end to allow a Dense layer to take in the output. So:

Chain(
  Recurrence(RNNCell(inputsize => latentsize); return_sequence=true),
  Recurrence(RNNCell(latentsize => latentsize); return_sequence=true),
      :
  x -> stack(x; dims=2)
)

works.

from lux.jl.

avik-pal avatar avik-pal commented on June 3, 2024

I will take a closer look at this, but I think we can just use Chain. If we can use a chain, we should just add a note in the manual

from lux.jl.

mchitre avatar mchitre commented on June 3, 2024

Chains of this type work:

Chain(
  Recurrence(RNNCell(inputsize => latentsize); return_sequence=true),
  x -> stack(x; dims=2),
  Recurrence(RNNCell(latentsize => latentsize); return_sequence=true),
  x -> stack(x; dims=2)
      :
)

from lux.jl.

avik-pal avatar avik-pal commented on June 3, 2024

You might not need a stack here I think. Recurrence should be able to take a VectorOfArray input (this was one of the reasons to not stack the outputs by default)

from lux.jl.

mchitre avatar mchitre commented on June 3, 2024

So just a note in the documentation is good enough for this.

from lux.jl.

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