Stacked RNN in Flux.jl?

[NeroBlackstone]

Motivation and description

How to build Stacked RNN in Flux.jl?

Is the following code the correct way?

using Flux
model = Chain(GRUv3(27 => 32),GRUv3(32 => 32),Dense(32 => 27))

Chain(
  Recur(
    GRUv3Cell(27 => 32),                # 5_792 parameters
  ),
  Recur(
    GRUv3Cell(32 => 32),                # 6_272 parameters
  ),
  Dense(32 => 27),                      # 891 parameters
)         # Total: 12 trainable arrays, 12_955 parameters,
          # plus 2 non-trainable, 64 parameters, summarysize 1.938 KiB.

There is no documentation mentioning this.

Possible Implementation

No response