The input to my network are N x 2 arrays and I’d like to implement a Dense layer, followed by a convolution. This requires reshaping the output of the dense layer. The forward pass seems to work fine, but I think there’s an error on the backprop somewhere. Any help is appreciated.

```
m = Chain(
Dense(N, N, relu),
x -> reshape(x, N, 1, 2, 1),
Conv((2,1), 2=>1, relu),
x -> x[:],
Dense(N-1, N, relu)) |> gpu
m(train[1][1])
loss(x, y) = Flux.mse(m(x), y)
```

This is the error, some kind of dimension mismatch?:

```
MethodError: no method matching *(::TrackedArray{…,CuArray{Float32,2}}, ::CuArray{Float32,3})
Closest candidates are:
*(::Any, ::Any, !Matched::Any, !Matched::Any...) at operators.jl:502
```