`get_data` creates NaNs on the GPU about fluxarchitectures.jl HOT 4 CLOSED

function prepare_data(data, poollength, datalength, horizon; normalise=true)
  extendedlength = datalength + poollength
  extendedlength > size(data, 1) && throw(ArgumentError("datalength $(datalength) larger than available data $(size(data, 1) - poollength)"))
  (normalise == true) && (data = Flux.normalise(data, dims=1))
  features = zeros(Float32, size(data, 2), poollength, 1, datalength)  # CHANGED THIS
  for i = 0:poollength - 1
      for j = poollength:datalength
          #                  \/ this j starts at poollength => 1:(poollength-1) will always be uninit data
          features[:,i + 1,1,j] = data[j - i,:]
      end
  end
  labels = circshift(data[1:datalength,1], -horizon)
  return features, labels
end

prepare_data(ones(Float32, 510, 3), 10, 500, 7, normalise=false)
> 3×10×1×500 Array{Float32, 4}:
[:, :, 1, 1] =
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0

[:, :, 1, 2] =
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0

[:, :, 1, 3] =
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0

...

[:, :, 1, 498] =
 1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0
 1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0
 1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0

[:, :, 1, 499] =
 1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0
 1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0
 1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0

[:, :, 1, 500] =
 1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0
 1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0
 1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0