Flux: Dimension mismatch error

New to Julia
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2

Dense wants either a vector (for one sample) or a matrix (whose columns are many samples), but it’s getting a vector of tuples. One way to convert is this:

julia> rawInputs
100-element Vector{Tuple{Float32, Float32}}:
 (-0.953125, -0.203125)
 (0.046875, 0.796875)
 (0.546875, -0.703125)
...

julia> stack(rawInputs)
2×100 Matrix{Float32}:
 -0.953125  0.046875   0.546875  -0.453125  …  -0.882812  0.117188   0.617188  -0.382812
 -0.203125  0.796875  -0.703125   0.296875     -0.867188  0.132812  -0.367188   0.632812

julia> size(ans, 1) == 2
true

The way you have written training is the old “implicit” style, I’d recommend writing it like this (see docs here for more):

julia> loss(m, x, y) = Flux.Losses.mse(m(x), y);  # takes model as explicit argument

julia> opt = Flux.setup(Descent(lr), model);  # state necc. really for other opt rules

julia> train_data = [(stack(rawInputs), stack(rawOutputs))];

julia> @time for ii in 1:epochs
           Flux.train!(loss, model, train_data, opt)
       end
  0.483642 seconds (375.89 k allocations: 1.744 GiB, 23.82% gc time, 14.30% compilation time: 100% of which was recompilation)
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