TastyPancakes
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Flux.jl
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use Float32 here

This commit is contained in:
Mike J Innes 2016-10-25 16:23:04 +01:00
parent a06145a145
commit d442dd8c5b
2 changed files with 3 additions and 2 deletions
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2
examples/MNIST.jl
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@ -1,6 +1,6 @@
using Flux, MNIST
data = [(trainfeatures(i), Vector{Float32}(onehot(trainlabel(i), 0:9))) for i = 1:60_000]
data = [(Vector{Float32}(trainfeatures(i)), onehot(Float32, trainlabel(i), 0:9)) for i = 1:60_000]
train = data[1:50_000]
test = data[50_001:60_000]

3
src/utils.jl
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@ -2,7 +2,8 @@ export AArray, onehot, onecold
const AArray = AbstractArray
onehot(label, labels) = [i == label for i in labels]
onehot(T::Type, label, labels) = T[i == label for i in labels]
onehot(label, labels) = onehot(Int, label, labels)
onecold(pred, labels = 1:length(pred)) = labels[findfirst(pred, maximum(pred))]
initn(dims...) = randn(Float32, dims...)/1000