Flux.jl/examples/MNIST.jl
2017-05-01 14:23:48 +01:00

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510 B
Julia

using Flux, MNIST
using Flux: accuracy
data = [(trainfeatures(i), onehot(trainlabel(i), 0:9)) for i = 1:60_000]
train = data[1:50_000]
test = data[50_001:60_000]
m = @Chain(
Input(784),
Affine(128), relu,
Affine( 64), relu,
Affine( 10), softmax)
# Convert to MXNet
model = mxnet(m)
# An example prediction pre-training
model(tobatch(data[1][1]))
Flux.train!(model, train, η = 1e-3,
cb = [()->@show accuracy(m, test)])
# An example prediction post-training
model(tobatch(data[1][1]))