2016-08-25 21:49:21 +00:00
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using Flux, MNIST
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2016-04-01 21:11:42 +00:00
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2016-08-25 16:26:52 +00:00
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@time begin
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const data = [(trainfeatures(i), onehot(trainlabel(i), 0:9)) for i = 1:60_000]
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const train = data[1:50_000]
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const test = data[50_001:60_000]
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nothing
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end
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2016-04-01 21:11:42 +00:00
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2016-08-25 16:26:52 +00:00
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m = Chain(
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2016-04-01 21:11:42 +00:00
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Input(784),
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2016-08-25 21:49:21 +00:00
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Dense(128), relu,
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Dense( 64), relu,
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Dense( 10), softmax)
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2016-04-01 21:11:42 +00:00
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2016-08-25 16:26:52 +00:00
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model = mxnet(m, 784)
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@time Flux.train!(model, train, test, epoch = 1, η=0.001)
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