41 lines
900 B
Markdown
41 lines
900 B
Markdown
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# Char RNN
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```julia
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using Flux
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import StatsBase: wsample
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nunroll = 50
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nbatch = 50
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getseqs(chars, alphabet) = sequences((onehot(Float32, char, alphabet) for char in chars), nunroll)
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getbatches(chars, alphabet) = batches((getseqs(part, alphabet) for part in chunk(chars, nbatch))...)
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input = readstring("$(homedir())/Downloads/shakespeare_input.txt")
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alphabet = unique(input)
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N = length(alphabet)
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Xs, Ys = getbatches(input, alphabet), getbatches(input[2:end], alphabet)
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model = Chain(
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Input(N),
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LSTM(N, 256),
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LSTM(256, 256),
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Affine(256, N),
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softmax)
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m = tf(unroll(model, nunroll))
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@time Flux.train!(m, Xs, Ys, η = 0.1, epoch = 1)
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function sample(model, n, temp = 1)
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s = [rand(alphabet)]
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m = tf(unroll(model, 1))
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for i = 1:n
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push!(s, wsample(alphabet, softmax(m(Seq((onehot(Float32, s[end], alphabet),)))[1]./temp)))
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end
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return string(s...)
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end
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sample(model, 100)
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```
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