47 lines
1.3 KiB
Julia
47 lines
1.3 KiB
Julia
using Flux, CuArrays, Test
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@testset "RNN" begin
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@testset for R in [RNN, GRU, LSTM]
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rnn = R(10, 5)
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curnn = mapleaves(gpu, rnn)
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@testset for batch_size in (1, 5)
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Flux.reset!(rnn)
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Flux.reset!(curnn)
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x = batch_size == 1 ?
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param(rand(10)) :
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param(rand(10,batch_size))
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cux = gpu(x)
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y = (rnn(x); rnn(x))
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cuy = (curnn(cux); curnn(cux))
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@test y.data ≈ collect(cuy.data)
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@test haskey(Flux.CUDA.descs, curnn.cell)
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Δ = randn(size(y))
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Flux.back!(y, Δ)
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Flux.back!(cuy, gpu(Δ))
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@test x.grad ≈ collect(cux.grad)
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@test rnn.cell.Wi.grad ≈ collect(curnn.cell.Wi.grad)
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@test rnn.cell.Wh.grad ≈ collect(curnn.cell.Wh.grad)
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@test rnn.cell.b.grad ≈ collect(curnn.cell.b.grad)
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@test rnn.cell.h.grad ≈ collect(curnn.cell.h.grad)
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if isdefined(rnn.cell, :c)
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@test rnn.cell.c.grad ≈ collect(curnn.cell.c.grad)
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end
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Flux.reset!(rnn)
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Flux.reset!(curnn)
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ohx = batch_size == 1 ?
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Flux.onehot(rand(1:10), 1:10) :
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Flux.onehotbatch(rand(1:10, batch_size), 1:10)
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cuohx = gpu(ohx)
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y = (rnn(ohx); rnn(ohx))
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cuy = (curnn(cuohx); curnn(cuohx))
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@test y.data ≈ collect(cuy.data)
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end
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end
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end
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