35 lines
811 B
Julia
35 lines
811 B
Julia
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using MXNet
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Flux.loadmx()
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@testset "MXNet" begin
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xs = rand(20)
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d = Affine(20, 10)
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dm = mxnet(d, (20, 1))
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@test d(xs) ≈ dm(xs)
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@testset "FeedForward interface" begin
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# TODO: test run
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f = mx.FeedForward(Chain(d, softmax))
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@test mx.infer_shape(f.arch, data = (20, 1))[2] == [(10, 1)]
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m = Chain(Input(28,28), Conv2D((5,5), out = 3), MaxPool((2,2)),
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flatten, Affine(1587, 10), softmax)
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f = mx.FeedForward(m)
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@test mx.infer_shape(f.arch, data = (20, 20, 5, 1))[2] == [(10, 1)]
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end
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@testset "Stack Traces" begin
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model = TLP(Affine(10, 20), Affine(21, 15))
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info("The following warning is normal")
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e = try mxnet(model, (10, 1))
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catch e e end
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@test isa(e, DataFlow.Interpreter.Exception)
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@test e.trace[1].func == Symbol("Flux.Affine")
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@test e.trace[2].func == :TLP
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end
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end
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