38 lines
736 B
Julia
38 lines
736 B
Julia
xs = rand(20)
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d = Affine(20, 10)
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# MXNet
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@mxonly let dm = mxnet(d, (20, 1))
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@test d(xs) ≈ dm(xs)
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end
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@mxonly let
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# TODO: test run
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using MXNet
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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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# TensorFlow
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@tfonly let dt = tf(d)
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@test d(xs) ≈ dt(xs)
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end
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@tfonly let
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using TensorFlow
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sess = TensorFlow.Session()
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X = placeholder(Float32)
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Y = Tensor(d, X)
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run(sess, initialize_all_variables())
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@test run(sess, Y, Dict(X=>xs')) ≈ d(xs)'
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end
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