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Refactor #3
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Refactor #3
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foldfelis
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Aug 11, 2021
| loss(𝐱, 𝐲) = sum(abs2, 𝐲 .- m(𝐱)) / size(𝐱)[end] | ||
| data = [(𝐱[:, :, 1:5], 𝐲[:, 1:5])] | ||
| Flux.train!(loss, params(m), data, Flux.ADAM()) | ||
| @test true |
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Due to the use of Flux.train, it is a nondeterministic process. @test true is added to make sure the process is passed.
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The test case will still passed if the train! failed
| loss(𝐱, 𝐲) = sum(abs2, 𝐲 .- m(𝐱)) / size(𝐱)[end] | ||
| data = [(𝐱[:, :, 1:5], 𝐲[:, 1:5])] | ||
| Flux.train!(loss, params(m), data, Flux.ADAM()) | ||
| @test true |
| loss(x, y) = Flux.mse(real.(m(x)), y) | ||
| data = [(T.(𝐱[:, :, 1:5]), rand(T, 64, 1024, 5))] | ||
| Flux.train!(loss, params(m), data, Flux.ADAM()) | ||
| @test true |
|
Thanks in advance |
Merged
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