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examples/Project.toml

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[deps]
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CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
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DiffEqFlux = "aae7a2af-3d4f-5e19-a356-7da93b79d9d0"
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DifferentialEquations = "0c46a032-eb83-5123-abaf-570d42b7fbaa"
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Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
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GraphNeuralNetworks = "cffab07f-9bc2-4db1-8861-388f63bf7694"
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Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
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MLDatasets = "eb30cadb-4394-5ae3-aed4-317e484a6458"
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MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
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NNlib = "872c559c-99b0-510c-b3b7-b6c96a88d5cd"
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NNlibCUDA = "a00861dc-f156-4864-bf3c-e6376f28a68d"

examples/link_prediction_cora.jl

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epochs = 200 # number of epochs
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seed = 17 # set seed > 0 for reproducibility
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usecuda = false # if true use cuda (if available)
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nhidden = 128 # dimension of hidden features
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nhidden = 64 # dimension of hidden features
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infotime = 10 # report every `infotime` epochs
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end
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