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Revert unrelated changes, make coherent PR on binarize() and nothing else
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GNNlib/ext/GNNlibCUDAExt.jl

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@@ -7,6 +7,14 @@ using GNNGraphs: GNNGraph, COO_T, SPARSE_T
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###### PROPAGATE SPECIALIZATIONS ####################
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## COPY_XJ
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## avoid the fast path on gpu until we have better cuda support
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function GNNlib.propagate(::typeof(copy_xj), g::GNNGraph{<:Union{COO_T, SPARSE_T}}, ::typeof(+),
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xi, xj::AnyCuMatrix, e)
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propagate((xi, xj, e) -> copy_xj(xi, xj, e), g, +, xi, xj, e)
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end
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## E_MUL_XJ
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## avoid the fast path on gpu until we have better cuda support

GNNlib/src/msgpass.jl

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@@ -213,8 +213,7 @@ end
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## COPY_XJ
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function propagate(::typeof(copy_xj), g::GNNGraph, ::typeof(+), xi, xj::AbstractMatrix, e)
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@debug "copy_xj: propagating with type $(typeof(xj))"
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A = adjacency_matrix(g, eltype(xj); weighted = false)
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A = adjacency_matrix(g, weighted = false)
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return xj * A
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end
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