Provide CUDA support for the binarize() operation on sparse matrices (#601)

* Add binarize function for CuSparseMatrixCSC and update its usage

* Refactor CUDA binarize function to use Bool as the CPU version

* Revert unrelated changes, make coherent PR on binarize() and nothing else

* Removed debug prints

Co-authored-by: Carlo Lucibello <carlo.lucibello@gmail.com>

* Unify binarize function signature

* Remove debug print statement from binarize function

---------

Co-authored-by: Carlo Lucibello <carlo.lucibello@gmail.com>

Author: dferre97

GNNGraphs/ext/GNNGraphsCUDAExt.jl

@@ -4,6 +4,7 @@ using CUDA
 using Random, Statistics, LinearAlgebra
 using GNNGraphs
 using GNNGraphs: COO_T, ADJMAT_T, SPARSE_T 
+using SparseArrays
 
 const CUMAT_T = Union{CUDA.AnyCuMatrix, CUDA.CUSPARSE.CuSparseMatrix}
 
@@ -20,6 +21,11 @@ GNNGraphs.dense_zeros_like(a::CUMAT_T, T::Type, sz = size(a)) = CUDA.zeros(T, sz
 
 GNNGraphs.iscuarray(x::AnyCuArray) = true
 
+function GNNGraphs.binarize(Mat::CUSPARSE.CuSparseMatrixCSC, T::DataType = Bool)
+    bin_vals = fill!(similar(nonzeros(Mat)), one(T))
+    return CUSPARSE.CuSparseMatrixCSC(Mat.colPtr, rowvals(Mat), bin_vals, size(Mat))
+end
+
 
 function sort_edge_index(u::AnyCuArray, v::AnyCuArray)
     dev = get_device(u)

GNNGraphs/src/query.jl

@@ -235,7 +235,7 @@ function Graphs.adjacency_matrix(g::GNNGraph{<:ADJMAT_T}, T::DataType = eltype(g
     @assert dir ∈ [:in, :out]
     A = g.graph
     if !weighted
-        A = binarize(A)
+        A = binarize(A, T)
     end
     A = T != eltype(A) ? T.(A) : A
     return dir == :out ? A : A'
@@ -377,7 +377,7 @@ end
 
 function _degree(A::AbstractMatrix, T::Type, dir::Symbol, edge_weight::Bool, num_nodes::Int)
     if edge_weight === false
-        A = binarize(A)
+        A = binarize(A, T)
     end
     A = eltype(A) != T ? T.(A) : A
     return dir == :out ? vec(sum(A, dims = 2)) :

GNNGraphs/src/utils.jl

@@ -295,7 +295,7 @@ function _rand_edges(rng, (n1, n2), m)
     return s, t, val
 end
 
-binarize(x) = map(>(0), x)
+binarize(x, T::DataType = Bool) = ifelse.(x .> 0, one(T), zero(T))
 
 CRC.@non_differentiable binarize(x...)
 CRC.@non_differentiable edge_encoding(x...)