More tests and a matmatmul fix (#2697)

Author: kshyatt

lib/cusparse/interfaces.jl

@@ -177,8 +177,9 @@ function LinearAlgebra.generic_matmatmul!(C::CuSparseMatrixCOO{T}, tA, tB, A::Cu
     A_csr = CuSparseMatrixCSR(A)
     B_csr = CuSparseMatrixCSR(B)
     C_csr = CuSparseMatrixCSR(C)
-    generic_matmatmul!(C_csr, tA, tB, A_csr, B_csr, alpha, beta)
-    C = CuSparseMatrixCOO(C_csr) # is this in-place of the original C?
+    LinearAlgebra.generic_matmatmul!(C_csr, tA, tB, A_csr, B_csr, alpha, beta)
+    copyto!(C, CuSparseMatrixCOO(C_csr))
+    return C
 end
 
 for SparseMatrixType in (:CuSparseMatrixCSC, :CuSparseMatrixCSR)

test/libraries/cusparse.jl

@@ -101,9 +101,14 @@ blockdim = 5
     d_x = CuSparseMatrixCOO(x)
     d_tx = CuSparseMatrixCOO(transpose(x))
     d_ax = CuSparseMatrixCOO(adjoint(x))
+    d_tcx = CuSparseMatrixCOO(transpose(CuSparseMatrixCSC(x)))
+    d_acx = CuSparseMatrixCOO(adjoint(CuSparseMatrixCSC(x)))
+    # reordered I, J to test other indexing path
+    d_rx = CuSparseMatrixCOO{eltype(d_x), Int32}(copy(d_x.colInd), copy(d_x.rowInd), copy(d_x.nzVal))
     @test CuSparseMatrixCOO(d_x) === d_x
     @test length(d_x) == m*n
     @test size(d_x)   == (m,n)
+    @test size(d_rx)  == (n,m)
     @test size(d_x,1) == m
     @test size(d_x,2) == n
     @test size(d_x,3) == 1
@@ -119,6 +124,10 @@ blockdim = 5
         @test d_x[end]             == x[end]
         @test d_tx[:, 1]           == transpose(x)[:, 1]
         @test d_ax[1, :]           == adjoint(x)[1, :]
+        @test d_tcx[:, 1]          == transpose(x)[:, 1]
+        @test d_acx[1, :]          == adjoint(x)[1, :]
+        @test d_rx[:, 1]           == transpose(x)[:, 1]
+        @test d_rx[1, :]           == transpose(x)[1, :]
         @test d_x[firstindex(d_x), firstindex(d_x)] == x[firstindex(x), firstindex(x)]
         @test d_x[div(end, 2), div(end, 2)]         == x[div(end, 2), div(end, 2)]
         @test d_x[end, end]        == x[end, end]

test/libraries/cusparse/interfaces.jl

@@ -85,6 +85,14 @@ using LinearAlgebra, SparseArrays
                     C = opa(A) * opb(B)
                     dC = opa(dA) * opb(dB)
                     @test C ≈ collect(dC)
+                    if opa == opb == identity
+                        dA = SparseMatrixType(A)
+                        dB = SparseMatrixType(B)
+                        mul!(dC, opa(dA), opb(dB), 3, 3.2)
+                        C = 3.2 * C + 3 * opa(A) * opb(B)
+                        @show SparseMatrixType
+                        @test collect(dC) ≈ C
+                    end
                 end
             end
         end