Even more sparse tests (#2695)

* Even more sparse tests

* Yet more show tests

Author: kshyatt

lib/cusparse/array.jl

@@ -646,7 +646,7 @@ for (gpu, cpu) in [:CuSparseMatrixCSC => :SparseMatrixCSC,
                    :CuSparseMatrixCSR => :SparseMatrixCSC,
                    :CuSparseMatrixBSR => :SparseMatrixCSC,
                    :CuSparseMatrixCOO => :SparseMatrixCSC]
-    @eval Base.show(io::IOContext, x::$gpu) =
+    @eval Base.show(io::IO, x::$gpu) =
         show(io, $cpu(x))
 
     @eval function Base.show(io::IO, mime::MIME"text/plain", S::$gpu)

test/libraries/cusparse.jl

@@ -23,6 +23,7 @@ blockdim = 5
     dense_d_x = CuVector(x)
     CUDA.@allowscalar begin
         @test sprint(show, d_x) == replace(sprint(show, x), "SparseVector{Float64, Int64}"=>"CUDA.CUSPARSE.CuSparseVector{Float64, Int32}", "sparsevec(["=>"sparsevec(Int32[")
+        @test sprint(show, MIME"text/plain"(), d_x) == replace(sprint(show, MIME"text/plain"(), x), "SparseVector{Float64, Int64}"=>"CuSparseVector{Float64, Int32}", "sparsevec(["=>"sparsevec(Int32[")
         @test Array(d_x[:])        == x[:]
         @test d_x[firstindex(d_x)] == x[firstindex(x)]
         @test d_x[div(end, 2)]     == x[div(end, 2)]
@@ -44,6 +45,10 @@ blockdim = 5
     @test size(d_x) == (m, 1)
     x = sprand(m,n,0.2)
     d_x = CuSparseMatrixCSC(x)
+    d_tx = CuSparseMatrixCSC(transpose(x))
+    d_ax = CuSparseMatrixCSC(adjoint(x))
+    @test size(d_tx) == (n,m)
+    @test size(d_ax) == (n,m)
     @test CuSparseMatrixCSC(d_x) === d_x
     @test length(d_x) == m*n
     @test size(d_x)   == (m,n)
@@ -52,9 +57,12 @@ blockdim = 5
     @test size(d_x,3) == 1
     @test ndims(d_x)  == 2
     CUDA.@allowscalar begin
+        @test sprint(show, d_x) == sprint(show, SparseMatrixCSC(d_x))
         @test sprint(show, MIME"text/plain"(), d_x) == replace(sprint(show, MIME"text/plain"(), x), "SparseMatrixCSC{Float64, Int64}"=>"CuSparseMatrixCSC{Float64, Int32}")
         @test Array(d_x[:])        == x[:]
         @test d_x[:, :]            == x[:, :]
+        @test d_tx[:, :]           == transpose(x)[:, :]
+        @test d_ax[:, :]           == adjoint(x)[:, :]
         @test d_x[(1, 1)]          == x[1, 1]
         @test d_x[firstindex(d_x)] == x[firstindex(x)]
         @test d_x[div(end, 2)]     == x[div(end, 2)]
@@ -91,6 +99,8 @@ blockdim = 5
     @test_throws ArgumentError copyto!(d_y,d_x)
     x = sprand(m,n,0.2)
     d_x = CuSparseMatrixCOO(x)
+    d_tx = CuSparseMatrixCOO(transpose(x))
+    d_ax = CuSparseMatrixCOO(adjoint(x))
     @test CuSparseMatrixCOO(d_x) === d_x
     @test length(d_x) == m*n
     @test size(d_x)   == (m,n)
@@ -107,6 +117,8 @@ blockdim = 5
         @test d_x[firstindex(d_x)] == x[firstindex(x)]
         @test d_x[div(end, 2)]     == x[div(end, 2)]
         @test d_x[end]             == x[end]
+        @test d_tx[:, 1]           == transpose(x)[:, 1]
+        @test d_ax[1, :]           == adjoint(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/reduce.jl

@@ -1,8 +1,5 @@
 using CUDA.CUSPARSE, SparseArrays
 
-# XXX: these tests cause GC corruption (see JuliaGPU/CUDA.jl#2027)
-if false
-
 m,n = 5,6
 p = 0.5
 
@@ -25,7 +22,10 @@ for elty in [Int32, Int64, Float32, Float64]
         y = sum(x, dims=2)
         dy = sum(dx, dims=2)
         @test y ≈ Array(dy)
+        if elty in (Float32, Float64)
+            dy = mapreduce(abs, +, dx; init=zero(elty))
+            y  = mapreduce(abs, +, x; init=zero(elty))
+            @test y ≈ dy
+        end
     end
 end
-
-end