Bugfix for batched gemv

lib/cublas/wrappers.jl

@@ -424,15 +424,16 @@ for (fname, fname_64, eltyin, eltyout) in (
             if length(A) != length(x) || length(A) != length(y)
                 throw(DimensionMismatch("Lengths of inputs must be the same"))
             end
+            m = size(A[1], 1)
+            n = size(A[1], 2)
             for (i, (As,xs,ys)) in enumerate(zip(A,x,y))
-                m,n = size(As)
+                if size(As) != (m, n)
+                    throw(DimensionMismatch("A[$i] has different dimension from A[1]. Dimensions between A's should be identical."))
+                end
                 if length(xs) != (trans == 'N' ? n : m) || length(ys) != (trans == 'N' ? m : n)
                     throw(DimensionMismatch("Input $i: A has dimension $(size(As)), x has dimension $(size(xs)), y has dimension $(size(ys))"))
                 end
             end
-
-            m = size(A[1], trans == 'N' ? 1 : 2)
-            n = size(A[1], trans == 'N' ? 2 : 1)
             lda = max(1,stride(A[1],2))
             incx = stride(x[1],1)
             incy = stride(y[1],1)
@@ -470,9 +471,9 @@ for (fname, fname_64, eltyin, eltyout) in (
             if size(A, 3) != size(x, 2) || size(A, 3) != size(y, 2)
                 throw(DimensionMismatch("Batch sizes must be equal for all inputs"))
             end
-            m = size(A, trans == 'N' ? 1 : 2)
-            n = size(A, trans == 'N' ? 2 : 1)
-            if m != size(y, 1) || n != size(x, 1)
+            m = size(A, 1)
+            n = size(A, 2)
+            if size(y, 1) != (trans == 'N' ? m : n) || size(x, 1) != (trans == 'N' ? n : m)
                 throw(DimensionMismatch("A has dimension $(size(A)), x has dimension $(size(x)), y has dimension $(size(y))"))
             end
 

test/libraries/cublas/level2.jl

@@ -24,8 +24,8 @@ k = 13
             @test testf(*, transpose(rand(elty, m, n)), rand(elty, m))
             @test testf(*, rand(elty, m, n)', rand(elty, m))
             x = rand(elty, m)
-            A = rand(elty, m, m + 1 )
-            y = rand(elty, m)
+            A = rand(elty, m, m + 1)
+            y = rand(elty, n)
             dx = CuArray(x)
             dA = CuArray(A)
             dy = CuArray(y)
@@ -44,6 +44,10 @@ k = 13
             dy = CUBLAS.gemv('N', dA, dx)
             hy = collect(dy)
             @test hy ≈ A * x
+            dy = CuArray(y)
+            dx = CUBLAS.gemv(elty <: Real ? 'T' : 'C', alpha, dA, dy)
+            hx = collect(dx)
+            @test hx ≈ alpha * A' * y
         end
 
         if CUBLAS.version() >= v"11.9"
@@ -72,6 +76,16 @@ k = 13
                     y[i] = alpha * A[i] * x[i] + beta * y[i]
                     @test y[i] ≈ hy
                 end
+                dy = CuArray{elty, 1}[]
+                for i=1:length(A)
+                    push!(dy, CuArray(y[i]))
+                end
+                CUBLAS.gemv_batched!(elty <: Real ? 'T' : 'C', alpha, dA, dy, beta, dx)
+                for i=1:length(A)
+                    hx = collect(dx[i])
+                    x[i] = alpha * A[i]' * y[i] + beta * x[i]
+                    @test x[i] ≈ hx
+                end
             end
         end
 
@@ -97,6 +111,13 @@ k = 13
                     y[:, i] = alpha * A[:, :, i] * x[:, i] + beta * y[:, i]
                     @test y[:, i] ≈ hy
                 end
+                dy = CuArray(y)
+                CUBLAS.gemv_strided_batched!(elty <: Real ? 'T' : 'C', alpha, dA, dy, beta, dx)
+                for i=1:size(A, 3)
+                    hx = collect(dx[:, i])
+                    x[:, i] = alpha * A[:, :, i]' * y[:, i] + beta * x[:, i]
+                    @test x[:, i] ≈ hx
+                end
             end
         end