xref: /llvm-project/mlir/test/Dialect/SparseTensor/sparse_vector_mv.mlir (revision 5a9af39aab40bba52d4e46cabf4b1ab47f614fa2)
1// RUN: mlir-opt %s -sparsifier="vl=8" |  FileCheck %s
2
3#Dense = #sparse_tensor.encoding<{
4  map = (d0, d1) -> (d0 : dense, d1 : dense)
5}>
6
7#matvec = {
8  indexing_maps = [
9    affine_map<(i,j) -> (i,j)>, // A
10    affine_map<(i,j) -> (j)>,   // b
11    affine_map<(i,j) -> (i)>    // x (out)
12  ],
13  iterator_types = ["parallel", "reduction"],
14  doc = "X(i) += A(i,j) * B(j)"
15}
16
17// CHECK-LABEL: llvm.func @kernel_matvec
18// CHECK:       llvm.intr.vector.reduce.fadd
19func.func @kernel_matvec(%arga: tensor<?x?xf32, #Dense>,
20                         %argb: tensor<?xf32>,
21			 %argx: tensor<?xf32>) -> tensor<?xf32> {
22  %x = linalg.generic #matvec
23    ins(%arga, %argb: tensor<?x?xf32, #Dense>, tensor<?xf32>)
24    outs(%argx: tensor<?xf32>) {
25    ^bb(%a: f32, %b: f32, %x: f32):
26      %0 = arith.mulf %a, %b : f32
27      %1 = arith.addf %x, %0 : f32
28      linalg.yield %1 : f32
29  } -> tensor<?xf32>
30  return %x : tensor<?xf32>
31}
32