xref: /llvm-project/mlir/test/Dialect/SparseTensor/sparse_transpose.mlir (revision 94e27c265a9aeb3659175ecee81a68d1763e0180)
1// RUN: mlir-opt %s --sparse-reinterpret-map -sparsification | FileCheck %s
2
3#DCSR = #sparse_tensor.encoding<{
4  map = (d0, d1) -> (d0 : compressed, d1 : compressed)
5}>
6
7#transpose_trait = {
8  indexing_maps = [
9    affine_map<(i,j) -> (j,i)>,  // A
10    affine_map<(i,j) -> (i,j)>   // X
11  ],
12  iterator_types = ["parallel", "parallel"],
13  doc = "X(i,j) = A(j,i)"
14}
15
16// TODO: improve auto-conversion followed by yield
17
18// CHECK-LABEL:   func.func @sparse_transpose_auto(
19// CHECK-SAME:      %[[VAL_0:.*]]: tensor<3x4xf64, #sparse{{[0-9]*}}>) -> tensor<4x3xf64, #sparse{{[0-9]*}}> {
20// CHECK-DAG:       %[[VAL_1:.*]] = arith.constant 0 : index
21// CHECK-DAG:       %[[VAL_2:.*]] = arith.constant 1 : index
22// CHECK-DAG:       %[[VAL_3:.*]] = tensor.empty() : tensor<4x3xf64, #sparse{{[0-9]*}}>
23// CHECK-DAG:       %[[VAL_4:.*]] = sparse_tensor.convert %[[VAL_0]] : tensor<3x4xf64, #sparse{{[0-9]*}}> to tensor<3x4xf64, #sparse{{[0-9]*}}>
24// CHECK:           %[[DEMAP:.*]] = sparse_tensor.reinterpret_map %[[VAL_4]] : tensor<3x4xf64, #sparse{{[0-9]*}}> to tensor<4x3xf64, #sparse{{[0-9]*}}>
25// CHECK-DAG:       %[[VAL_5:.*]] = sparse_tensor.positions %[[DEMAP]] {level = 0 : index} : tensor<4x3xf64, #sparse{{[0-9]*}}> to memref<?xindex>
26// CHECK-DAG:       %[[VAL_6:.*]] = sparse_tensor.coordinates %[[DEMAP]] {level = 0 : index} : tensor<4x3xf64, #sparse{{[0-9]*}}> to memref<?xindex>
27// CHECK-DAG:       %[[VAL_7:.*]] = sparse_tensor.positions %[[DEMAP]] {level = 1 : index} : tensor<4x3xf64, #sparse{{[0-9]*}}> to memref<?xindex>
28// CHECK-DAG:       %[[VAL_8:.*]] = sparse_tensor.coordinates %[[DEMAP]] {level = 1 : index} : tensor<4x3xf64, #sparse{{[0-9]*}}> to memref<?xindex>
29// CHECK-DAG:       %[[VAL_9:.*]] = sparse_tensor.values %[[DEMAP]] : tensor<4x3xf64, #sparse{{[0-9]*}}> to memref<?xf64>
30// CHECK:           %[[VAL_10:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_1]]] : memref<?xindex>
31// CHECK:           %[[VAL_11:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_2]]] : memref<?xindex>
32// CHECK:           %[[VAL_12:.*]] = scf.for %[[VAL_13:.*]] = %[[VAL_10]] to %[[VAL_11]] step %[[VAL_2]] iter_args(%[[VAL_14:.*]] = %[[VAL_3]]) -> (tensor<4x3xf64, #sparse{{[0-9]*}}>) {
33// CHECK:             %[[VAL_15:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_13]]] : memref<?xindex>
34// CHECK:             %[[VAL_16:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_13]]] : memref<?xindex>
35// CHECK:             %[[VAL_17:.*]] = arith.addi %[[VAL_13]], %[[VAL_2]] : index
36// CHECK:             %[[VAL_18:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_17]]] : memref<?xindex>
37// CHECK:             %[[VAL_19:.*]] = scf.for %[[VAL_20:.*]] = %[[VAL_16]] to %[[VAL_18]] step %[[VAL_2]] iter_args(%[[VAL_21:.*]] = %[[VAL_14]]) -> (tensor<4x3xf64, #sparse{{[0-9]*}}>) {
38// CHECK:               %[[VAL_22:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_20]]] : memref<?xindex>
39// CHECK:               %[[VAL_23:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_20]]] : memref<?xf64>
40// CHECK:               %[[VAL_24:.*]] = tensor.insert %[[VAL_23]] into %[[VAL_21]]{{\[}}%[[VAL_15]], %[[VAL_22]]] : tensor<4x3xf64, #sparse{{[0-9]*}}>
41// CHECK:               scf.yield %[[VAL_24]] : tensor<4x3xf64, #sparse{{[0-9]*}}>
42// CHECK:             }
43// CHECK:             scf.yield %[[VAL_25:.*]] : tensor<4x3xf64, #sparse{{[0-9]*}}>
44// CHECK:           }
45// CHECK:           %[[VAL_26:.*]] = sparse_tensor.load %[[VAL_27:.*]] hasInserts : tensor<4x3xf64, #sparse{{[0-9]*}}>
46// CHECK:           return %[[VAL_26]] : tensor<4x3xf64, #sparse{{[0-9]*}}>
47// CHECK:         }
48func.func @sparse_transpose_auto(%arga: tensor<3x4xf64, #DCSR>)
49                                     -> tensor<4x3xf64, #DCSR> {
50  %i = tensor.empty() : tensor<4x3xf64, #DCSR>
51  %0 = linalg.generic #transpose_trait
52     ins(%arga: tensor<3x4xf64, #DCSR>)
53     outs(%i: tensor<4x3xf64, #DCSR>) {
54     ^bb(%a: f64, %x: f64):
55       linalg.yield %a : f64
56  } -> tensor<4x3xf64, #DCSR>
57  return %0 : tensor<4x3xf64, #DCSR>
58}
59