xref: /llvm-project/mlir/test/Dialect/SparseTensor/sparse_lower_col.mlir (revision ced2fc7819d5ddea616ec330f18e08ff284c1868)
1// RUN: mlir-opt %s --sparse-reinterpret-map -sparsification | FileCheck %s --check-prefix=CHECK-HIR
2//
3// RUN: mlir-opt %s --sparse-reinterpret-map -sparsification --sparse-tensor-conversion --cse | \
4// RUN: FileCheck %s --check-prefix=CHECK-MIR
5//
6// RUN: mlir-opt %s --sparse-reinterpret-map -sparsification --sparse-tensor-conversion --cse \
7// RUN: --one-shot-bufferize="copy-before-write bufferize-function-boundaries function-boundary-type-conversion=identity-layout-map" | \
8// RUN: FileCheck %s --check-prefix=CHECK-LIR
9
10#CSC = #sparse_tensor.encoding<{
11  map = (d0, d1) -> (d1 : dense, d0 : compressed)
12}>
13
14#trait_matvec = {
15  indexing_maps = [
16    affine_map<(i,j) -> (i,j)>,  // A
17    affine_map<(i,j) -> (j)>,    // b
18    affine_map<(i,j) -> (i)>     // x (out)
19  ],
20  iterator_types = ["parallel","reduction"],
21  doc = "x(i) += A(i,j) * b(j)"
22}
23
24// CHECK-HIR-LABEL:   func @matvec(
25// CHECK-HIR-SAME:                 %[[VAL_0:.*]]: tensor<32x64xf64, #sparse{{[0-9]*}}>,
26// CHECK-HIR-SAME:                 %[[VAL_1:.*]]: tensor<64xf64>,
27// CHECK-HIR-SAME:                 %[[VAL_2:.*]]: tensor<32xf64>) -> tensor<32xf64> {
28// CHECK-HIR-DAG:       %[[VAL_3:.*]] = arith.constant 64 : index
29// CHECK-HIR-DAG:       %[[VAL_4:.*]] = arith.constant 0 : index
30// CHECK-HIR-DAG:       %[[VAL_5:.*]] = arith.constant 1 : index
31// CHECK-HIR:           %[[DEMAP:.*]] = sparse_tensor.reinterpret_map %[[VAL_0]]
32// CHECK-HIR-DAG:       %[[VAL_6:.*]] = sparse_tensor.positions %[[DEMAP]] {level = 1 : index}
33// CHECK-HIR-DAG:       %[[VAL_7:.*]] = sparse_tensor.coordinates %[[DEMAP]] {level = 1 : index}
34// CHECK-HIR-DAG:       %[[VAL_8:.*]] = sparse_tensor.values %[[DEMAP]]
35// CHECK-HIR-DAG:       %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : tensor<64xf64> to memref<64xf64>
36// CHECK-HIR-DAG:       %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : tensor<32xf64> to memref<32xf64>
37// CHECK-HIR:           scf.for %[[VAL_12:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {
38// CHECK-HIR-DAG:         %[[VAL_13:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_12]]] : memref<64xf64>
39// CHECK-HIR-DAG:         %[[VAL_14:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_12]]] : memref<?xindex>
40// CHECK-HIR-DAG:         %[[VAL_15:.*]] = arith.addi %[[VAL_12]], %[[VAL_5]] : index
41// CHECK-HIR-DAG:         %[[VAL_16:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_15]]] : memref<?xindex>
42// CHECK-HIR:             scf.for %[[VAL_17:.*]] = %[[VAL_14]] to %[[VAL_16]] step %[[VAL_5]] {
43// CHECK-HIR-DAG:           %[[VAL_18:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_17]]] : memref<?xindex>
44// CHECK-HIR-DAG:           %[[VAL_19:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_18]]] : memref<32xf64>
45// CHECK-HIR-DAG:           %[[VAL_20:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_17]]] : memref<?xf64>
46// CHECK-HIR:               %[[VAL_21:.*]] = arith.mulf %[[VAL_20]], %[[VAL_13]] : f64
47// CHECK-HIR:               %[[VAL_22:.*]] = arith.addf %[[VAL_19]], %[[VAL_21]] : f64
48// CHECK-HIR:               memref.store %[[VAL_22]], %[[VAL_11]]{{\[}}%[[VAL_18]]] : memref<32xf64>
49// CHECK-HIR:             }
50// CHECK-HIR:           }
51// CHECK-HIR:           %[[VAL_23:.*]] = bufferization.to_tensor %[[VAL_11]] : memref<32xf64>
52// CHECK-HIR:           return %[[VAL_23]] : tensor<32xf64>
53// CHECK-HIR:         }
54
55// CHECK-MIR-LABEL:   func @matvec(
56// CHECK-MIR-SAME:                 %[[VAL_0:.*]]: !llvm.ptr,
57// CHECK-MIR-SAME:                 %[[VAL_1:.*]]: tensor<64xf64>,
58// CHECK-MIR-SAME:                 %[[VAL_2:.*]]: tensor<32xf64>) -> tensor<32xf64> {
59// CHECK-MIR-DAG:       %[[VAL_3:.*]] = arith.constant 64 : index
60// CHECK-MIR-DAG:       %[[VAL_5:.*]] = arith.constant 0 : index
61// CHECK-MIR-DAG:       %[[VAL_6:.*]] = arith.constant 1 : index
62// CHECK-MIR-DAG:       %[[VAL_7:.*]] = call @sparsePositions0(%[[VAL_0]], %[[VAL_6]]) : (!llvm.ptr, index) -> memref<?xindex>
63// CHECK-MIR-DAG:       %[[VAL_8:.*]] = call @sparseCoordinates0(%[[VAL_0]], %[[VAL_6]]) : (!llvm.ptr, index) -> memref<?xindex>
64// CHECK-MIR-DAG:       %[[VAL_9:.*]] = call @sparseValuesF64(%[[VAL_0]]) : (!llvm.ptr) -> memref<?xf64>
65// CHECK-MIR-DAG:       %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_1]] : tensor<64xf64> to memref<64xf64>
66// CHECK-MIR-DAG:       %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]] : tensor<32xf64> to memref<32xf64>
67// CHECK-MIR:           scf.for %[[VAL_15:.*]] = %[[VAL_5]] to %[[VAL_3]] step %[[VAL_6]] {
68// CHECK-MIR:             %[[VAL_16:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_15]]] : memref<64xf64>
69// CHECK-MIR:             %[[VAL_17:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_15]]] : memref<?xindex>
70// CHECK-MIR:             %[[VAL_18:.*]] = arith.addi %[[VAL_15]], %[[VAL_6]] : index
71// CHECK-MIR:             %[[VAL_19:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_18]]] : memref<?xindex>
72// CHECK-MIR:             scf.for %[[VAL_20:.*]] = %[[VAL_17]] to %[[VAL_19]] step %[[VAL_6]] {
73// CHECK-MIR:               %[[VAL_21:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_20]]] : memref<?xindex>
74// CHECK-MIR:               %[[VAL_22:.*]] = memref.load %[[VAL_12]]{{\[}}%[[VAL_21]]] : memref<32xf64>
75// CHECK-MIR:               %[[VAL_23:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_20]]] : memref<?xf64>
76// CHECK-MIR:               %[[VAL_24:.*]] = arith.mulf %[[VAL_23]], %[[VAL_16]] : f64
77// CHECK-MIR:               %[[VAL_25:.*]] = arith.addf %[[VAL_22]], %[[VAL_24]] : f64
78// CHECK-MIR:               memref.store %[[VAL_25]], %[[VAL_12]]{{\[}}%[[VAL_21]]] : memref<32xf64>
79// CHECK-MIR:             }
80// CHECK-MIR:           }
81// CHECK-MIR:           %[[VAL_26:.*]] = bufferization.to_tensor %[[VAL_12]] : memref<32xf64>
82// CHECK-MIR:           return %[[VAL_26]] : tensor<32xf64>
83// CHECK-MIR:         }
84
85// CHECK-LIR-LABEL:   func @matvec(
86// CHECK-LIR-SAME:                 %[[VAL_0:.*]]: !llvm.ptr,
87// CHECK-LIR-SAME:                 %[[VAL_1:.*]]: memref<64xf64>,
88// CHECK-LIR-SAME:                 %[[VAL_2:.*]]: memref<32xf64>) -> memref<32xf64> {
89// CHECK-LIR-DAG:       %[[VAL_3:.*]] = arith.constant 64 : index
90// CHECK-LIR-DAG:       %[[VAL_5:.*]] = arith.constant 0 : index
91// CHECK-LIR-DAG:       %[[VAL_6:.*]] = arith.constant 1 : index
92// CHECK-LIR-DAG:       %[[VAL_7:.*]] = call @sparsePositions0(%[[VAL_0]], %[[VAL_6]]) : (!llvm.ptr, index) -> memref<?xindex>
93// CHECK-LIR-DAG:       %[[VAL_8:.*]] = call @sparseCoordinates0(%[[VAL_0]], %[[VAL_6]]) : (!llvm.ptr, index) -> memref<?xindex>
94// CHECK-LIR-DAG:       %[[VAL_9:.*]] = call @sparseValuesF64(%[[VAL_0]]) : (!llvm.ptr) -> memref<?xf64>
95// CHECK-LIR:           scf.for %[[VAL_13:.*]] = %[[VAL_5]] to %[[VAL_3]] step %[[VAL_6]] {
96// CHECK-LIR:             %[[VAL_14:.*]] = memref.load %[[VAL_1]]{{\[}}%[[VAL_13]]] : memref<64xf64>
97// CHECK-LIR:             %[[VAL_15:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_13]]] : memref<?xindex>
98// CHECK-LIR:             %[[VAL_16:.*]] = arith.addi %[[VAL_13]], %[[VAL_6]] : index
99// CHECK-LIR:             %[[VAL_17:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_16]]] : memref<?xindex>
100// CHECK-LIR:             scf.for %[[VAL_18:.*]] = %[[VAL_15]] to %[[VAL_17]] step %[[VAL_6]] {
101// CHECK-LIR:               %[[VAL_19:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_18]]] : memref<?xindex>
102// CHECK-LIR:               %[[VAL_20:.*]] = memref.load %[[VAL_2]]{{\[}}%[[VAL_19]]] : memref<32xf64>
103// CHECK-LIR:               %[[VAL_21:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_18]]] : memref<?xf64>
104// CHECK-LIR:               %[[VAL_22:.*]] = arith.mulf %[[VAL_21]], %[[VAL_14]] : f64
105// CHECK-LIR:               %[[VAL_23:.*]] = arith.addf %[[VAL_20]], %[[VAL_22]] : f64
106// CHECK-LIR:               memref.store %[[VAL_23]], %[[VAL_2]]{{\[}}%[[VAL_19]]] : memref<32xf64>
107// CHECK-LIR:             }
108// CHECK-LIR:           }
109// CHECK-LIR:           return %[[VAL_2]] : memref<32xf64>
110// CHECK-LIR:         }
111
112func.func @matvec(%arga: tensor<32x64xf64, #CSC>,
113             %argb: tensor<64xf64>,
114             %argx: tensor<32xf64>) -> tensor<32xf64> {
115  %0 = linalg.generic #trait_matvec
116      ins(%arga, %argb : tensor<32x64xf64, #CSC>, tensor<64xf64>)
117      outs(%argx: tensor<32xf64>) {
118    ^bb(%A: f64, %b: f64, %x: f64):
119      %0 = arith.mulf %A, %b : f64
120      %1 = arith.addf %x, %0 : f64
121      linalg.yield %1 : f64
122  } -> tensor<32xf64>
123  return %0 : tensor<32xf64>
124}
125