xref: /llvm-project/mlir/test/Dialect/SparseTensor/convert_sparse2sparse_element.mlir (revision dbe1be9aa4e010f8ed945e19ba93a1f927aade8e)
1// RUN: mlir-opt %s --sparse-tensor-codegen --canonicalize --cse | FileCheck %s
2
3#SparseVector64 = #sparse_tensor.encoding<{
4  map = (d0) -> (d0 : compressed),
5  posWidth = 64,
6  crdWidth = 64
7}>
8
9#SparseVector32 = #sparse_tensor.encoding<{
10  map = (d0) -> (d0 : compressed),
11  posWidth = 32,
12  crdWidth = 32
13}>
14
15
16// CHECK-LABEL:   func.func @sparse_convert(
17// CHECK-SAME:      %[[VAL_0:.*0]]: memref<?xi64>,
18// CHECK-SAME:      %[[VAL_1:.*1]]: memref<?xi64>,
19// CHECK-SAME:      %[[VAL_2:.*2]]: memref<?xf32>,
20// CHECK-SAME:      %[[VAL_3:.*3]]: !sparse_tensor.storage_specifier
21// CHECK:           %[[VAL_4:.*]] = arith.constant 1 : index
22// CHECK:           %[[VAL_5:.*]] = arith.constant 0 : index
23// CHECK:           %[[VAL_6:.*]] = memref.dim %[[VAL_0]], %[[VAL_5]] : memref<?xi64>
24// CHECK:           %[[VAL_7:.*]] = memref.alloc(%[[VAL_6]]) : memref<?xi32>
25// CHECK:           scf.for %[[VAL_8:.*]] = %[[VAL_5]] to %[[VAL_6]] step %[[VAL_4]] {
26// CHECK:             %[[VAL_9:.*]] = memref.load %[[VAL_0]]{{\[}}%[[VAL_8]]] : memref<?xi64>
27// CHECK:             %[[VAL_10:.*]] = arith.trunci %[[VAL_9]] : i64 to i32
28// CHECK:             memref.store %[[VAL_10]], %[[VAL_7]]{{\[}}%[[VAL_8]]] : memref<?xi32>
29// CHECK:           }
30// CHECK:           %[[VAL_11:.*]] = memref.dim %[[VAL_1]], %[[VAL_5]] : memref<?xi64>
31// CHECK:           %[[VAL_12:.*]] = memref.alloc(%[[VAL_11]]) : memref<?xi32>
32// CHECK:           scf.for %[[VAL_13:.*]] = %[[VAL_5]] to %[[VAL_11]] step %[[VAL_4]] {
33// CHECK:             %[[VAL_14:.*]] = memref.load %[[VAL_1]]{{\[}}%[[VAL_13]]] : memref<?xi64>
34// CHECK:             %[[VAL_15:.*]] = arith.trunci %[[VAL_14]] : i64 to i32
35// CHECK:             memref.store %[[VAL_15]], %[[VAL_12]]{{\[}}%[[VAL_13]]] : memref<?xi32>
36// CHECK:           }
37// CHECK:           %[[VAL_16:.*]] = memref.dim %[[VAL_2]], %[[VAL_5]] : memref<?xf32>
38// CHECK:           %[[VAL_17:.*]] = memref.alloc(%[[VAL_16]]) : memref<?xf32>
39// CHECK:           memref.copy %[[VAL_2]], %[[VAL_17]] : memref<?xf32> to memref<?xf32>
40// CHECK:           return %[[VAL_7]], %[[VAL_12]], %[[VAL_17]], %[[VAL_3]] : memref<?xi32>, memref<?xi32>, memref<?xf32>, !sparse_tensor.storage_specifier
41// CHECK:         }
42func.func @sparse_convert(%arg0: tensor<?xf32, #SparseVector64>) -> tensor<?xf32, #SparseVector32> {
43  %0 = sparse_tensor.convert %arg0 : tensor<?xf32, #SparseVector64> to tensor<?xf32, #SparseVector32>
44  return %0 : tensor<?xf32, #SparseVector32>
45}
46
47// CHECK-LABEL:   func.func @sparse_convert_value(
48// CHECK-SAME:      %[[VAL_0:.*0]]: memref<?xi32>,
49// CHECK-SAME:      %[[VAL_1:.*1]]: memref<?xi32>,
50// CHECK-SAME:      %[[VAL_2:.*2]]: memref<?xf32>,
51// CHECK-SAME:      %[[VAL_3:.*]]: !sparse_tensor.storage_specifier
52// CHECK-DAG:       %[[VAL_4:.*]] = arith.constant 1 : index
53// CHECK-DAG:       %[[VAL_5:.*]] = arith.constant 0 : index
54// CHECK:           %[[VAL_6:.*]] = memref.dim %[[VAL_0]], %[[VAL_5]] : memref<?xi32>
55// CHECK:           %[[VAL_7:.*]] = memref.alloc(%[[VAL_6]]) : memref<?xi32>
56// CHECK:           memref.copy %[[VAL_0]], %[[VAL_7]] : memref<?xi32> to memref<?xi32>
57// CHECK:           %[[VAL_8:.*]] = memref.dim %[[VAL_1]], %[[VAL_5]] : memref<?xi32>
58// CHECK:           %[[VAL_9:.*]] = memref.alloc(%[[VAL_8]]) : memref<?xi32>
59// CHECK:           memref.copy %[[VAL_1]], %[[VAL_9]] : memref<?xi32> to memref<?xi32>
60// CHECK:           %[[VAL_10:.*]] = memref.dim %[[VAL_2]], %[[VAL_5]] : memref<?xf32>
61// CHECK:           %[[VAL_11:.*]] = memref.alloc(%[[VAL_10]]) : memref<?xf64>
62// CHECK:           scf.for %[[VAL_12:.*]] = %[[VAL_5]] to %[[VAL_10]] step %[[VAL_4]] {
63// CHECK:             %[[VAL_13:.*]] = memref.load %[[VAL_2]]{{\[}}%[[VAL_12]]] : memref<?xf32>
64// CHECK:             %[[VAL_14:.*]] = arith.extf %[[VAL_13]] : f32 to f64
65// CHECK:             memref.store %[[VAL_14]], %[[VAL_11]]{{\[}}%[[VAL_12]]] : memref<?xf64>
66// CHECK:           }
67// CHECK:           return %[[VAL_7]], %[[VAL_9]], %[[VAL_11]], %[[VAL_3]] : memref<?xi32>, memref<?xi32>, memref<?xf64>, !sparse_tensor.storage_specifier
68// CHECK:         }
69func.func @sparse_convert_value(%arg0: tensor<?xf32, #SparseVector32>) -> tensor<?xf64, #SparseVector32> {
70  %0 = sparse_tensor.convert %arg0 : tensor<?xf32, #SparseVector32> to tensor<?xf64, #SparseVector32>
71  return %0 : tensor<?xf64, #SparseVector32>
72}
73