1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
|
// RUN: mlir-opt %s -post-sparsification-rewrite="enable-runtime-library=false enable-convert=false" | \
// RUN: FileCheck %s
#CSR = #sparse_tensor.encoding<{
lvlTypes = ["dense", "compressed"]
}>
#CSC = #sparse_tensor.encoding<{
lvlTypes = [ "dense", "compressed" ],
dimToLvl = affine_map<(i, j) -> (j, i)>
}>
#COO = #sparse_tensor.encoding<{
lvlTypes = [ "compressed-nu", "singleton" ]
}>
// CHECK-LABEL: func.func @sparse_new(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> tensor<?x?xf32, #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>> {
// CHECK: %[[COO:.*]] = sparse_tensor.new %[[A]] : !llvm.ptr<i8> to tensor<?x?xf32, #sparse_tensor.encoding<{ lvlTypes = [ "compressed-nu", "singleton" ] }>>
// CHECK: %[[R:.*]] = sparse_tensor.convert %[[COO]]
// CHECK: bufferization.dealloc_tensor %[[COO]]
// CHECK: return %[[R]]
func.func @sparse_new(%arg0: !llvm.ptr<i8>) -> tensor<?x?xf32, #CSR> {
%0 = sparse_tensor.new %arg0 : !llvm.ptr<i8> to tensor<?x?xf32, #CSR>
return %0 : tensor<?x?xf32, #CSR>
}
// CHECK-LABEL: func.func @sparse_new_csc(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> tensor<?x?xf32, #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ], dimToLvl = affine_map<(d0, d1) -> (d1, d0)> }>> {
// CHECK: %[[COO:.*]] = sparse_tensor.new %[[A]] : !llvm.ptr<i8> to tensor<?x?xf32, #sparse_tensor.encoding<{ lvlTypes = [ "compressed-nu", "singleton" ], dimToLvl = affine_map<(d0, d1) -> (d1, d0)> }>>
// CHECK: %[[R:.*]] = sparse_tensor.convert %[[COO]]
// CHECK: bufferization.dealloc_tensor %[[COO]]
// CHECK: return %[[R]]
func.func @sparse_new_csc(%arg0: !llvm.ptr<i8>) -> tensor<?x?xf32, #CSC> {
%0 = sparse_tensor.new %arg0 : !llvm.ptr<i8> to tensor<?x?xf32, #CSC>
return %0 : tensor<?x?xf32, #CSC>
}
// CHECK-LABEL: func.func @sparse_new_coo(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> tensor<?x?xf32, #sparse_tensor.encoding<{ lvlTypes = [ "compressed-nu", "singleton" ] }>> {
// CHECK: %[[COO:.*]] = sparse_tensor.new %[[A]] : !llvm.ptr<i8> to tensor<?x?xf32, #sparse_tensor.encoding<{ lvlTypes = [ "compressed-nu", "singleton" ] }>>
// CHECK: return %[[COO]]
func.func @sparse_new_coo(%arg0: !llvm.ptr<i8>) -> tensor<?x?xf32, #COO> {
%0 = sparse_tensor.new %arg0 : !llvm.ptr<i8> to tensor<?x?xf32, #COO>
return %0 : tensor<?x?xf32, #COO>
}
// CHECK-LABEL: func.func @sparse_out(
// CHECK-SAME: %[[A:.*]]: tensor<10x20xf32, #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>>,
// CHECK-SAME: %[[B:.*]]: !llvm.ptr<i8>) {
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[C2:.*]] = arith.constant 2 : index
// CHECK-DAG: %[[C10:.*]] = arith.constant 10 : index
// CHECK-DAG: %[[C20:.*]] = arith.constant 20 : index
// CHECK: %[[NNZ:.*]] = sparse_tensor.number_of_entries %[[A]]
// CHECK: %[[DS:.*]] = memref.alloca(%[[C2]]) : memref<?xindex>
// CHECK: memref.store %[[C10]], %[[DS]]{{\[}}%[[C0]]] : memref<?xindex>
// CHECK: memref.store %[[C20]], %[[DS]]{{\[}}%[[C1]]] : memref<?xindex>
// CHECK: %[[W:.*]] = call @createSparseTensorWriter(%[[B]])
// CHECK: call @outSparseTensorWriterMetaData(%[[W]], %[[C2]], %[[NNZ]], %[[DS]])
// CHECK: %[[V:.*]] = memref.alloca() : memref<f32>
// CHECK: scf.for %{{.*}} = %[[C0]] to %[[C10]] step %[[C1]] {
// CHECK: scf.for {{.*}} {
// CHECK: func.call @outSparseTensorWriterNextF32(%[[W]], %[[C2]], %[[DS]], %[[V]])
// CHECK: }
// CHECK: }
// CHECK: call @delSparseTensorWriter(%[[W]])
// CHECK: return
// CHECK: }
func.func @sparse_out( %arg0: tensor<10x20xf32, #CSR>, %arg1: !llvm.ptr<i8>) -> () {
sparse_tensor.out %arg0, %arg1 : tensor<10x20xf32, #CSR>, !llvm.ptr<i8>
return
}
|
