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
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
|
// RUN: mlir-opt %s --sparse-tensor-conversion --canonicalize --cse | FileCheck %s
#SparseVector = #sparse_tensor.encoding<{
lvlTypes = ["compressed"]
}>
#SparseVector64 = #sparse_tensor.encoding<{
lvlTypes = ["compressed"],
posWidth = 64,
crdWidth = 64
}>
#SparseVector32 = #sparse_tensor.encoding<{
lvlTypes = ["compressed"],
posWidth = 32,
crdWidth = 32
}>
#CSR = #sparse_tensor.encoding<{
lvlTypes = ["dense", "compressed"]
}>
#CSC = #sparse_tensor.encoding<{
lvlTypes = ["dense", "compressed"],
dimToLvl = affine_map<(i,j) -> (j,i)>
}>
#SparseTensor = #sparse_tensor.encoding<{
lvlTypes = ["dense", "compressed", "compressed"],
dimToLvl = affine_map<(i,j,k) -> (k,i,j)>
}>
// CHECK-LABEL: func @sparse_nop(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> !llvm.ptr<i8>
// CHECK: return %[[A]] : !llvm.ptr<i8>
func.func @sparse_nop(%arg0: tensor<?xf64, #SparseVector>) -> tensor<?xf64, #SparseVector> {
return %arg0 : tensor<?xf64, #SparseVector>
}
// CHECK-LABEL: func @sparse_dim1d(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: %[[C:.*]] = arith.constant 0 : index
// CHECK: %[[D:.*]] = call @sparseDimSize(%[[A]], %[[C]])
// CHECK: return %[[D]] : index
func.func @sparse_dim1d(%arg0: tensor<?xf64, #SparseVector>) -> index {
%c = arith.constant 0 : index
%0 = tensor.dim %arg0, %c : tensor<?xf64, #SparseVector>
return %0 : index
}
// Querying the size of dimension 1 should do so; i.e., it should
// not be permuted into a query for the size of level 2 (even though
// dimension 1 is stored as level 2).
// CHECK-LABEL: func @sparse_dim3d(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: %[[C:.*]] = arith.constant 1 : index
// CHECK: %[[D:.*]] = call @sparseDimSize(%[[A]], %[[C]])
// CHECK: return %[[D]] : index
func.func @sparse_dim3d(%arg0: tensor<?x?x?xf64, #SparseTensor>) -> index {
%c = arith.constant 1 : index
%0 = tensor.dim %arg0, %c : tensor<?x?x?xf64, #SparseTensor>
return %0 : index
}
// Querying the size of a static dimension should be folded into a
// constant (and we should be sure to get the size of dimension 1,
// not dimension 2 nor level 1).
// CHECK-LABEL: func @sparse_dim3d_const(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: %[[C:.*]] = arith.constant 20 : index
// CHECK: return %[[C]] : index
func.func @sparse_dim3d_const(%arg0: tensor<10x20x30xf64, #SparseTensor>) -> index {
%c = arith.constant 1 : index
%0 = tensor.dim %arg0, %c : tensor<10x20x30xf64, #SparseTensor>
return %0 : index
}
// CHECK-LABEL: func @sparse_new1d(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> !llvm.ptr<i8>
// CHECK-DAG: %[[DimShape0:.*]] = memref.alloca() : memref<1xindex>
// CHECK-DAG: %[[DimShape:.*]] = memref.cast %[[DimShape0]] : memref<1xindex> to memref<?xindex>
// CHECK: %[[Reader:.*]] = call @createCheckedSparseTensorReader(%[[A]], %[[DimShape]], %{{.*}})
// CHECK-DAG: %[[Iota0:.*]] = memref.alloca() : memref<1xindex>
// CHECK-DAG: %[[Iota:.*]] = memref.cast %[[Iota0]] : memref<1xindex> to memref<?xindex>
// CHECK-DAG: %[[LvlTypes0:.*]] = memref.alloca() : memref<1xi8>
// CHECK-DAG: %[[LvlTypes:.*]] = memref.cast %[[LvlTypes0]] : memref<1xi8> to memref<?xi8>
// CHECK: %[[T:.*]] = call @newSparseTensorFromReader(%[[Reader]], %[[DimShape]], %[[LvlTypes]], %[[Iota]], %[[Iota]], %{{.*}}, %{{.*}}, %{{.*}})
// CHECK: call @delSparseTensorReader(%[[Reader]])
// CHECK: return %[[T]] : !llvm.ptr<i8>
func.func @sparse_new1d(%arg0: !llvm.ptr<i8>) -> tensor<128xf64, #SparseVector> {
%0 = sparse_tensor.new %arg0 : !llvm.ptr<i8> to tensor<128xf64, #SparseVector>
return %0 : tensor<128xf64, #SparseVector>
}
// CHECK-LABEL: func @sparse_new2d(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> !llvm.ptr<i8>
// CHECK-DAG: %[[DimShape0:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[DimShape:.*]] = memref.cast %[[DimShape0]] : memref<2xindex> to memref<?xindex>
// CHECK: %[[Reader:.*]] = call @createCheckedSparseTensorReader(%[[A]], %[[DimShape]], %{{.*}})
// CHECK: %[[DimSizes:.*]] = call @getSparseTensorReaderDimSizes(%[[Reader]])
// CHECK-DAG: %[[Iota0:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[Iota:.*]] = memref.cast %[[Iota0]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: %[[LvlTypes0:.*]] = memref.alloca() : memref<2xi8>
// CHECK-DAG: %[[LvlTypes:.*]] = memref.cast %[[LvlTypes0]] : memref<2xi8> to memref<?xi8>
// CHECK: %[[T:.*]] = call @newSparseTensorFromReader(%[[Reader]], %[[DimSizes]], %[[LvlTypes]], %[[Iota]], %[[Iota]], %{{.*}}, %{{.*}}, %{{.*}})
// CHECK: call @delSparseTensorReader(%[[Reader]])
// CHECK: return %[[T]] : !llvm.ptr<i8>
func.func @sparse_new2d(%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 @sparse_new3d(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> !llvm.ptr<i8>
// CHECK-DAG: %[[DimShape0:.*]] = memref.alloca() : memref<3xindex>
// CHECK-DAG: %[[DimShape:.*]] = memref.cast %[[DimShape0]] : memref<3xindex> to memref<?xindex>
// CHECK: %[[Reader:.*]] = call @createCheckedSparseTensorReader(%[[A]], %[[DimShape]], %{{.*}})
// CHECK: %[[DimSizes:.*]] = call @getSparseTensorReaderDimSizes(%[[Reader]])
// CHECK-DAG: %[[LvlSizes0:.*]] = memref.alloca() : memref<3xindex>
// CHECK-DAG: %[[LvlSizes:.*]] = memref.cast %[[LvlSizes0]] : memref<3xindex> to memref<?xindex>
// CHECK-DAG: %[[Lvl2Dim0:.*]] = memref.alloca() : memref<3xindex>
// CHECK-DAG: %[[Lvl2Dim:.*]] = memref.cast %[[Lvl2Dim0]] : memref<3xindex> to memref<?xindex>
// CHECK-DAG: %[[Dim2Lvl0:.*]] = memref.alloca() : memref<3xindex>
// CHECK-DAG: %[[Dim2Lvl:.*]] = memref.cast %[[Dim2Lvl0]] : memref<3xindex> to memref<?xindex>
// CHECK-DAG: %[[LvlTypes0:.*]] = memref.alloca() : memref<3xi8>
// CHECK-DAG: %[[LvlTypes:.*]] = memref.cast %[[LvlTypes0]] : memref<3xi8> to memref<?xi8>
// CHECK: %[[T:.*]] = call @newSparseTensorFromReader(%[[Reader]], %[[LvlSizes]], %[[LvlTypes]], %[[Lvl2Dim]], %[[Dim2Lvl]], %{{.*}}, %{{.*}}, %{{.*}})
// CHECK: call @delSparseTensorReader(%[[Reader]])
// CHECK: return %[[T]] : !llvm.ptr<i8>
func.func @sparse_new3d(%arg0: !llvm.ptr<i8>) -> tensor<?x?x?xf32, #SparseTensor> {
%0 = sparse_tensor.new %arg0 : !llvm.ptr<i8> to tensor<?x?x?xf32, #SparseTensor>
return %0 : tensor<?x?x?xf32, #SparseTensor>
}
// CHECK-LABEL: func @sparse_init(
// CHECK-SAME: %[[I:.*]]: index,
// CHECK-SAME: %[[J:.*]]: index) -> !llvm.ptr<i8>
// CHECK-DAG: %[[Empty:.*]] = arith.constant 0 : i32
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[DimSizes0:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[LvlSizes0:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[LvlTypes0:.*]] = memref.alloca() : memref<2xi8>
// CHECK-DAG: %[[Iota0:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[DimSizes:.*]] = memref.cast %[[DimSizes0]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: %[[LvlSizes:.*]] = memref.cast %[[LvlSizes0]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: %[[LvlTypes:.*]] = memref.cast %[[LvlTypes0]] : memref<2xi8> to memref<?xi8>
// CHECK-DAG: %[[Iota:.*]] = memref.cast %[[Iota0]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: memref.store %[[I]], %[[DimSizes0]][%[[C0]]] : memref<2xindex>
// CHECK-DAG: memref.store %[[J]], %[[DimSizes0]][%[[C1]]] : memref<2xindex>
// CHECK: %[[NP:.*]] = llvm.mlir.null : !llvm.ptr<i8>
// CHECK: %[[T:.*]] = call @newSparseTensor(%[[DimSizes]], %[[LvlSizes]], %[[LvlTypes]], %[[Iota]], %[[Iota]], %{{.*}}, %{{.*}}, %{{.*}}, %[[Empty]], %[[NP]])
// CHECK: return %[[T]] : !llvm.ptr<i8>
func.func @sparse_init(%arg0: index, %arg1: index) -> tensor<?x?xf64, #CSR> {
%0 = bufferization.alloc_tensor(%arg0, %arg1) : tensor<?x?xf64, #CSR>
%1 = sparse_tensor.load %0 : tensor<?x?xf64, #CSR>
return %1 : tensor<?x?xf64, #CSR>
}
// CHECK-LABEL: func @sparse_release(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: call @delSparseTensor(%[[A]]) : (!llvm.ptr<i8>) -> ()
// CHECK: return
func.func @sparse_release(%arg0: tensor<128xf64, #SparseVector>) {
bufferization.dealloc_tensor %arg0 : tensor<128xf64, #SparseVector>
return
}
// CHECK-LABEL: func @sparse_nop_cast(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> !llvm.ptr<i8>
// CHECK: return %[[A]] : !llvm.ptr<i8>
func.func @sparse_nop_cast(%arg0: tensor<64xf32, #SparseVector>) -> tensor<?xf32, #SparseVector> {
%0 = tensor.cast %arg0 : tensor<64xf32, #SparseVector> to tensor<?xf32, #SparseVector>
return %0 : tensor<?xf32, #SparseVector>
}
// CHECK-LABEL: func @sparse_positions(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: %[[C:.*]] = arith.constant 0 : index
// CHECK: %[[T:.*]] = call @sparsePositions0(%[[A]], %[[C]]) : (!llvm.ptr<i8>, index) -> memref<?xindex>
// CHECK: return %[[T]] : memref<?xindex>
func.func @sparse_positions(%arg0: tensor<128xf64, #SparseVector>) -> memref<?xindex> {
%0 = sparse_tensor.positions %arg0 { level = 0 : index } : tensor<128xf64, #SparseVector> to memref<?xindex>
return %0 : memref<?xindex>
}
// CHECK-LABEL: func @sparse_positions64(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: %[[C:.*]] = arith.constant 0 : index
// CHECK: %[[T:.*]] = call @sparsePositions64(%[[A]], %[[C]]) : (!llvm.ptr<i8>, index) -> memref<?xi64>
// CHECK: return %[[T]] : memref<?xi64>
func.func @sparse_positions64(%arg0: tensor<128xf64, #SparseVector64>) -> memref<?xi64> {
%0 = sparse_tensor.positions %arg0 { level = 0 : index } : tensor<128xf64, #SparseVector64> to memref<?xi64>
return %0 : memref<?xi64>
}
// CHECK-LABEL: func @sparse_positions32(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: %[[C:.*]] = arith.constant 0 : index
// CHECK: %[[T:.*]] = call @sparsePositions32(%[[A]], %[[C]]) : (!llvm.ptr<i8>, index) -> memref<?xi32>
// CHECK: return %[[T]] : memref<?xi32>
func.func @sparse_positions32(%arg0: tensor<128xf64, #SparseVector32>) -> memref<?xi32> {
%0 = sparse_tensor.positions %arg0 { level = 0 : index } : tensor<128xf64, #SparseVector32> to memref<?xi32>
return %0 : memref<?xi32>
}
// CHECK-LABEL: func @sparse_indices(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: %[[C:.*]] = arith.constant 0 : index
// CHECK: %[[T:.*]] = call @sparseCoordinates0(%[[A]], %[[C]]) : (!llvm.ptr<i8>, index) -> memref<?xindex>
// CHECK: return %[[T]] : memref<?xindex>
func.func @sparse_indices(%arg0: tensor<128xf64, #SparseVector>) -> memref<?xindex> {
%0 = sparse_tensor.coordinates %arg0 { level = 0 : index } : tensor<128xf64, #SparseVector> to memref<?xindex>
return %0 : memref<?xindex>
}
// CHECK-LABEL: func @sparse_indices64(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: %[[C:.*]] = arith.constant 0 : index
// CHECK: %[[T:.*]] = call @sparseCoordinates64(%[[A]], %[[C]]) : (!llvm.ptr<i8>, index) -> memref<?xi64>
// CHECK: return %[[T]] : memref<?xi64>
func.func @sparse_indices64(%arg0: tensor<128xf64, #SparseVector64>) -> memref<?xi64> {
%0 = sparse_tensor.coordinates %arg0 { level = 0 : index } : tensor<128xf64, #SparseVector64> to memref<?xi64>
return %0 : memref<?xi64>
}
// CHECK-LABEL: func @sparse_indices32(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: %[[C:.*]] = arith.constant 0 : index
// CHECK: %[[T:.*]] = call @sparseCoordinates32(%[[A]], %[[C]]) : (!llvm.ptr<i8>, index) -> memref<?xi32>
// CHECK: return %[[T]] : memref<?xi32>
func.func @sparse_indices32(%arg0: tensor<128xf64, #SparseVector32>) -> memref<?xi32> {
%0 = sparse_tensor.coordinates %arg0 { level = 0 : index } : tensor<128xf64, #SparseVector32> to memref<?xi32>
return %0 : memref<?xi32>
}
// CHECK-LABEL: func @sparse_valuesf64(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: %[[T:.*]] = call @sparseValuesF64(%[[A]]) : (!llvm.ptr<i8>) -> memref<?xf64>
// CHECK: return %[[T]] : memref<?xf64>
func.func @sparse_valuesf64(%arg0: tensor<128xf64, #SparseVector>) -> memref<?xf64> {
%0 = sparse_tensor.values %arg0 : tensor<128xf64, #SparseVector> to memref<?xf64>
return %0 : memref<?xf64>
}
// CHECK-LABEL: func @sparse_valuesf32(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: %[[T:.*]] = call @sparseValuesF32(%[[A]]) : (!llvm.ptr<i8>) -> memref<?xf32>
// CHECK: return %[[T]] : memref<?xf32>
func.func @sparse_valuesf32(%arg0: tensor<128xf32, #SparseVector>) -> memref<?xf32> {
%0 = sparse_tensor.values %arg0: tensor<128xf32, #SparseVector> to memref<?xf32>
return %0 : memref<?xf32>
}
// CHECK-LABEL: func @sparse_valuesi32(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: %[[T:.*]] = call @sparseValuesI32(%[[A]]) : (!llvm.ptr<i8>) -> memref<?xi32>
// CHECK: return %[[T]] : memref<?xi32>
func.func @sparse_valuesi32(%arg0: tensor<128xi32, #SparseVector>) -> memref<?xi32> {
%0 = sparse_tensor.values %arg0: tensor<128xi32, #SparseVector> to memref<?xi32>
return %0 : memref<?xi32>
}
// CHECK-LABEL: func @sparse_valuesi16(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: %[[T:.*]] = call @sparseValuesI16(%[[A]]) : (!llvm.ptr<i8>) -> memref<?xi16>
// CHECK: return %[[T]] : memref<?xi16>
func.func @sparse_valuesi16(%arg0: tensor<128xi16, #SparseVector>) -> memref<?xi16> {
%0 = sparse_tensor.values %arg0: tensor<128xi16, #SparseVector> to memref<?xi16>
return %0 : memref<?xi16>
}
// CHECK-LABEL: func @sparse_valuesi8(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: %[[T:.*]] = call @sparseValuesI8(%[[A]]) : (!llvm.ptr<i8>) -> memref<?xi8>
// CHECK: return %[[T]] : memref<?xi8>
func.func @sparse_valuesi8(%arg0: tensor<128xi8, #SparseVector>) -> memref<?xi8> {
%0 = sparse_tensor.values %arg0: tensor<128xi8, #SparseVector> to memref<?xi8>
return %0 : memref<?xi8>
}
// CHECK-LABEL: func @sparse_noe(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK-DAG: %[[C:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[T:.*]] = call @sparseValuesF64(%[[A]]) : (!llvm.ptr<i8>) -> memref<?xf64>
// CHECK: %[[NOE:.*]] = memref.dim %[[T]], %[[C]] : memref<?xf64>
// CHECK: return %[[NOE]] : index
func.func @sparse_noe(%arg0: tensor<128xf64, #SparseVector>) -> index {
%0 = sparse_tensor.number_of_entries %arg0 : tensor<128xf64, #SparseVector>
return %0 : index
}
// CHECK-LABEL: func @sparse_reconstruct(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>
// CHECK: return %[[A]] : !llvm.ptr<i8>
func.func @sparse_reconstruct(%arg0: tensor<128xf32, #SparseVector>) -> tensor<128xf32, #SparseVector> {
%0 = sparse_tensor.load %arg0 : tensor<128xf32, #SparseVector>
return %0 : tensor<128xf32, #SparseVector>
}
// CHECK-LABEL: func @sparse_reconstruct_ins(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>
// CHECK: call @endInsert(%[[A]]) : (!llvm.ptr<i8>) -> ()
// CHECK: return %[[A]] : !llvm.ptr<i8>
func.func @sparse_reconstruct_ins(%arg0: tensor<128xf32, #SparseVector>) -> tensor<128xf32, #SparseVector> {
%0 = sparse_tensor.load %arg0 hasInserts : tensor<128xf32, #SparseVector>
return %0 : tensor<128xf32, #SparseVector>
}
// CHECK-LABEL: func @sparse_insert(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>,
// CHECK-SAME: %[[B:.*]]: index,
// CHECK-SAME: %[[C:.*]]: f32) -> !llvm.ptr<i8> {
// CHECK-DAG: %[[M:.*]] = memref.alloca() : memref<1xindex>
// CHECK-DAG: %[[V:.*]] = memref.alloca() : memref<f32>
// CHECK-DAG: %[[MC:.*]] = memref.cast %[[M]] : memref<1xindex> to memref<?xindex>
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: memref.store %[[B]], %[[M]][%[[C0]]] : memref<1xindex>
// CHECK-DAG: memref.store %[[C]], %[[V]][] : memref<f32>
// CHECK: call @lexInsertF32(%[[A]], %[[MC]], %[[V]]) : (!llvm.ptr<i8>, memref<?xindex>, memref<f32>) -> ()
// CHECK: return %[[A]] : !llvm.ptr<i8>
func.func @sparse_insert(%arg0: tensor<128xf32, #SparseVector>,
%arg1: index,
%arg2: f32) -> tensor<128xf32, #SparseVector> {
%0 = sparse_tensor.insert %arg2 into %arg0[%arg1] : tensor<128xf32, #SparseVector>
return %0 : tensor<128xf32, #SparseVector>
}
// CHECK-LABEL: func @sparse_expansion1()
// CHECK: %[[N:.*]] = call @newSparseTensor
// CHECK: %[[A:.*]] = memref.alloc() : memref<8xf64>
// CHECK: %[[B:.*]] = memref.alloc() : memref<8xi1>
// CHECK: %[[C:.*]] = memref.alloc() : memref<8xindex>
// CHECK: %[[D:.*]] = memref.cast %[[C]] : memref<8xindex> to memref<?xindex>
// CHECK-DAG: linalg.fill ins(%{{.*}} : f64) outs(%[[A]] : memref<8xf64>)
// CHECK-DAG: linalg.fill ins(%{{.*}} : i1) outs(%[[B]] : memref<8xi1>)
// CHECK: return %[[D]] : memref<?xindex>
func.func @sparse_expansion1() -> memref<?xindex> {
%0 = bufferization.alloc_tensor() : tensor<4x8xf64, #CSR>
%values, %filled, %added, %count = sparse_tensor.expand %0
: tensor<4x8xf64, #CSR> to memref<?xf64>, memref<?xi1>, memref<?xindex>
return %added : memref<?xindex>
}
// CHECK-LABEL: func @sparse_expansion2()
// CHECK: %[[N:.*]] = call @newSparseTensor
// CHECK: %[[A:.*]] = memref.alloc() : memref<4xf64>
// CHECK: %[[B:.*]] = memref.alloc() : memref<4xi1>
// CHECK: %[[C:.*]] = memref.alloc() : memref<4xindex>
// CHECK: %[[D:.*]] = memref.cast %[[C]] : memref<4xindex> to memref<?xindex>
// CHECK-DAG: linalg.fill ins(%{{.*}} : f64) outs(%[[A]] : memref<4xf64>)
// CHECK-DAG: linalg.fill ins(%{{.*}} : i1) outs(%[[B]] : memref<4xi1>)
// CHECK: return %[[D]] : memref<?xindex>
func.func @sparse_expansion2() -> memref<?xindex> {
%0 = bufferization.alloc_tensor() : tensor<4x8xf64, #CSC>
%values, %filled, %added, %count = sparse_tensor.expand %0
: tensor<4x8xf64, #CSC> to memref<?xf64>, memref<?xi1>, memref<?xindex>
return %added : memref<?xindex>
}
// CHECK-LABEL: func @sparse_expansion3(
// CHECK: %[[C1:.*]] = arith.constant 1 : index
// CHECK: %[[N:.*]] = call @newSparseTensor
// CHECK: %[[S:.*]] = call @sparseLvlSize(%[[N]], %[[C1]])
// CHECK: %[[A:.*]] = memref.alloc(%[[S]]) : memref<?xf64>
// CHECK: %[[B:.*]] = memref.alloc(%[[S]]) : memref<?xi1>
// CHECK: %[[C:.*]] = memref.alloc(%[[S]]) : memref<?xindex>
// CHECK-DAG: linalg.fill ins(%{{.*}} : f64) outs(%[[A]] : memref<?xf64>)
// CHECK-DAG: linalg.fill ins(%{{.*}} : i1) outs(%[[B]] : memref<?xi1>)
// CHECK: return %[[C]] : memref<?xindex>
func.func @sparse_expansion3(%arg0: index, %arg1: index) -> memref<?xindex> {
%0 = bufferization.alloc_tensor(%arg0, %arg1) : tensor<?x?xf64, #CSC>
%values, %filled, %added, %count = sparse_tensor.expand %0
: tensor<?x?xf64, #CSC> to memref<?xf64>, memref<?xi1>, memref<?xindex>
return %added : memref<?xindex>
}
// CHECK-LABEL: func @sparse_compression(
// CHECK-SAME: %[[A:.*0]]: !llvm.ptr<i8>,
// CHECK-SAME: %[[B:.*1]]: memref<?xf64>,
// CHECK-SAME: %[[C:.*2]]: memref<?xi1>,
// CHECK-SAME: %[[D:.*3]]: memref<?xindex>,
// CHECK-SAME: %[[E:.*4]]: index,
// CHECK-SAME: %[[F:.*5]]: index) -> !llvm.ptr<i8> {
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[X:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[Y:.*]] = memref.cast %[[X]] : memref<2xindex> to memref<?xindex>
// CHECK: memref.store %[[F]], %[[X]][%[[C0]]] : memref<2xindex>
// CHECK: call @expInsertF64(%[[A]], %[[Y]], %[[B]], %[[C]], %[[D]], %[[E]])
// CHECK-DAG: memref.dealloc %[[B]] : memref<?xf64>
// CHECK-DAG: memref.dealloc %[[C]] : memref<?xi1>
// CHECK-DAG: memref.dealloc %[[D]] : memref<?xindex>
// CHECK: return %[[A]] : !llvm.ptr<i8>
func.func @sparse_compression(%tensor: tensor<8x8xf64, #CSR>,
%values: memref<?xf64>,
%filled: memref<?xi1>,
%added: memref<?xindex>,
%count: index,
%i: index) -> tensor<8x8xf64, #CSR> {
%0 = sparse_tensor.compress %values, %filled, %added, %count into %tensor[%i]
: memref<?xf64>, memref<?xi1>, memref<?xindex>, tensor<8x8xf64, #CSR>
return %0 : tensor<8x8xf64, #CSR>
}
// CHECK-LABEL: func @sparse_out1(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>,
// CHECK-SAME: %[[B:.*]]: !llvm.ptr<i8>)
// CHECK-DAG: %[[ToCOO:.*]] = arith.constant 5 : i32
// CHECK-DAG: %[[Sort:.*]] = arith.constant false
// CHECK: %[[COO:.*]] = call @newSparseTensor(%{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[ToCOO]], %[[A]])
// CHECK: call @outSparseTensorF64(%[[COO]], %[[B]], %[[Sort]]) : (!llvm.ptr<i8>, !llvm.ptr<i8>, i1) -> ()
// CHECK: call @delSparseTensorCOOF64(%[[COO]])
// CHECK: return
func.func @sparse_out1(%arg0: tensor<?x?xf64, #CSR>, %arg1: !llvm.ptr<i8>) {
sparse_tensor.out %arg0, %arg1 : tensor<?x?xf64, #CSR>, !llvm.ptr<i8>
return
}
// CHECK-LABEL: func @sparse_out2(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>,
// CHECK-SAME: %[[B:.*]]: !llvm.ptr<i8>)
// CHECK-DAG: %[[ToCOO:.*]] = arith.constant 5 : i32
// CHECK-DAG: %[[Sort:.*]] = arith.constant true
// CHECK: %[[COO:.*]] = call @newSparseTensor(%{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[ToCOO]], %[[A]])
// CHECK: call @outSparseTensorF32(%[[COO]], %[[B]], %[[Sort]]) : (!llvm.ptr<i8>, !llvm.ptr<i8>, i1) -> ()
// CHECK: call @delSparseTensorCOOF32(%[[COO]])
// CHECK: return
func.func @sparse_out2(%arg0: tensor<?x?x?xf32, #SparseTensor>, %arg1: !llvm.ptr<i8>) {
sparse_tensor.out %arg0, %arg1 : tensor<?x?x?xf32, #SparseTensor>, !llvm.ptr<i8>
return
}
// CHECK-LABEL: func @sparse_and_dense_init(
// CHECK: %[[S:.*]] = call @newSparseTensor
// CHECK: %[[D:.*]] = bufferization.alloc_tensor
// CHECK: return %[[S]], %[[D]] : !llvm.ptr<i8>, tensor<?x?xf64>
func.func @sparse_and_dense_init(%arg0: index, %arg1: index)
-> (tensor<?x?xf64, #CSR>, tensor<?x?xf64>) {
%0 = bufferization.alloc_tensor(%arg0, %arg1) : tensor<?x?xf64, #CSR>
%1 = sparse_tensor.load %0 : tensor<?x?xf64, #CSR>
%2 = bufferization.alloc_tensor(%arg0, %arg1) : tensor<?x?xf64>
return %1, %2 : tensor<?x?xf64, #CSR>, tensor<?x?xf64>
}
|
