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
|
// RUN: mlir-opt %s --sparse-tensor-conversion --canonicalize --cse | FileCheck %s
// RUN: mlir-opt %s --post-sparsification-rewrite="enable-runtime-library=false enable-foreach=false" \
// RUN: --canonicalize --cse | FileCheck %s --check-prefix=CHECK-RWT
#SparseVector = #sparse_tensor.encoding<{
lvlTypes = ["compressed"]
}>
#SparseMatrix = #sparse_tensor.encoding<{
lvlTypes = ["dense", "compressed"]
}>
#SparseTensor = #sparse_tensor.encoding<{
lvlTypes = ["dense", "compressed", "compressed"],
dimOrdering = affine_map<(i,j,k) -> (k,i,j)>
}>
// CHECK-LABEL: func @sparse_convert_1d(
// CHECK-SAME: %[[Arg:.*]]: !llvm.ptr<i8>) -> tensor<13xi32>
// CHECK-DAG: %[[I0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[I13:.*]] = arith.constant 13 : index
// CHECK-DAG: %[[DenseDLT:.*]] = arith.constant 4 : i8
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : i32
// CHECK-DAG: %[[C6:.*]] = arith.constant 6 : i32
//
// CHECK-DAG: %[[LvlTypes:.*]] = memref.alloca() : memref<1xi8>
// CHECK-DAG: %[[LvlTypesP:.*]] = memref.cast %[[LvlTypes]] : memref<1xi8> to memref<?xi8>
// CHECK-DAG: memref.store %[[DenseDLT]], %[[LvlTypes]][%[[I0]]] : memref<1xi8>
// CHECK-DAG: %[[DimSizes:.*]] = memref.alloca() : memref<1xindex>
// CHECK-DAG: %[[DimSizesP:.*]] = memref.cast %[[DimSizes]] : memref<1xindex> to memref<?xindex>
// CHECK-DAG: memref.store %[[I13]], %[[DimSizes]][%[[I0]]] : memref<1xindex>
// CHECK-DAG: %[[LvlSizes:.*]] = memref.alloca() : memref<1xindex>
// CHECK-DAG: %[[LvlSizesP:.*]] = memref.cast %[[LvlSizes]] : memref<1xindex> to memref<?xindex>
// CHECK-DAG: %[[Iota:.*]] = memref.alloca() : memref<1xindex>
// CHECK-DAG: %[[IotaP:.*]] = memref.cast %[[Iota]] : memref<1xindex> to memref<?xindex>
// CHECK-DAG: memref.store %[[I0]], %[[Iota]][%[[I0]]] : memref<1xindex>
// CHECK: %[[Iter:.*]] = call @newSparseTensor(%[[DimSizesP]], %[[LvlSizesP]], %[[LvlTypesP]], %[[IotaP]], %[[IotaP]], %[[C0]], %[[C0]], %[[C6]], %[[C6]], %[[Arg]])
//
// CHECK-DAG: %[[IndS:.*]] = memref.alloca() : memref<1xindex>
// CHECK-DAG: %[[IndD:.*]] = memref.cast %[[IndS]] : memref<1xindex> to memref<?xindex>
// CHECK-DAG: %[[ElemBuffer:.*]] = memref.alloca() : memref<i32>
// CHECK-DAG: %[[M:.*]] = memref.alloc() : memref<13xi32>
// CHECK-DAG: linalg.fill ins(%[[C0]] : i32) outs(%[[M]] : memref<13xi32>)
// CHECK: scf.while : () -> () {
// CHECK: %[[Cond:.*]] = func.call @getNextI32(%[[Iter]], %[[IndD]], %[[ElemBuffer]]) : (!llvm.ptr<i8>, memref<?xindex>, memref<i32>) -> i1
// CHECK: scf.condition(%[[Cond]])
// CHECK: } do {
// CHECK: %[[Iv0:.*]] = memref.load %[[IndS]][%[[I0]]] : memref<1xindex>
// CHECK: %[[ElemVal:.*]] = memref.load %[[ElemBuffer]][] : memref<i32>
// CHECK: memref.store %[[ElemVal]], %[[M]][%[[Iv0]]] : memref<13xi32>
// CHECK: scf.yield
// CHECK: }
// CHECK: %[[T:.*]] = bufferization.to_tensor %[[M]] : memref<13xi32>
// CHECK: return %[[T]] : tensor<13xi32>
func.func @sparse_convert_1d(%arg0: tensor<13xi32, #SparseVector>) -> tensor<13xi32> {
%0 = sparse_tensor.convert %arg0 : tensor<13xi32, #SparseVector> to tensor<13xi32>
return %0 : tensor<13xi32>
}
// CHECK-LABEL: func @sparse_convert_1d_dyn(
// CHECK-SAME: %[[Arg:.*]]: !llvm.ptr<i8>) -> tensor<?xi32>
// CHECK-DAG: %[[I0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[DenseDLT:.*]] = arith.constant 4 : i8
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : i32
// CHECK-DAG: %[[C6:.*]] = arith.constant 6 : i32
//
// CHECK-DAG: %[[LvlTypes:.*]] = memref.alloca() : memref<1xi8>
// CHECK-DAG: %[[LvlTypesP:.*]] = memref.cast %[[LvlTypes]] : memref<1xi8> to memref<?xi8>
// CHECK-DAG: memref.store %[[DenseDLT]], %[[LvlTypes]][%[[I0]]] : memref<1xi8>
// CHECK-DAG: %[[DimSizes:.*]] = memref.alloca() : memref<1xindex>
// CHECK-DAG: %[[DimSizesP:.*]] = memref.cast %[[DimSizes]] : memref<1xindex> to memref<?xindex>
// CHECK-DAG: %[[SizeI0:.*]] = call @sparseDimSize(%[[Arg]], %[[I0]]) : (!llvm.ptr<i8>, index) -> index
// CHECK-DAG: memref.store %[[SizeI0]], %[[DimSizes]][%[[I0]]] : memref<1xindex>
// CHECK-DAG: %[[LvlSizes:.*]] = memref.alloca() : memref<1xindex>
// CHECK-DAG: %[[LvlSizesP:.*]] = memref.cast %[[LvlSizes]] : memref<1xindex> to memref<?xindex>
// CHECK-DAG: %[[Iota:.*]] = memref.alloca() : memref<1xindex>
// CHECK-DAG: %[[IotaP:.*]] = memref.cast %[[Iota]] : memref<1xindex> to memref<?xindex>
// CHECK-DAG: memref.store %[[I0]], %[[Iota]][%[[I0]]] : memref<1xindex>
// CHECK: %[[Iter:.*]] = call @newSparseTensor(%[[DimSizesP]], %[[LvlSizesP]], %[[LvlTypesP]], %[[IotaP]], %[[IotaP]], %[[C0]], %[[C0]], %[[C6]], %[[C6]], %[[Arg]])
//
// CHECK-DAG: %[[IndS:.*]] = memref.alloca() : memref<1xindex>
// CHECK-DAG: %[[IndD:.*]] = memref.cast %[[IndS]] : memref<1xindex> to memref<?xindex>
// CHECK-DAG: %[[ElemBuffer:.*]] = memref.alloca() : memref<i32>
// CHECK-DAG: %[[M:.*]] = memref.alloc(%[[SizeI0]]) : memref<?xi32>
// CHECK-DAG: linalg.fill ins(%[[C0]] : i32) outs(%[[M]] : memref<?xi32>)
// CHECK: scf.while : () -> () {
// CHECK: %[[Cond:.*]] = func.call @getNextI32(%[[Iter]], %[[IndD]], %[[ElemBuffer]]) : (!llvm.ptr<i8>, memref<?xindex>, memref<i32>) -> i1
// CHECK: scf.condition(%[[Cond]])
// CHECK: } do {
// CHECK: %[[Iv0:.*]] = memref.load %[[IndS]][%[[I0]]] : memref<1xindex>
// CHECK: %[[ElemVal:.*]] = memref.load %[[ElemBuffer]][] : memref<i32>
// CHECK: memref.store %[[ElemVal]], %[[M]][%[[Iv0]]] : memref<?xi32>
// CHECK: scf.yield
// CHECK: }
// CHECK: %[[T:.*]] = bufferization.to_tensor %[[M]] : memref<?xi32>
// CHECK: return %[[T]] : tensor<?xi32>
func.func @sparse_convert_1d_dyn(%arg0: tensor<?xi32, #SparseVector>) -> tensor<?xi32> {
%0 = sparse_tensor.convert %arg0 : tensor<?xi32, #SparseVector> to tensor<?xi32>
return %0 : tensor<?xi32>
}
// CHECK-LABEL: func @sparse_convert_2d(
// CHECK-SAME: %[[Arg:.*]]: !llvm.ptr<i8>) -> tensor<2x4xf64>
// CHECK-DAG: %[[I0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[I1:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[I2:.*]] = arith.constant 2 : index
// CHECK-DAG: %[[I4:.*]] = arith.constant 4 : index
// CHECK-DAG: %[[DenseDLT:.*]] = arith.constant 4 : i8
// CHECK-DAG: %[[ActionToIter:.*]] = arith.constant 6 : i32
// CHECK-DAG: %[[E0:.*]] = arith.constant 0.000000e+00 : f64
//
// CHECK-DAG: %[[LvlTypes:.*]] = memref.alloca() : memref<2xi8>
// CHECK-DAG: %[[LvlTypesP:.*]] = memref.cast %[[LvlTypes]] : memref<2xi8> to memref<?xi8>
// CHECK-DAG: memref.store %[[DenseDLT]], %[[LvlTypes]][%[[I0]]] : memref<2xi8>
// CHECK-DAG: memref.store %[[DenseDLT]], %[[LvlTypes]][%[[I1]]] : memref<2xi8>
// CHECK-DAG: %[[DimSizes:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[DimSizesP:.*]] = memref.cast %[[DimSizes]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: memref.store %[[I2]], %[[DimSizes]][%[[I0]]] : memref<2xindex>
// CHECK-DAG: memref.store %[[I4]], %[[DimSizes]][%[[I1]]] : memref<2xindex>
// CHECK-DAG: %[[LvlSizes:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[LvlSizesP:.*]] = memref.cast %[[LvlSizes]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: %[[Iota:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[IotaP:.*]] = memref.cast %[[Iota]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: memref.store %[[I0]], %[[Iota]][%[[I0]]] : memref<2xindex>
// CHECK-DAG: memref.store %[[I1]], %[[Iota]][%[[I1]]] : memref<2xindex>
// CHECK: %[[Iter:.*]] = call @newSparseTensor(%[[DimSizesP]], %[[LvlSizesP]], %[[LvlTypesP]], %[[IotaP]], %[[IotaP]], %{{.*}}, %{{.*}}, %{{.*}}, %[[ActionToIter]], %[[Arg]])
//
// CHECK-DAG: %[[IndS:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[IndD:.*]] = memref.cast %[[IndS]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: %[[ElemBuffer:.*]] = memref.alloca() : memref<f64>
// CHECK-DAG: %[[M:.*]] = memref.alloc() : memref<2x4xf64>
// CHECK-DAG: linalg.fill ins(%[[E0]] : f64) outs(%[[M]] : memref<2x4xf64>)
// CHECK: scf.while : () -> () {
// CHECK: %[[Cond:.*]] = func.call @getNextF64(%[[Iter]], %[[IndD]], %[[ElemBuffer]]) : (!llvm.ptr<i8>, memref<?xindex>, memref<f64>) -> i1
// CHECK: scf.condition(%[[Cond]])
// CHECK: } do {
// CHECK: %[[Iv0:.*]] = memref.load %[[IndS]][%[[I0]]] : memref<2xindex>
// CHECK: %[[Iv1:.*]] = memref.load %[[IndS]][%[[I1]]] : memref<2xindex>
// CHECK: %[[ElemVal:.*]] = memref.load %[[ElemBuffer]][] : memref<f64>
// CHECK: memref.store %[[ElemVal]], %[[M]][%[[Iv0]], %[[Iv1]]] : memref<2x4xf64>
// CHECK: scf.yield
// CHECK: }
// CHECK: %[[T:.*]] = bufferization.to_tensor %[[M]] : memref<2x4xf64>
// CHECK: return %[[T]] : tensor<2x4xf64>
// CHECK-RWT-LABEL: func.func @sparse_convert_2d(
// CHECK-RWT-SAME: %[[A:.*]]: tensor<2x4xf64, #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>>) -> tensor<2x4xf64> {
// CHECK-RWT: %[[F0:.*]] = arith.constant 0.000000e+00 : f64
// CHECK-RWT: %[[B:.*]] = memref.alloc() : memref<2x4xf64>
// CHECK-RWT: linalg.fill ins(%[[F0]] : f64) outs(%[[B]]
// CHECK-RWT: sparse_tensor.foreach in %[[A]]
// CHECK-RWT: ^bb0(%[[FI0:.*]]: index, %[[FI1:.*]]: index, %[[FV:.*]]: f64):
// CHECK-RWT: memref.store %[[FV]], %[[B]]{{\[}}%[[FI0]], %[[FI1]]]
// CHECK-RWT: }
// CHECK-RWT: %[[T:.*]] = bufferization.to_tensor %[[B]]
// CHECK-RWT: return %[[T]] : tensor<2x4xf64>
func.func @sparse_convert_2d(%arg0: tensor<2x4xf64, #SparseMatrix>) -> tensor<2x4xf64> {
%0 = sparse_tensor.convert %arg0 : tensor<2x4xf64, #SparseMatrix> to tensor<2x4xf64>
return %0 : tensor<2x4xf64>
}
// CHECK-LABEL: func @sparse_convert_2d_dyn0(
// CHECK-SAME: %[[Arg:.*]]: !llvm.ptr<i8>) -> tensor<?x4xf64>
// CHECK-DAG: %[[I0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[I1:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[I4:.*]] = arith.constant 4 : index
// CHECK-DAG: %[[DenseDLT:.*]] = arith.constant 4 : i8
// CHECK-DAG: %[[ActionToIter:.*]] = arith.constant 6 : i32
// CHECK-DAG: %[[E0:.*]] = arith.constant 0.000000e+00 : f64
//
// CHECK-DAG: %[[LvlTypes:.*]] = memref.alloca() : memref<2xi8>
// CHECK-DAG: %[[LvlTypesP:.*]] = memref.cast %[[LvlTypes]] : memref<2xi8> to memref<?xi8>
// CHECK-DAG: memref.store %[[DenseDLT]], %[[LvlTypes]][%[[I0]]] : memref<2xi8>
// CHECK-DAG: memref.store %[[DenseDLT]], %[[LvlTypes]][%[[I1]]] : memref<2xi8>
// CHECK-DAG: %[[DimSizes:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[DimSizesP:.*]] = memref.cast %[[DimSizes]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: %[[SizeI0:.*]] = call @sparseDimSize(%[[Arg]], %[[I0]]) : (!llvm.ptr<i8>, index) -> index
// CHECK-DAG: memref.store %[[SizeI0]], %[[DimSizes]][%[[I0]]] : memref<2xindex>
// CHECK-DAG: memref.store %[[I4]], %[[DimSizes]][%[[I1]]] : memref<2xindex>
// CHECK-DAG: %[[LvlSizes:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[LvlSizesP:.*]] = memref.cast %[[LvlSizes]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: %[[Iota:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[IotaP:.*]] = memref.cast %[[Iota]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: memref.store %[[I0]], %[[Iota]][%[[I0]]] : memref<2xindex>
// CHECK-DAG: memref.store %[[I1]], %[[Iota]][%[[I1]]] : memref<2xindex>
// CHECK: %[[Iter:.*]] = call @newSparseTensor(%[[DimSizesP]], %[[LvlSizesP]], %[[LvlTypesP]], %[[IotaP]], %[[IotaP]], %{{.*}}, %{{.*}}, %{{.*}}, %[[ActionToIter]], %[[Arg]])
//
// CHECK-DAG: %[[IndS:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[IndD:.*]] = memref.cast %[[IndS]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: %[[ElemBuffer:.*]] = memref.alloca() : memref<f64>
// CHECK-DAG: %[[M:.*]] = memref.alloc(%[[SizeI0]]) : memref<?x4xf64>
// CHECK-DAG: linalg.fill ins(%[[E0]] : f64) outs(%[[M]] : memref<?x4xf64>)
// CHECK: scf.while : () -> () {
// CHECK: %[[Cond:.*]] = func.call @getNextF64(%[[Iter]], %[[IndD]], %[[ElemBuffer]]) : (!llvm.ptr<i8>, memref<?xindex>, memref<f64>) -> i1
// CHECK: scf.condition(%[[Cond]])
// CHECK: } do {
// CHECK: %[[Iv0:.*]] = memref.load %[[IndS]][%[[I0]]] : memref<2xindex>
// CHECK: %[[Iv1:.*]] = memref.load %[[IndS]][%[[I1]]] : memref<2xindex>
// CHECK: %[[ElemVal:.*]] = memref.load %[[ElemBuffer]][] : memref<f64>
// CHECK: memref.store %[[ElemVal]], %[[M]][%[[Iv0]], %[[Iv1]]] : memref<?x4xf64>
// CHECK: scf.yield
// CHECK: }
// CHECK: %[[T:.*]] = bufferization.to_tensor %[[M]] : memref<?x4xf64>
// CHECK: return %[[T]] : tensor<?x4xf64>
func.func @sparse_convert_2d_dyn0(%arg0: tensor<?x4xf64, #SparseMatrix>) -> tensor<?x4xf64> {
%0 = sparse_tensor.convert %arg0 : tensor<?x4xf64, #SparseMatrix> to tensor<?x4xf64>
return %0 : tensor<?x4xf64>
}
// CHECK-LABEL: func @sparse_convert_2d_dyn1(
// CHECK-SAME: %[[Arg:.*]]: !llvm.ptr<i8>) -> tensor<2x?xf64>
// CHECK-DAG: %[[I0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[I1:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[I2:.*]] = arith.constant 2 : index
// CHECK-DAG: %[[DenseDLT:.*]] = arith.constant 4 : i8
// CHECK-DAG: %[[ActionToIter:.*]] = arith.constant 6 : i32
// CHECK-DAG: %[[E0:.*]] = arith.constant 0.000000e+00 : f64
//
// CHECK-DAG: %[[LvlTypes:.*]] = memref.alloca() : memref<2xi8>
// CHECK-DAG: %[[LvlTypesP:.*]] = memref.cast %[[LvlTypes]] : memref<2xi8> to memref<?xi8>
// CHECK-DAG: memref.store %[[DenseDLT]], %[[LvlTypes]][%[[I0]]] : memref<2xi8>
// CHECK-DAG: memref.store %[[DenseDLT]], %[[LvlTypes]][%[[I1]]] : memref<2xi8>
// CHECK-DAG: %[[DimSizes:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[DimSizesP:.*]] = memref.cast %[[DimSizes]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: %[[SizeI1:.*]] = call @sparseDimSize(%[[Arg]], %[[I1]]) : (!llvm.ptr<i8>, index) -> index
// CHECK-DAG: memref.store %[[I2]], %[[DimSizes]][%[[I0]]] : memref<2xindex>
// CHECK-DAG: memref.store %[[SizeI1]], %[[DimSizes]][%[[I1]]] : memref<2xindex>
// CHECK-DAG: %[[LvlSizes:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[LvlSizesP:.*]] = memref.cast %[[LvlSizes]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: %[[Iota:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[IotaP:.*]] = memref.cast %[[Iota]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: memref.store %[[I0]], %[[Iota]][%[[I0]]] : memref<2xindex>
// CHECK-DAG: memref.store %[[I1]], %[[Iota]][%[[I1]]] : memref<2xindex>
// CHECK: %[[Iter:.*]] = call @newSparseTensor(%[[DimSizesP]], %[[LvlSizesP]], %[[LvlTypesP]], %[[IotaP]], %[[IotaP]], %{{.*}}, %{{.*}}, %{{.*}}, %[[ActionToIter]], %[[Arg]])
//
// CHECK-DAG: %[[IndS:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[IndD:.*]] = memref.cast %[[IndS]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: %[[ElemBuffer:.*]] = memref.alloca() : memref<f64>
// CHECK-DAG: %[[M:.*]] = memref.alloc(%[[SizeI1]]) : memref<2x?xf64>
// CHECK-DAG: linalg.fill ins(%[[E0]] : f64) outs(%[[M]] : memref<2x?xf64>)
// CHECK: scf.while : () -> () {
// CHECK: %[[Cond:.*]] = func.call @getNextF64(%[[Iter]], %[[IndD]], %[[ElemBuffer]]) : (!llvm.ptr<i8>, memref<?xindex>, memref<f64>) -> i1
// CHECK: scf.condition(%[[Cond]])
// CHECK: } do {
// CHECK: %[[Iv0:.*]] = memref.load %[[IndS]][%[[I0]]] : memref<2xindex>
// CHECK: %[[Iv1:.*]] = memref.load %[[IndS]][%[[I1]]] : memref<2xindex>
// CHECK: %[[ElemVal:.*]] = memref.load %[[ElemBuffer]][] : memref<f64>
// CHECK: memref.store %[[ElemVal]], %[[M]][%[[Iv0]], %[[Iv1]]] : memref<2x?xf64>
// CHECK: scf.yield
// CHECK: }
// CHECK: %[[T:.*]] = bufferization.to_tensor %[[M]] : memref<2x?xf64>
// CHECK: return %[[T]] : tensor<2x?xf64>
func.func @sparse_convert_2d_dyn1(%arg0: tensor<2x?xf64, #SparseMatrix>) -> tensor<2x?xf64> {
%0 = sparse_tensor.convert %arg0 : tensor<2x?xf64, #SparseMatrix> to tensor<2x?xf64>
return %0 : tensor<2x?xf64>
}
// CHECK-LABEL: func @sparse_convert_2d_dyn2(
// CHECK-SAME: %[[Arg:.*]]: !llvm.ptr<i8>) -> tensor<?x?xf64>
// CHECK-DAG: %[[I0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[I1:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[DenseDLT:.*]] = arith.constant 4 : i8
// CHECK-DAG: %[[ActionToIter:.*]] = arith.constant 6 : i32
// CHECK-DAG: %[[E0:.*]] = arith.constant 0.000000e+00 : f64
//
// CHECK-DAG: %[[LvlTypes:.*]] = memref.alloca() : memref<2xi8>
// CHECK-DAG: %[[LvlTypesP:.*]] = memref.cast %[[LvlTypes]] : memref<2xi8> to memref<?xi8>
// CHECK-DAG: memref.store %[[DenseDLT]], %[[LvlTypes]][%[[I0]]] : memref<2xi8>
// CHECK-DAG: memref.store %[[DenseDLT]], %[[LvlTypes]][%[[I1]]] : memref<2xi8>
// CHECK-DAG: %[[DimSizes:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[DimSizesP:.*]] = memref.cast %[[DimSizes]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: %[[SizeI0:.*]] = call @sparseDimSize(%[[Arg]], %[[I0]]) : (!llvm.ptr<i8>, index) -> index
// CHECK-DAG: %[[SizeI1:.*]] = call @sparseDimSize(%[[Arg]], %[[I1]]) : (!llvm.ptr<i8>, index) -> index
// CHECK-DAG: memref.store %[[SizeI0]], %[[DimSizes]][%[[I0]]] : memref<2xindex>
// CHECK-DAG: memref.store %[[SizeI1]], %[[DimSizes]][%[[I1]]] : memref<2xindex>
// CHECK-DAG: %[[LvlSizes:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[LvlSizesP:.*]] = memref.cast %[[LvlSizes]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: %[[Iota:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[IotaP:.*]] = memref.cast %[[Iota]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: memref.store %[[I0]], %[[Iota]][%[[I0]]] : memref<2xindex>
// CHECK-DAG: memref.store %[[I1]], %[[Iota]][%[[I1]]] : memref<2xindex>
// CHECK: %[[Iter:.*]] = call @newSparseTensor(%[[DimSizesP]], %[[LvlSizesP]], %[[LvlTypesP]], %[[IotaP]], %[[IotaP]], %{{.*}}, %{{.*}}, %{{.*}}, %[[ActionToIter]], %[[Arg]])
//
// CHECK-DAG: %[[IndS:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[IndD:.*]] = memref.cast %[[IndS]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: %[[ElemBuffer:.*]] = memref.alloca() : memref<f64>
// CHECK-DAG: %[[M:.*]] = memref.alloc(%[[SizeI0]], %[[SizeI1]]) : memref<?x?xf64>
// CHECK-DAG: linalg.fill ins(%[[E0]] : f64) outs(%[[M]] : memref<?x?xf64>)
// CHECK: scf.while : () -> () {
// CHECK: %[[Cond:.*]] = func.call @getNextF64(%[[Iter]], %[[IndD]], %[[ElemBuffer]]) : (!llvm.ptr<i8>, memref<?xindex>, memref<f64>) -> i1
// CHECK: scf.condition(%[[Cond]])
// CHECK: } do {
// CHECK: %[[Iv0:.*]] = memref.load %[[IndS]][%[[I0]]] : memref<2xindex>
// CHECK: %[[Iv1:.*]] = memref.load %[[IndS]][%[[I1]]] : memref<2xindex>
// CHECK: %[[ElemVal:.*]] = memref.load %[[ElemBuffer]][] : memref<f64>
// CHECK: memref.store %[[ElemVal]], %[[M]][%[[Iv0]], %[[Iv1]]] : memref<?x?xf64>
// CHECK: scf.yield
// CHECK: }
// CHECK: %[[T:.*]] = bufferization.to_tensor %[[M]] : memref<?x?xf64>
// CHECK: return %[[T]] : tensor<?x?xf64>
// CHECK-RWT-LABEL: func.func @sparse_convert_2d_dyn2(
// CHECK-RWT-SAME: %[[A:.*]]: tensor<?x?xf64, #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>>) -> tensor<?x?xf64> {
// CHECK-RWT-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-RWT-DAG: %[[C1:.*]] = arith.constant 1 : index
// CHECK-RWT-DAG: %[[F0:.*]] = arith.constant 0.000000e+00 : f64
// CHECK-RWT: %[[D0:.*]] = tensor.dim %[[A]], %[[C0]]
// CHECK-RWT: %[[D1:.*]] = tensor.dim %[[A]], %[[C1]]
// CHECK-RWT: %[[B:.*]] = memref.alloc(%[[D0]], %[[D1]])
// CHECK-RWT: linalg.fill ins(%[[F0]] : f64) outs(%[[B]]
// CHECK-RWT: sparse_tensor.foreach in %[[A]]
// CHECK-RWT: ^bb0(%[[FI0:.*]]: index, %[[FI1:.*]]: index, %[[FV:.*]]: f64):
// CHECK-RWT: memref.store %[[FV]], %[[B]]{{\[}}%[[FI0]], %[[FI1]]]
// CHECK-RWT: }
// CHECK-RWT: %[[T:.*]] = bufferization.to_tensor %[[B]]
// CHECK-RWT: return %[[T]] : tensor<?x?xf64>
func.func @sparse_convert_2d_dyn2(%arg0: tensor<?x?xf64, #SparseMatrix>) -> tensor<?x?xf64> {
%0 = sparse_tensor.convert %arg0 : tensor<?x?xf64, #SparseMatrix> to tensor<?x?xf64>
return %0 : tensor<?x?xf64>
}
// CHECK-LABEL: func @sparse_convert_3d(
// CHECK-SAME: %[[Arg:.*]]: !llvm.ptr<i8>) -> tensor<2x3x4xf64>
// CHECK-DAG: %[[I0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[I1:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[I2:.*]] = arith.constant 2 : index
// CHECK-DAG: %[[I3:.*]] = arith.constant 3 : index
// CHECK-DAG: %[[I4:.*]] = arith.constant 4 : index
// CHECK-DAG: %[[DenseDLT:.*]] = arith.constant 4 : i8
// CHECK-DAG: %[[ActionToIter:.*]] = arith.constant 6 : i32
// CHECK-DAG: %[[E0:.*]] = arith.constant 0.000000e+00 : f64
//
// CHECK-DAG: %[[LvlTypes:.*]] = memref.alloca() : memref<3xi8>
// CHECK-DAG: %[[LvlTypesP:.*]] = memref.cast %[[LvlTypes]] : memref<3xi8> to memref<?xi8>
// CHECK-DAG: memref.store %[[DenseDLT]], %[[LvlTypes]][%[[I0]]] : memref<3xi8>
// CHECK-DAG: memref.store %[[DenseDLT]], %[[LvlTypes]][%[[I1]]] : memref<3xi8>
// CHECK-DAG: memref.store %[[DenseDLT]], %[[LvlTypes]][%[[I2]]] : memref<3xi8>
// CHECK-DAG: %[[DimSizes:.*]] = memref.alloca() : memref<3xindex>
// CHECK-DAG: %[[DimSizesP:.*]] = memref.cast %[[DimSizes]] : memref<3xindex> to memref<?xindex>
// CHECK-DAG: memref.store %[[I2]], %[[DimSizes]][%[[I0]]] : memref<3xindex>
// CHECK-DAG: memref.store %[[I3]], %[[DimSizes]][%[[I1]]] : memref<3xindex>
// CHECK-DAG: memref.store %[[I4]], %[[DimSizes]][%[[I2]]] : memref<3xindex>
// CHECK-DAG: %[[LvlSizes:.*]] = memref.alloca() : memref<3xindex>
// CHECK-DAG: %[[LvlSizesP:.*]] = memref.cast %[[LvlSizes]] : memref<3xindex> to memref<?xindex>
// CHECK-DAG: %[[Iota:.*]] = memref.alloca() : memref<3xindex>
// CHECK-DAG: %[[IotaP:.*]] = memref.cast %[[Iota]] : memref<3xindex> to memref<?xindex>
// CHECK-DAG: memref.store %[[I0]], %[[Iota]][%[[I0]]] : memref<3xindex>
// CHECK-DAG: memref.store %[[I1]], %[[Iota]][%[[I1]]] : memref<3xindex>
// CHECK-DAG: memref.store %[[I2]], %[[Iota]][%[[I2]]] : memref<3xindex>
// CHECK: %[[Iter:.*]] = call @newSparseTensor(%[[DimSizesP]], %[[LvlSizesP]], %[[LvlTypesP]], %[[IotaP]], %[[IotaP]], %{{.*}}, %{{.*}}, %{{.*}}, %[[ActionToIter]], %[[Arg]])
//
// CHECK-DAG: %[[IndS:.*]] = memref.alloca() : memref<3xindex>
// CHECK-DAG: %[[IndD:.*]] = memref.cast %[[IndS]] : memref<3xindex> to memref<?xindex>
// CHECK-DAG: %[[ElemBuffer:.*]] = memref.alloca() : memref<f64>
// CHECK-DAG: %[[M:.*]] = memref.alloc() : memref<2x3x4xf64>
// CHECK-DAG: linalg.fill ins(%[[E0]] : f64) outs(%[[M]] : memref<2x3x4xf64>)
// CHECK: scf.while : () -> () {
// CHECK: %[[Cond:.*]] = func.call @getNextF64(%[[Iter]], %[[IndD]], %[[ElemBuffer]]) : (!llvm.ptr<i8>, memref<?xindex>, memref<f64>) -> i1
// CHECK: scf.condition(%[[Cond]])
// CHECK: } do {
// CHECK: %[[Iv0:.*]] = memref.load %[[IndS]][%[[I0]]] : memref<3xindex>
// CHECK: %[[Iv1:.*]] = memref.load %[[IndS]][%[[I1]]] : memref<3xindex>
// CHECK: %[[Iv2:.*]] = memref.load %[[IndS]][%[[I2]]] : memref<3xindex>
// CHECK: %[[ElemVal:.*]] = memref.load %[[ElemBuffer]][] : memref<f64>
// CHECK: memref.store %[[ElemVal]], %[[M]][%[[Iv0]], %[[Iv1]], %[[Iv2]]] : memref<2x3x4xf64>
// CHECK: scf.yield
// CHECK: }
// CHECK: %[[T:.*]] = bufferization.to_tensor %[[M]] : memref<2x3x4xf64>
// CHECK: return %[[T]] : tensor<2x3x4xf64>
func.func @sparse_convert_3d(%arg0: tensor<2x3x4xf64, #SparseTensor>) -> tensor<2x3x4xf64> {
%0 = sparse_tensor.convert %arg0 : tensor<2x3x4xf64, #SparseTensor> to tensor<2x3x4xf64>
return %0 : tensor<2x3x4xf64>
}
|
