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[mlir][sparse] Migration to sparse_tensor.print (#83506)
Continuous efforts #83357. Previously reverted #83377.
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4 files changed

+258
-199
lines changed

4 files changed

+258
-199
lines changed

‎mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_loose.mlir

Lines changed: 9 additions & 14 deletions
Original file line numberDiff line numberDiff line change
@@ -10,7 +10,7 @@
1010
// DEFINE: %{compile} = mlir-opt %s --sparsifier="%{sparsifier_opts}"
1111
// DEFINE: %{compile_sve} = mlir-opt %s --sparsifier="%{sparsifier_opts_sve}"
1212
// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils
13-
// DEFINE: %{run_opts} = -e entry -entry-point-result=void
13+
// DEFINE: %{run_opts} = -e main -entry-point-result=void
1414
// DEFINE: %{run} = mlir-cpu-runner %{run_opts} %{run_libs}
1515
// DEFINE: %{run_sve} = %mcr_aarch64_cmd --march=aarch64 --mattr="+sve" %{run_opts} %{run_libs}
1616
//
@@ -28,7 +28,7 @@
2828
}>
2929

3030
module {
31-
func.func @entry() {
31+
func.func @main() {
3232
%c0 = arith.constant 0 : index
3333
%f0 = arith.constant 0.0 : f64
3434
%d = arith.constant dense<[[ 1.0, 2.0, 3.0, 4.0 ],
@@ -39,19 +39,14 @@ module {
3939
%s = sparse_tensor.convert %d : tensor<5x4xf64> to tensor<5x4xf64, #CSR_hi>
4040

4141
//
42-
// CHECK: ( 0, 4, 4, 8, 8, 9, 9, 13 )
43-
// CHECK-NEXT: ( 0, 1, 2, 3, 0, 1, 2, 3, 2, 0, 1, 2, 3, 0, 1, 2, 3 )
44-
// CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 5.5, 9, 10, 11, 12, 13, 14, 15, 16 )
42+
// CHECK: ---- Sparse Tensor ----
43+
// CHECK-NEXT: nse = 17
44+
// CHECK-NEXT: pos[1] : ( 0, 4, 4, 8, 8, 9, 9, 13
45+
// CHECK-NEXT: crd[1] : ( 0, 1, 2, 3, 0, 1, 2, 3, 2, 0, 1, 2, 3, 0, 1, 2, 3
46+
// CHECK-NEXT: values : ( 1, 2, 3, 4, 5, 6, 7, 8, 5.5, 9, 10, 11, 12, 13, 14, 15, 16
47+
// CHECK-NEXT: ----
4548
//
46-
%pos = sparse_tensor.positions %s {level = 1 : index } : tensor<5x4xf64, #CSR_hi> to memref<?xindex>
47-
%vecp = vector.transfer_read %pos[%c0], %c0 : memref<?xindex>, vector<8xindex>
48-
vector.print %vecp : vector<8xindex>
49-
%crd = sparse_tensor.coordinates %s {level = 1 : index } : tensor<5x4xf64, #CSR_hi> to memref<?xindex>
50-
%vecc = vector.transfer_read %crd[%c0], %c0 : memref<?xindex>, vector<17xindex>
51-
vector.print %vecc : vector<17xindex>
52-
%val = sparse_tensor.values %s : tensor<5x4xf64, #CSR_hi> to memref<?xf64>
53-
%vecv = vector.transfer_read %val[%c0], %f0 : memref<?xf64>, vector<17xf64>
54-
vector.print %vecv : vector<17xf64>
49+
sparse_tensor.print %s : tensor<5x4xf64, #CSR_hi>
5550

5651
// Release the resources.
5752
bufferization.dealloc_tensor %s: tensor<5x4xf64, #CSR_hi>

‎mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_matmul.mlir

Lines changed: 138 additions & 99 deletions
Original file line numberDiff line numberDiff line change
@@ -10,7 +10,7 @@
1010
// DEFINE: %{compile} = mlir-opt %s --sparsifier="%{sparsifier_opts}"
1111
// DEFINE: %{compile_sve} = mlir-opt %s --sparsifier="%{sparsifier_opts_sve}"
1212
// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils
13-
// DEFINE: %{run_opts} = -e entry -entry-point-result=void
13+
// DEFINE: %{run_opts} = -e main -entry-point-result=void
1414
// DEFINE: %{run} = mlir-cpu-runner %{run_opts} %{run_libs}
1515
// DEFINE: %{run_sve} = %mcr_aarch64_cmd --march=aarch64 --mattr="+sve" %{run_opts} %{run_libs}
1616
//
@@ -90,7 +90,7 @@ module {
9090
//
9191
// Main driver.
9292
//
93-
func.func @entry() {
93+
func.func @main() {
9494
%c0 = arith.constant 0 : index
9595

9696
// Initialize various matrices, dense for stress testing,
@@ -140,33 +140,94 @@ module {
140140
%b4 = sparse_tensor.convert %sb : tensor<8x4xf64> to tensor<8x4xf64, #DCSR>
141141

142142
//
143-
// Sanity check on stored entries before going into the computations.
144-
//
145-
// CHECK: 32
146-
// CHECK-NEXT: 32
147-
// CHECK-NEXT: 4
148-
// CHECK-NEXT: 4
149-
// CHECK-NEXT: 32
150-
// CHECK-NEXT: 32
151-
// CHECK-NEXT: 8
152-
// CHECK-NEXT: 8
153-
//
154-
%noea1 = sparse_tensor.number_of_entries %a1 : tensor<4x8xf64, #CSR>
155-
%noea2 = sparse_tensor.number_of_entries %a2 : tensor<4x8xf64, #DCSR>
156-
%noea3 = sparse_tensor.number_of_entries %a3 : tensor<4x8xf64, #CSR>
157-
%noea4 = sparse_tensor.number_of_entries %a4 : tensor<4x8xf64, #DCSR>
158-
%noeb1 = sparse_tensor.number_of_entries %b1 : tensor<8x4xf64, #CSR>
159-
%noeb2 = sparse_tensor.number_of_entries %b2 : tensor<8x4xf64, #DCSR>
160-
%noeb3 = sparse_tensor.number_of_entries %b3 : tensor<8x4xf64, #CSR>
161-
%noeb4 = sparse_tensor.number_of_entries %b4 : tensor<8x4xf64, #DCSR>
162-
vector.print %noea1 : index
163-
vector.print %noea2 : index
164-
vector.print %noea3 : index
165-
vector.print %noea4 : index
166-
vector.print %noeb1 : index
167-
vector.print %noeb2 : index
168-
vector.print %noeb3 : index
169-
vector.print %noeb4 : index
143+
// Sanity check before going into the computations.
144+
//
145+
// CHECK: ---- Sparse Tensor ----
146+
// CHECK-NEXT: nse = 32
147+
// CHECK-NEXT: pos[1] : ( 0, 8, 16, 24, 32
148+
// CHECK-NEXT: crd[1] : ( 0, 1, 2, 3, 4, 5, 6, 7, 0, 1, 2, 3, 4, 5, 6, 7, 0, 1, 2, 3, 4, 5, 6, 7, 0, 1, 2, 3, 4, 5, 6, 7
149+
// CHECK-NEXT: values : ( 1.1, 2.1, 3.1, 4.1, 5.1, 6.1, 7.1, 8.1, 1.2, 2.2, 3.2, 4.2, 5.2, 6.2, 7.2, 8.2, 1.3, 2.3, 3.3, 4.3, 5.3, 6.3, 7.3, 8.3, 1.4, 2.4, 3.4, 4.4, 5.4, 6.4, 7.4, 8.4
150+
// CHECK-NEXT: ----
151+
//
152+
sparse_tensor.print %a1 : tensor<4x8xf64, #CSR>
153+
154+
//
155+
// CHECK: ---- Sparse Tensor ----
156+
// CHECK-NEXT: nse = 32
157+
// CHECK-NEXT: pos[0] : ( 0, 4
158+
// CHECK-NEXT: crd[0] : ( 0, 1, 2, 3
159+
// CHECK-NEXT: pos[1] : ( 0, 8, 16, 24, 32
160+
// CHECK-NEXT: crd[1] : ( 0, 1, 2, 3, 4, 5, 6, 7, 0, 1, 2, 3, 4, 5, 6, 7, 0, 1, 2, 3, 4, 5, 6, 7, 0, 1, 2, 3, 4, 5, 6, 7
161+
// CHECK-NEXT: values : ( 1.1, 2.1, 3.1, 4.1, 5.1, 6.1, 7.1, 8.1, 1.2, 2.2, 3.2, 4.2, 5.2, 6.2, 7.2, 8.2, 1.3, 2.3, 3.3, 4.3, 5.3, 6.3, 7.3, 8.3, 1.4, 2.4, 3.4, 4.4, 5.4, 6.4, 7.4, 8.4
162+
// CHECK-NEXT: ----
163+
//
164+
sparse_tensor.print %a2 : tensor<4x8xf64, #DCSR>
165+
166+
//
167+
// CHECK: ---- Sparse Tensor ----
168+
// CHECK-NEXT: nse = 4
169+
// CHECK-NEXT: pos[1] : ( 0, 2, 2, 3, 4
170+
// CHECK-NEXT: crd[1] : ( 1, 5, 1, 7
171+
// CHECK-NEXT: values : ( 2.1, 6.1, 2.3, 1
172+
// CHECK-NEXT: ----
173+
//
174+
sparse_tensor.print %a3 : tensor<4x8xf64, #CSR>
175+
176+
//
177+
// CHECK: ---- Sparse Tensor ----
178+
// CHECK-NEXT: nse = 4
179+
// CHECK-NEXT: pos[0] : ( 0, 3
180+
// CHECK-NEXT: crd[0] : ( 0, 2, 3
181+
// CHECK-NEXT: pos[1] : ( 0, 2, 3, 4
182+
// CHECK-NEXT: crd[1] : ( 1, 5, 1, 7
183+
// CHECK-NEXT: values : ( 2.1, 6.1, 2.3, 1
184+
// CHECK-NEXT: ----
185+
//
186+
sparse_tensor.print %a4 : tensor<4x8xf64, #DCSR>
187+
188+
//
189+
// CHECK: ---- Sparse Tensor ----
190+
// CHECK-NEXT: nse = 32
191+
// CHECK-NEXT: pos[1] : ( 0, 4, 8, 12, 16, 20, 24, 28, 32
192+
// CHECK-NEXT: crd[1] : ( 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3
193+
// CHECK-NEXT: values : ( 10.1, 11.1, 12.1, 13.1, 10.2, 11.2, 12.2, 13.2, 10.3, 11.3, 12.3, 13.3, 10.4, 11.4, 12.4, 13.4, 10.5, 11.5, 12.5, 13.5, 10.6, 11.6, 12.6, 13.6, 10.7, 11.7, 12.7, 13.7, 10.8, 11.8, 12.8, 13.8
194+
// CHECK-NEXT: ----
195+
//
196+
sparse_tensor.print %b1 : tensor<8x4xf64, #CSR>
197+
198+
//
199+
// CHECK: ---- Sparse Tensor ----
200+
// CHECK-NEXT: nse = 32
201+
// CHECK-NEXT: pos[0] : ( 0, 8
202+
// CHECK-NEXT: crd[0] : ( 0, 1, 2, 3, 4, 5, 6, 7
203+
// CHECK-NEXT: pos[1] : ( 0, 4, 8, 12, 16, 20, 24, 28, 32
204+
// CHECK-NEXT: crd[1] : ( 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3
205+
// CHECK-NEXT: values : ( 10.1, 11.1, 12.1, 13.1, 10.2, 11.2, 12.2, 13.2, 10.3, 11.3, 12.3, 13.3, 10.4, 11.4, 12.4, 13.4, 10.5, 11.5, 12.5, 13.5, 10.6, 11.6, 12.6, 13.6, 10.7, 11.7, 12.7, 13.7, 10.8, 11.8, 12.8, 13.8
206+
// CHECK-NEXT: ----
207+
//
208+
sparse_tensor.print %b2 : tensor<8x4xf64, #DCSR>
209+
210+
//
211+
// CHECK: ---- Sparse Tensor ----
212+
// CHECK-NEXT: nse = 8
213+
// CHECK-NEXT: pos[1] : ( 0, 1, 2, 3, 4, 4, 5, 6, 8
214+
// CHECK-NEXT: crd[1] : ( 3, 2, 1, 0, 1, 2, 2, 3
215+
// CHECK-NEXT: values : ( 1, 2, 3, 4, 5, 6, 7, 8
216+
// CHECK-NEXT: ----
217+
//
218+
sparse_tensor.print %b3 : tensor<8x4xf64, #CSR>
219+
220+
//
221+
// CHECK: ---- Sparse Tensor ----
222+
// CHECK-NEXT: nse = 8
223+
// CHECK-NEXT: pos[0] : ( 0, 7
224+
// CHECK-NEXT: crd[0] : ( 0, 1, 2, 3, 5, 6, 7
225+
// CHECK-NEXT: pos[1] : ( 0, 1, 2, 3, 4, 5, 6, 8
226+
// CHECK-NEXT: crd[1] : ( 3, 2, 1, 0, 1, 2, 2, 3
227+
// CHECK-NEXT: values : ( 1, 2, 3, 4, 5, 6, 7, 8
228+
// CHECK-NEXT: ----
229+
//
230+
sparse_tensor.print %b4 : tensor<8x4xf64, #DCSR>
170231

171232
// Call kernels with dense.
172233
%0 = call @matmul1(%da, %db, %zero)
@@ -208,24 +269,26 @@ module {
208269
call @printMemrefF64(%u0) : (tensor<*xf64>) -> ()
209270

210271
//
211-
// CHECK: {{\[}}[388.76, 425.56, 462.36, 499.16],
212-
// CHECK-NEXT: [397.12, 434.72, 472.32, 509.92],
213-
// CHECK-NEXT: [405.48, 443.88, 482.28, 520.68],
214-
// CHECK-NEXT: [413.84, 453.04, 492.24, 531.44]]
272+
// CHECK: ---- Sparse Tensor ----
273+
// CHECK-NEXT: nse = 16
274+
// CHECK-NEXT: pos[1] : ( 0, 4, 8, 12, 16
275+
// CHECK-NEXT: crd[1] : ( 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3
276+
// CHECK-NEXT: values : ( 388.76, 425.56, 462.36, 499.16, 397.12, 434.72, 472.32, 509.92, 405.48, 443.88, 482.28, 520.68, 413.84, 453.04, 492.24, 531.44
277+
// CHECK-NEXT: ----
215278
//
216-
%c1 = sparse_tensor.convert %1 : tensor<4x4xf64, #CSR> to tensor<4x4xf64>
217-
%c1u = tensor.cast %c1 : tensor<4x4xf64> to tensor<*xf64>
218-
call @printMemrefF64(%c1u) : (tensor<*xf64>) -> ()
279+
sparse_tensor.print %1 : tensor<4x4xf64, #CSR>
219280

220281
//
221-
// CHECK: {{\[}}[388.76, 425.56, 462.36, 499.16],
222-
// CHECK-NEXT: [397.12, 434.72, 472.32, 509.92],
223-
// CHECK-NEXT: [405.48, 443.88, 482.28, 520.68],
224-
// CHECK-NEXT: [413.84, 453.04, 492.24, 531.44]]
282+
// CHECK: ---- Sparse Tensor ----
283+
// CHECK-NEXT: nse = 16
284+
// CHECK-NEXT: pos[0] : ( 0, 4
285+
// CHECK-NEXT: crd[0] : ( 0, 1, 2, 3
286+
// CHECK-NEXT: pos[1] : ( 0, 4, 8, 12, 16
287+
// CHECK-NEXT: crd[1] : ( 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3
288+
// CHECK-NEXT: values : ( 388.76, 425.56, 462.36, 499.16, 397.12, 434.72, 472.32, 509.92, 405.48, 443.88, 482.28, 520.68, 413.84, 453.04, 492.24, 531.44
289+
// CHECK-NEXT: ----
225290
//
226-
%c2 = sparse_tensor.convert %2 : tensor<4x4xf64, #DCSR> to tensor<4x4xf64>
227-
%c2u = tensor.cast %c2 : tensor<4x4xf64> to tensor<*xf64>
228-
call @printMemrefF64(%c2u) : (tensor<*xf64>) -> ()
291+
sparse_tensor.print %2 : tensor<4x4xf64, #DCSR>
229292

230293
//
231294
// CHECK: {{\[}}[86.08, 94.28, 102.48, 110.68],
@@ -237,24 +300,26 @@ module {
237300
call @printMemrefF64(%u3) : (tensor<*xf64>) -> ()
238301

239302
//
240-
// CHECK: {{\[}}[86.08, 94.28, 102.48, 110.68],
241-
// CHECK-NEXT: [0, 0, 0, 0],
242-
// CHECK-NEXT: [23.46, 25.76, 28.06, 30.36],
243-
// CHECK-NEXT: [10.8, 11.8, 12.8, 13.8]]
303+
// CHECK: ---- Sparse Tensor ----
304+
// CHECK-NEXT: nse = 12
305+
// CHECK-NEXT: pos[1] : ( 0, 4, 4, 8, 12
306+
// CHECK-NEXT: crd[1] : ( 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3
307+
// CHECK-NEXT: values : ( 86.08, 94.28, 102.48, 110.68, 23.46, 25.76, 28.06, 30.36, 10.8, 11.8, 12.8, 13.8
308+
// CHECK-NEXT: ----
244309
//
245-
%c4 = sparse_tensor.convert %4 : tensor<4x4xf64, #CSR> to tensor<4x4xf64>
246-
%c4u = tensor.cast %c4 : tensor<4x4xf64> to tensor<*xf64>
247-
call @printMemrefF64(%c4u) : (tensor<*xf64>) -> ()
310+
sparse_tensor.print %4 : tensor<4x4xf64, #CSR>
248311

249312
//
250-
// CHECK: {{\[}}[86.08, 94.28, 102.48, 110.68],
251-
// CHECK-NEXT: [0, 0, 0, 0],
252-
// CHECK-NEXT: [23.46, 25.76, 28.06, 30.36],
253-
// CHECK-NEXT: [10.8, 11.8, 12.8, 13.8]]
313+
// CHECK: ---- Sparse Tensor ----
314+
// CHECK-NEXT: nse = 12
315+
// CHECK-NEXT: pos[0] : ( 0, 3
316+
// CHECK-NEXT: crd[0] : ( 0, 2, 3
317+
// CHECK-NEXT: pos[1] : ( 0, 4, 8, 12
318+
// CHECK-NEXT: crd[1] : ( 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3
319+
// CHECK-NEXT: values : ( 86.08, 94.28, 102.48, 110.68, 23.46, 25.76, 28.06, 30.36, 10.8, 11.8, 12.8, 13.8
320+
// CHECK-NEXT: ----
254321
//
255-
%c5 = sparse_tensor.convert %5 : tensor<4x4xf64, #DCSR> to tensor<4x4xf64>
256-
%c5u = tensor.cast %c5 : tensor<4x4xf64> to tensor<*xf64>
257-
call @printMemrefF64(%c5u) : (tensor<*xf64>) -> ()
322+
sparse_tensor.print %5 : tensor<4x4xf64, #DCSR>
258323

259324
//
260325
// CHECK: {{\[}}[0, 30.5, 4.2, 0],
@@ -266,46 +331,26 @@ module {
266331
call @printMemrefF64(%u6) : (tensor<*xf64>) -> ()
267332

268333
//
269-
// CHECK: {{\[}}[0, 30.5, 4.2, 0],
270-
// CHECK-NEXT: [0, 0, 0, 0],
271-
// CHECK-NEXT: [0, 0, 4.6, 0],
272-
// CHECK-NEXT: [0, 0, 7, 8]]
334+
// CHECK: ---- Sparse Tensor ----
335+
// CHECK-NEXT: nse = 5
336+
// CHECK-NEXT: pos[1] : ( 0, 2, 2, 3, 5
337+
// CHECK-NEXT: crd[1] : ( 1, 2, 2, 2, 3
338+
// CHECK-NEXT: values : ( 30.5, 4.2, 4.6, 7, 8
339+
// CHECK-NEXT: ----
273340
//
274-
%c7 = sparse_tensor.convert %7 : tensor<4x4xf64, #CSR> to tensor<4x4xf64>
275-
%c7u = tensor.cast %c7 : tensor<4x4xf64> to tensor<*xf64>
276-
call @printMemrefF64(%c7u) : (tensor<*xf64>) -> ()
341+
sparse_tensor.print %7 : tensor<4x4xf64, #CSR>
277342

278343
//
279-
// CHECK: {{\[}}[0, 30.5, 4.2, 0],
280-
// CHECK-NEXT: [0, 0, 0, 0],
281-
// CHECK-NEXT: [0, 0, 4.6, 0],
282-
// CHECK-NEXT: [0, 0, 7, 8]]
283-
//
284-
%c8 = sparse_tensor.convert %8 : tensor<4x4xf64, #DCSR> to tensor<4x4xf64>
285-
%c8u = tensor.cast %c8 : tensor<4x4xf64> to tensor<*xf64>
286-
call @printMemrefF64(%c8u) : (tensor<*xf64>) -> ()
287-
288-
//
289-
// Sanity check on nonzeros.
290-
//
291-
// CHECK: [30.5, 4.2, 4.6, 7, 8{{.*}}]
292-
// CHECK: [30.5, 4.2, 4.6, 7, 8{{.*}}]
293-
//
294-
%val7 = sparse_tensor.values %7 : tensor<4x4xf64, #CSR> to memref<?xf64>
295-
%val8 = sparse_tensor.values %8 : tensor<4x4xf64, #DCSR> to memref<?xf64>
296-
call @printMemref1dF64(%val7) : (memref<?xf64>) -> ()
297-
call @printMemref1dF64(%val8) : (memref<?xf64>) -> ()
298-
299-
//
300-
// Sanity check on stored entries after the computations.
301-
//
302-
// CHECK-NEXT: 5
303-
// CHECK-NEXT: 5
344+
// CHECK: ---- Sparse Tensor ----
345+
// CHECK-NEXT: nse = 5
346+
// CHECK-NEXT: pos[0] : ( 0, 3
347+
// CHECK-NEXT: crd[0] : ( 0, 2, 3
348+
// CHECK-NEXT: pos[1] : ( 0, 2, 3, 5
349+
// CHECK-NEXT: crd[1] : ( 1, 2, 2, 2, 3
350+
// CHECK-NEXT: values : ( 30.5, 4.2, 4.6, 7, 8
351+
// CHECK-NEXT: ----
304352
//
305-
%noe7 = sparse_tensor.number_of_entries %7 : tensor<4x4xf64, #CSR>
306-
%noe8 = sparse_tensor.number_of_entries %8 : tensor<4x4xf64, #DCSR>
307-
vector.print %noe7 : index
308-
vector.print %noe8 : index
353+
sparse_tensor.print %8 : tensor<4x4xf64, #DCSR>
309354

310355
// Release the resources.
311356
bufferization.dealloc_tensor %a1 : tensor<4x8xf64, #CSR>
@@ -316,12 +361,6 @@ module {
316361
bufferization.dealloc_tensor %b2 : tensor<8x4xf64, #DCSR>
317362
bufferization.dealloc_tensor %b3 : tensor<8x4xf64, #CSR>
318363
bufferization.dealloc_tensor %b4 : tensor<8x4xf64, #DCSR>
319-
bufferization.dealloc_tensor %c1 : tensor<4x4xf64>
320-
bufferization.dealloc_tensor %c2 : tensor<4x4xf64>
321-
bufferization.dealloc_tensor %c4 : tensor<4x4xf64>
322-
bufferization.dealloc_tensor %c5 : tensor<4x4xf64>
323-
bufferization.dealloc_tensor %c7 : tensor<4x4xf64>
324-
bufferization.dealloc_tensor %c8 : tensor<4x4xf64>
325364
bufferization.dealloc_tensor %0 : tensor<4x4xf64>
326365
bufferization.dealloc_tensor %1 : tensor<4x4xf64, #CSR>
327366
bufferization.dealloc_tensor %2 : tensor<4x4xf64, #DCSR>

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