Lines Matching full:on
2 // RUN: FileCheck %s --check-prefix=CHECK-ON
10 // CHECK-ON-LABEL: func.func @sparse_reduction_ori(
11 // CHECK-ON-SAME: %[[VAL_0:.*]]: tensor<i13>,
12 // CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xi13, #sparse{{[0-9]*}}>) -> tensor<i13> {
13 // CHECK-ON-DAG: %[[VAL_2:.*]] = arith.constant 8 : index
14 // CHECK-ON-DAG: %[[VAL_3:.*]] = arith.constant dense<0> : vector<8xi13>
15 // CHECK-ON-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
16 // CHECK-ON-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
17 // CHECK-ON-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi13, #sparse{{[0-9]*}}> to memref<?xindex>
18 // CHECK-ON-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi13, #sparse{{[0-9]*}}> to memref<?xi13>
19 // CHECK-ON-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_0]] : tensor<i13> to memref<i13>
20 // CHECK-ON: %[[VAL_9:.*]] = memref.load %[[VAL_8]][] : memref<i13>
21 // CHECK-ON: %[[VAL_10:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex>
22 // CHECK-ON: %[[VAL_11:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_5]]] : memref<?xindex>
23 // CHECK-ON: %[[VAL_12:.*]] = vector.broadcast %[[VAL_9]] : i13 to vector<8xi13>
24 // CHECK-ON: %[[VAL_13:.*]] = scf.for %[[VAL_14:.*]] = %[[VAL_10]] to %[[VAL_11]] step %[[VAL_2]] iter_args(%[[VAL_15:.*]] = %[[VAL_12]]) -> (vector<8xi13>) {
25 // CHECK-ON: %[[VAL_16:.*]] = affine.min #map(%[[VAL_11]], %[[VAL_14]]){{\[}}%[[VAL_2]]]
26 // CHECK-ON: %[[VAL_17:.*]] = vector.create_mask %[[VAL_16]] : vector<8xi1>
27 // CHECK-ON: %[[VAL_18:.*]] = vector.maskedload %[[VAL_7]]{{\[}}%[[VAL_14]]], %[[VAL_17]], %[[VAL_3]] : memref<?xi13>, vector<8xi1>, vector<8xi13> into vector<8xi13>
28 // CHECK-ON: %[[VAL_19:.*]] = arith.ori %[[VAL_15]], %[[VAL_18]] : vector<8xi13>
29 // CHECK-ON: %[[VAL_20:.*]] = arith.select %[[VAL_17]], %[[VAL_19]], %[[VAL_15]] : vector<8xi1>, vector<8xi13>
30 // CHECK-ON: scf.yield %[[VAL_20]] : vector<8xi13>
31 // CHECK-ON: } {"Emitted from" = "linalg.generic"}
32 // CHECK-ON: %[[VAL_21:.*]] = vector.reduction <or>, %[[VAL_22:.*]] : vector<8xi13> into i13
33 // CHECK-ON: memref.store %[[VAL_21]], %[[VAL_8]][] : memref<i13>
34 // CHECK-ON: %[[VAL_23:.*]] = bufferization.to_tensor %[[VAL_8]] : memref<i13>
35 // CHECK-ON: return %[[VAL_23]] : tensor<i13>
36 // CHECK-ON: }
83 // Same test as sparse_reduction_ori except that the accumulator is on the
85 // irrespective to where the accumulator appears on commutative operations.
87 // CHECK-ON-LABEL: func.func @sparse_reduction_ori_accumulator_on_rhs(
88 // CHECK-ON-SAME: %[[VAL_0:.*]]: tensor<i13>,
89 // CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xi13, #sparse{{[0-9]*}}>) -> tensor<i13> {
90 // CHECK-ON-DAG: %[[VAL_2:.*]] = arith.constant 8 : index
91 // CHECK-ON-DAG: %[[VAL_3:.*]] = arith.constant dense<0> : vector<8xi13>
92 // CHECK-ON-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
93 // CHECK-ON-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
94 // CHECK-ON-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi13, #sparse{{[0-9]*}}> to memref<?xindex>
95 // CHECK-ON-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi13, #sparse{{[0-9]*}}> to memref<?xi13>
96 // CHECK-ON-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_0]] : tensor<i13> to memref<i13>
97 // CHECK-ON: %[[VAL_9:.*]] = memref.load %[[VAL_8]][] : memref<i13>
98 // CHECK-ON: %[[VAL_10:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex>
99 // CHECK-ON: %[[VAL_11:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_5]]] : memref<?xindex>
100 // CHECK-ON: %[[VAL_12:.*]] = vector.broadcast %[[VAL_9]] : i13 to vector<8xi13>
101 // CHECK-ON: %[[VAL_13:.*]] = scf.for %[[VAL_14:.*]] = %[[VAL_10]] to %[[VAL_11]] step %[[VAL_2]] iter_args(%[[VAL_15:.*]] = %[[VAL_12]]) -> (vector<8xi13>) {
102 // CHECK-ON: %[[VAL_16:.*]] = affine.min #map(%[[VAL_11]], %[[VAL_14]]){{\[}}%[[VAL_2]]]
103 // CHECK-ON: %[[VAL_17:.*]] = vector.create_mask %[[VAL_16]] : vector<8xi1>
104 // CHECK-ON: %[[VAL_18:.*]] = vector.maskedload %[[VAL_7]]{{\[}}%[[VAL_14]]], %[[VAL_17]], %[[VAL_3]] : memref<?xi13>, vector<8xi1>, vector<8xi13> into vector<8xi13>
105 // CHECK-ON: %[[VAL_19:.*]] = arith.ori %[[VAL_18]], %[[VAL_15]] : vector<8xi13>
106 // CHECK-ON: %[[VAL_20:.*]] = arith.select %[[VAL_17]], %[[VAL_19]], %[[VAL_15]] : vector<8xi1>, vector<8xi13>
107 // CHECK-ON: scf.yield %[[VAL_20]] : vector<8xi13>
108 // CHECK-ON: } {"Emitted from" = "linalg.generic"}
109 // CHECK-ON: %[[VAL_21:.*]] = vector.reduction <or>, %[[VAL_22:.*]] : vector<8xi13> into i13
110 // CHECK-ON: memref.store %[[VAL_21]], %[[VAL_8]][] : memref<i13>
111 // CHECK-ON: %[[VAL_23:.*]] = bufferization.to_tensor %[[VAL_8]] : memref<i13>
112 // CHECK-ON: return %[[VAL_23]] : tensor<i13>
113 // CHECK-ON: }
162 // CHECK-ON-LABEL: func.func @sparse_reduction_subi(
163 // CHECK-ON-SAME: %[[VAL_0:.*]]: tensor<i32>,
164 // CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xi32, #sparse{{[0-9]*}}>) -> tensor<i32> {
165 // CHECK-ON-DAG: %[[VAL_2:.*]] = arith.constant 8 : index
166 // CHECK-ON-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
167 // CHECK-ON-DAG: %[[VAL_4:.*]] = arith.constant dense<0> : vector<8xi32>
168 // CHECK-ON-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
169 // CHECK-ON-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
170 // CHECK-ON-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi32, #sparse{{[0-9]*}}> to memref<?xi32>
171 // CHECK-ON-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_0]] : tensor<i32> to memref<i32>
172 // CHECK-ON: %[[VAL_9:.*]] = memref.load %[[VAL_8]][] : memref<i32>
173 // CHECK-ON: %[[VAL_10:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_3]]] : memref<?xindex>
174 // CHECK-ON: %[[VAL_11:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_5]]] : memref<?xindex>
175 // CHECK-ON: %[[VAL_12:.*]] = vector.insertelement %[[VAL_9]], %[[VAL_4]]{{\[}}%[[VAL_3]] : index] : vector<8xi32>
176 // CHECK-ON: %[[VAL_13:.*]] = scf.for %[[VAL_14:.*]] = %[[VAL_10]] to %[[VAL_11]] step %[[VAL_2]] iter_args(%[[VAL_15:.*]] = %[[VAL_12]]) -> (vector<8xi32>) {
177 // CHECK-ON: %[[VAL_16:.*]] = affine.min #map(%[[VAL_11]], %[[VAL_14]]){{\[}}%[[VAL_2]]]
178 // CHECK-ON: %[[VAL_17:.*]] = vector.create_mask %[[VAL_16]] : vector<8xi1>
179 // CHECK-ON: %[[VAL_18:.*]] = vector.maskedload %[[VAL_7]]{{\[}}%[[VAL_14]]], %[[VAL_17]], %[[VAL_4]] : memref<?xi32>, vector<8xi1>, vector<8xi32> into vector<8xi32>
180 // CHECK-ON: %[[VAL_19:.*]] = arith.subi %[[VAL_15]], %[[VAL_18]] : vector<8xi32>
181 // CHECK-ON: %[[VAL_20:.*]] = arith.select %[[VAL_17]], %[[VAL_19]], %[[VAL_15]] : vector<8xi1>, vector<8xi32>
182 // CHECK-ON: scf.yield %[[VAL_20]] : vector<8xi32>
183 // CHECK-ON: } {"Emitted from" = "linalg.generic"}
184 // CHECK-ON: %[[VAL_21:.*]] = vector.reduction <add>, %[[VAL_22:.*]] : vector<8xi32> into i32
185 // CHECK-ON: memref.store %[[VAL_21]], %[[VAL_8]][] : memref<i32>
186 // CHECK-ON: %[[VAL_23:.*]] = bufferization.to_tensor %[[VAL_8]] : memref<i32>
187 // CHECK-ON: return %[[VAL_23]] : tensor<i32>
188 // CHECK-ON: }
237 // CHECK-ON-LABEL: func.func @sparse_reduction_xor(
238 // CHECK-ON-SAME: %[[VAL_0:.*]]: tensor<i32>,
239 // CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xi32, #sparse{{[0-9]*}}>) -> tensor<i32> {
240 // CHECK-ON-DAG: %[[VAL_2:.*]] = arith.constant 8 : index
241 // CHECK-ON-DAG: %[[VAL_3:.*]] = arith.constant dense<0> : vector<8xi32>
242 // CHECK-ON-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
243 // CHECK-ON-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
244 // CHECK-ON-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
245 // CHECK-ON-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi32, #sparse{{[0-9]*}}> to memref<?xi32>
246 // CHECK-ON-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_0]] : tensor<i32> to memref<i32>
247 // CHECK-ON: %[[VAL_9:.*]] = memref.load %[[VAL_8]][] : memref<i32>
248 // CHECK-ON: %[[VAL_10:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex>
249 // CHECK-ON: %[[VAL_11:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_5]]] : memref<?xindex>
250 // CHECK-ON: %[[VAL_12:.*]] = vector.insertelement %[[VAL_9]], %[[VAL_3]]{{\[}}%[[VAL_4]] : index] : vector<8xi32>
251 // CHECK-ON: %[[VAL_13:.*]] = scf.for %[[VAL_14:.*]] = %[[VAL_10]] to %[[VAL_11]] step %[[VAL_2]] iter_args(%[[VAL_15:.*]] = %[[VAL_12]]) -> (vector<8xi32>) {
252 // CHECK-ON: %[[VAL_16:.*]] = affine.min #map(%[[VAL_11]], %[[VAL_14]]){{\[}}%[[VAL_2]]]
253 // CHECK-ON: %[[VAL_17:.*]] = vector.create_mask %[[VAL_16]] : vector<8xi1>
254 // CHECK-ON: %[[VAL_18:.*]] = vector.maskedload %[[VAL_7]]{{\[}}%[[VAL_14]]], %[[VAL_17]], %[[VAL_3]] : memref<?xi32>, vector<8xi1>, vector<8xi32> into vector<8xi32>
255 // CHECK-ON: %[[VAL_19:.*]] = arith.xori %[[VAL_15]], %[[VAL_18]] : vector<8xi32>
256 // CHECK-ON: %[[VAL_20:.*]] = arith.select %[[VAL_17]], %[[VAL_19]], %[[VAL_15]] : vector<8xi1>, vector<8xi32>
257 // CHECK-ON: scf.yield %[[VAL_20]] : vector<8xi32>
258 // CHECK-ON: } {"Emitted from" = "linalg.generic"}
259 // CHECK-ON: %[[VAL_21:.*]] = vector.reduction <xor>, %[[VAL_22:.*]] : vector<8xi32> into i32
260 // CHECK-ON: memref.store %[[VAL_21]], %[[VAL_8]][] : memref<i32>
261 // CHECK-ON: %[[VAL_23:.*]] = bufferization.to_tensor %[[VAL_8]] : memref<i32>
262 // CHECK-ON: return %[[VAL_23]] : tensor<i32>
263 // CHECK-ON: }
313 // CHECK-ON-LABEL: func.func @sparse_reduction_addi(
314 // CHECK-ON-SAME: %[[VAL_0:.*]]: tensor<i32>,
315 // CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xi32, #sparse{{[0-9]*}}>) -> tensor<i32> {
316 // CHECK-ON-DAG: %[[VAL_2:.*]] = arith.constant 8 : index
317 // CHECK-ON-DAG: %[[VAL_3:.*]] = arith.constant dense<0> : vector<8xi32>
318 // CHECK-ON-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
319 // CHECK-ON-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
320 // CHECK-ON-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
321 // CHECK-ON-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi32, #sparse{{[0-9]*}}> to memref<?xi32>
322 // CHECK-ON-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_0]] : tensor<i32> to memref<i32>
323 // CHECK-ON: %[[VAL_9:.*]] = memref.load %[[VAL_8]][] : memref<i32>
324 // CHECK-ON: %[[VAL_10:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex>
325 // CHECK-ON: %[[VAL_11:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_5]]] : memref<?xindex>
326 // CHECK-ON: %[[VAL_12:.*]] = vector.insertelement %[[VAL_9]], %[[VAL_3]]{{\[}}%[[VAL_4]] : index] : vector<8xi32>
327 // CHECK-ON: %[[VAL_13:.*]] = scf.for %[[VAL_14:.*]] = %[[VAL_10]] to %[[VAL_11]] step %[[VAL_2]] iter_args(%[[VAL_15:.*]] = %[[VAL_12]]) -> (vector<8xi32>) {
328 // CHECK-ON: %[[VAL_16:.*]] = affine.min #map(%[[VAL_11]], %[[VAL_14]]){{\[}}%[[VAL_2]]]
329 // CHECK-ON: %[[VAL_17:.*]] = vector.create_mask %[[VAL_16]] : vector<8xi1>
330 // CHECK-ON: %[[VAL_18:.*]] = vector.maskedload %[[VAL_7]]{{\[}}%[[VAL_14]]], %[[VAL_17]], %[[VAL_3]] : memref<?xi32>, vector<8xi1>, vector<8xi32> into vector<8xi32>
331 // CHECK-ON: %[[VAL_19:.*]] = arith.addi %[[VAL_15]], %[[VAL_18]] : vector<8xi32>
332 // CHECK-ON: %[[VAL_20:.*]] = arith.select %[[VAL_17]], %[[VAL_19]], %[[VAL_15]] : vector<8xi1>, vector<8xi32>
333 // CHECK-ON: scf.yield %[[VAL_20]] : vector<8xi32>
334 // CHECK-ON: } {"Emitted from" = "linalg.generic"}
335 // CHECK-ON: %[[VAL_21:.*]] = vector.reduction <add>, %[[VAL_22:.*]] : vector<8xi32> into i32
336 // CHECK-ON: memref.store %[[VAL_21]], %[[VAL_8]][] : memref<i32>
337 // CHECK-ON: %[[VAL_23:.*]] = bufferization.to_tensor %[[VAL_8]] : memref<i32>
338 // CHECK-ON: return %[[VAL_23]] : tensor<i32>
339 // CHECK-ON: }
389 // CHECK-ON-LABEL: func.func @sparse_reduction_subf(
390 // CHECK-ON-SAME: %[[VAL_0:.*]]: tensor<f32>,
391 // CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xf32, #sparse{{[0-9]*}}>) -> tensor<f32> {
392 // CHECK-ON-DAG: %[[VAL_2:.*]] = arith.constant 8 : index
393 // CHECK-ON-DAG: %[[VAL_3:.*]] = arith.constant dense<0.000000e+00> : vector<8xf32>
394 // CHECK-ON-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
395 // CHECK-ON-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
396 // CHECK-ON-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
397 // CHECK-ON-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf32, #sparse{{[0-9]*}}> to memref<?xf32>
398 // CHECK-ON-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_0]] : tensor<f32> to memref<f32>
399 // CHECK-ON: %[[VAL_9:.*]] = memref.load %[[VAL_8]][] : memref<f32>
400 // CHECK-ON: %[[VAL_10:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex>
401 // CHECK-ON: %[[VAL_11:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_5]]] : memref<?xindex>
402 // CHECK-ON: %[[VAL_12:.*]] = vector.insertelement %[[VAL_9]], %[[VAL_3]]{{\[}}%[[VAL_4]] : index] : vector<8xf32>
403 // CHECK-ON: %[[VAL_13:.*]] = scf.for %[[VAL_14:.*]] = %[[VAL_10]] to %[[VAL_11]] step %[[VAL_2]] iter_args(%[[VAL_15:.*]] = %[[VAL_12]]) -> (vector<8xf32>) {
404 // CHECK-ON: %[[VAL_16:.*]] = affine.min #map(%[[VAL_11]], %[[VAL_14]]){{\[}}%[[VAL_2]]]
405 // CHECK-ON: %[[VAL_17:.*]] = vector.create_mask %[[VAL_16]] : vector<8xi1>
406 // CHECK-ON: %[[VAL_18:.*]] = vector.maskedload %[[VAL_7]]{{\[}}%[[VAL_14]]], %[[VAL_17]], %[[VAL_3]] : memref<?xf32>, vector<8xi1>, vector<8xf32> into vector<8xf32>
407 // CHECK-ON: %[[VAL_19:.*]] = arith.subf %[[VAL_15]], %[[VAL_18]] : vector<8xf32>
408 // CHECK-ON: %[[VAL_20:.*]] = arith.select %[[VAL_17]], %[[VAL_19]], %[[VAL_15]] : vector<8xi1>, vector<8xf32>
409 // CHECK-ON: scf.yield %[[VAL_20]] : vector<8xf32>
410 // CHECK-ON: } {"Emitted from" = "linalg.generic"}
411 // CHECK-ON: %[[VAL_21:.*]] = vector.reduction <add>, %[[VAL_22:.*]] : vector<8xf32> into f32
412 // CHECK-ON: memref.store %[[VAL_21]], %[[VAL_8]][] : memref<f32>
413 // CHECK-ON: %[[VAL_23:.*]] = bufferization.to_tensor %[[VAL_8]] : memref<f32>
414 // CHECK-ON: return %[[VAL_23]] : tensor<f32>
415 // CHECK-ON: }
465 // CHECK-ON-LABEL: func.func @sparse_reduction_addf(
466 // CHECK-ON-SAME: %[[VAL_0:.*]]: tensor<f32>,
467 // CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xf32, #sparse{{[0-9]*}}>) -> tensor<f32> {
468 // CHECK-ON-DAG: %[[VAL_2:.*]] = arith.constant 8 : index
469 // CHECK-ON-DAG: %[[VAL_3:.*]] = arith.constant dense<0.000000e+00> : vector<8xf32>
470 // CHECK-ON-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
471 // CHECK-ON-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
472 // CHECK-ON-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
473 // CHECK-ON-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf32, #sparse{{[0-9]*}}> to memref<?xf32>
474 // CHECK-ON-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_0]] : tensor<f32> to memref<f32>
475 // CHECK-ON: %[[VAL_9:.*]] = memref.load %[[VAL_8]][] : memref<f32>
476 // CHECK-ON: %[[VAL_10:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex>
477 // CHECK-ON: %[[VAL_11:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_5]]] : memref<?xindex>
478 // CHECK-ON: %[[VAL_12:.*]] = vector.insertelement %[[VAL_9]], %[[VAL_3]]{{\[}}%[[VAL_4]] : index] : vector<8xf32>
479 // CHECK-ON: %[[VAL_13:.*]] = scf.for %[[VAL_14:.*]] = %[[VAL_10]] to %[[VAL_11]] step %[[VAL_2]] iter_args(%[[VAL_15:.*]] = %[[VAL_12]]) -> (vector<8xf32>) {
480 // CHECK-ON: %[[VAL_16:.*]] = affine.min #map(%[[VAL_11]], %[[VAL_14]]){{\[}}%[[VAL_2]]]
481 // CHECK-ON: %[[VAL_17:.*]] = vector.create_mask %[[VAL_16]] : vector<8xi1>
482 // CHECK-ON: %[[VAL_18:.*]] = vector.maskedload %[[VAL_7]]{{\[}}%[[VAL_14]]], %[[VAL_17]], %[[VAL_3]] : memref<?xf32>, vector<8xi1>, vector<8xf32> into vector<8xf32>
483 // CHECK-ON: %[[VAL_19:.*]] = arith.addf %[[VAL_15]], %[[VAL_18]] : vector<8xf32>
484 // CHECK-ON: %[[VAL_20:.*]] = arith.select %[[VAL_17]], %[[VAL_19]], %[[VAL_15]] : vector<8xi1>, vector<8xf32>
485 // CHECK-ON: scf.yield %[[VAL_20]] : vector<8xf32>
486 // CHECK-ON: } {"Emitted from" = "linalg.generic"}
487 // CHECK-ON: %[[VAL_21:.*]] = vector.reduction <add>, %[[VAL_22:.*]] : vector<8xf32> into f32
488 // CHECK-ON: memref.store %[[VAL_21]], %[[VAL_8]][] : memref<f32>
489 // CHECK-ON: %[[VAL_23:.*]] = bufferization.to_tensor %[[VAL_8]] : memref<f32>
490 // CHECK-ON: return %[[VAL_23]] : tensor<f32>
491 // CHECK-ON: }