Lines Matching refs:linalg
7 // DISABLED: mlir-opt %s --convert-linalg-to-llvm -o=/dev/null 2>&1
10 %0 = linalg.range %arg0:%arg1:%arg2 : !linalg.range
14 // CHECK-NEXT: linalg.range %{{.*}} : %{{.*}} : %{{.*}} : !linalg.range
24 %2 = linalg.range %arg0:%arg1:%arg2 : !linalg.range
26 %4 = linalg.slice %3[%2, %2] :
28 !linalg.range,
29 !linalg.range,
31 %5 = linalg.slice %3[%2, %arg2] : memref<?x?xf32>,
32 !linalg.range,
35 %6 = linalg.slice %3[%arg2, %2] : memref<?x?xf32>,
37 !linalg.range,
39 %7 = linalg.slice %3[%arg2, %arg3] : memref<?x?xf32>,
53 // CHECK-NEXT: linalg.slice %{{.*}}[%{{.*}}, %{{.*}}] :
55 // CHECK-SAME: !linalg.range,
56 // CHECK-SAME: !linalg.range,
58 // CHECK-NEXT: linalg.slice %{{.*}}[%{{.*}}, %{{.*}}] :
60 // CHECK-SAME: !linalg.range,
63 // CHECK-NEXT: linalg.slice %{{.*}}[%{{.*}}, %{{.*}}] :
66 // CHECK-SAME: !linalg.range,
68 // CHECK-NEXT: linalg.slice %{{.*}}[%{{.*}}, %{{.*}}] :
86 linalg.matmul ins(%arg0, %arg0 : memref<?x?xf32, offset: ?, strides: [?, 1]>,
89 linalg.matvec ins(%arg0, %arg1: memref<?x?xf32, offset: ?, strides: [?, 1]>,
92 linalg.dot ins(%arg1, %arg2: memref<?xf32, offset: ?, strides: [1]>,
98 // CHECK: linalg.matmul
102 // CHECK: linalg.matvec
106 // CHECK: linalg.dot
116 linalg.fill(%arg0, %arg1) : memref<?xf32, offset: ?, strides: [1]>, f32
121 // CHECK: linalg.fill(%{{.*}}, %{{.*}}) : memref<?xf32, #[[$strided1D]]>, f32
141 linalg.fill(%arg0, %arg1) : memref<?x?x?xf32, offset: ?, strides: [?, ?, 1]>, f32
146 // CHECK: linalg.fill(%{{.*}}, %{{.*}}) : memref<?x?x?xf32, #[[$strided3D]]>, f32
154 linalg.copy(%arg0, %arg1) : memref<?xf32, offset: ?, strides: [1]>,
159 // CHECK: linalg.copy(%{{.*}}, %{{.*}}) :
170 linalg.copy(%arg0, %arg1) {inputPermutation = affine_map<(i, j, k) -> (i, k, j)>,
177 // CHECK: linalg.copy(%{{.*}}, %{{.*}}) {
190 linalg.conv(%arg0, %arg1, %arg2) : memref<?x?x?xf32, offset: ?, strides: [?, ?, 1]>,
196 // CHECK: linalg.conv(%{{.*}}, %{{.*}}, %{{.*}}) :
208 linalg.conv(%arg0, %arg1, %arg2) {dilations = [4, 4, 5, 5], strides = [2, 2, 3, 3]} :
215 // CHECK: linalg.conv(%{{.*}}, %{{.*}}, %{{.*}}) {
226 linalg.conv(%arg0, %arg1, %arg2) {dilations = [1, 1],
234 // CHECK: linalg.conv(%{{.*}}, %{{.*}}, %{{.*}}) {
248 linalg.pooling_max(%arg0, %arg1, %arg2) {strides = [2, 1, 2]}:
253 // CHECK: linalg.pooling_max(%{{.*}}, %{{.*}}, %{{.*}})
262 linalg.pooling_min(%arg0, %arg1, %arg2) {strides = [2, 1, 2]}:
267 // CHECK: linalg.pooling_min(%{{.*}}, %{{.*}}, %{{.*}})
276 linalg.pooling_sum(%arg0, %arg1, %arg2) {strides = [2, 1, 2]}:
281 // CHECK: linalg.pooling_sum(%{{.*}}, %{{.*}}, %{{.*}})
303 linalg.generic #trait
309 linalg.yield %f0 : f32
314 // CHECK: linalg.generic {
324 linalg.generic #trait
330 linalg.yield %f0 : f32
335 // CHECK: linalg.generic {
346 linalg.generic {indexing_maps = [#map0],
351 linalg.yield %cst : f32
357 // CHECK: linalg.generic
377 %0 = linalg.generic #trait2
382 linalg.yield %f0 : f32
387 // CHECK: linalg.generic {
412 %0 = linalg.indexed_generic #trait2
417 linalg.yield %f0 : f32
422 // CHECK: linalg.indexed_generic {
445 %0 = linalg.generic #trait_broadcast
448 linalg.yield %a : f32
455 %0 = linalg.indexed_generic #trait_broadcast
458 linalg.yield %a : f32
481 linalg.generic #trait3
486 linalg.yield %b : f32
491 // CHECK: linalg.generic {
499 // CHECK: linalg.yield %{{.*}} : f32
503 linalg.indexed_generic #trait3
508 linalg.yield %b : f32
513 // CHECK: linalg.indexed_generic {
521 // CHECK: linalg.yield %{{.*}} : f32
537 %0 = linalg.reshape %arg0 [affine_map<(i, j, k) -> (i, j)>,
540 %r0 = linalg.reshape %0 [affine_map<(i, j, k) -> (i, j)>,
543 %1 = linalg.reshape %arg0 [affine_map<(i, j, k) -> (i)>,
546 %r1 = linalg.reshape %1 [affine_map<(i, j, k) -> (i)>,
549 %2 = linalg.reshape %arg0 [affine_map<(i, j, k) -> (i, j, k)>] :
551 %r2 = linalg.reshape %2 [affine_map<(i, j, k) -> (i, j, k)>] :
554 %3 = linalg.reshape %arg0 [affine_map<(i, j, k, l, m) -> (i, j)>,
558 %r3 = linalg.reshape %3 [affine_map<(i, j, k, l, m) -> (i, j)>,
563 %t0 = linalg.tensor_reshape %arg1 [affine_map<(i, j, k, l, m) -> (i, j)>,
567 %rt0 = linalg.tensor_reshape %t0 [affine_map<(i, j, k, l, m) -> (i, j)>,
571 %t1 = linalg.tensor_reshape %arg2 [affine_map<(i, j, k, l, m) -> (i, j)>,
575 %rt1 = linalg.tensor_reshape %t1 [affine_map<(i, j, k, l, m) -> (i)>,
582 // CHECK: linalg.reshape {{.*}} [#[[$reshapeD01]], #[[$reshapeD2]]]
584 // CHECK: linalg.reshape {{.*}} [#[[$reshapeD01]], #[[$reshapeD2]]]
586 // CHECK: linalg.reshape {{.*}} [#[[$reshapeD0]], #[[$reshapeD12]]]
588 // CHECK: linalg.reshape {{.*}} [#[[$reshapeD0]], #[[$reshapeD12]]]
590 // CHECK: linalg.reshape {{.*}} [#[[$reshapeD012]]]
592 // CHECK: linalg.reshape {{.*}} [#[[$reshapeD012]]]
594 // CHECK: linalg.reshape {{.*}} [#[[$reshape5D01]], #[[$reshape5D2]], #[[$reshape5D34]]]
596 // CHECK: linalg.reshape {{.*}} [#[[$reshape5D01]], #[[$reshape5D2]], #[[$reshape5D34]]]
599 // CHECK: linalg.tensor_reshape {{.*}}: tensor<3x4x5xf32> into tensor<1x3x4x1x5xf32>
600 // CHECK: linalg.tensor_reshape {{.*}}: tensor<1x3x4x1x5xf32> into tensor<3x4x5xf32>
601 // CHECK: linalg.tensor_reshape {{.*}}: tensor<3x?x5xf32> into tensor<1x3x?x1x5xf32>
602 // CHECK: linalg.tensor_reshape {{.*}}: tensor<1x3x?x1x5xf32> into tensor<1x?x5xf32>
614 %0 = linalg.reshape %arg0 [affine_map<(i, j, k) -> (i, j)>,
617 %r0 = linalg.reshape %0 [affine_map<(i, j, k) -> (i, j)>,
620 %1 = linalg.reshape %arg1 [affine_map<(i, j, k) -> (i, j)>,
624 %r1 = linalg.reshape %1 [affine_map<(i, j, k) -> (i, j)>,
628 %2 = linalg.reshape %arg2 [affine_map<(i, j, k) -> (i, j)>,
632 %r2 = linalg.reshape %2 [affine_map<(i, j, k) -> (i, j)>,
643 // CHECK: linalg.reshape {{.*}} [#[[$reshapeD01]], #[[$reshapeD2]]]
645 // CHECK: linalg.reshape {{.*}} [#[[$reshapeD01]], #[[$reshapeD2]]]
647 // CHECK: linalg.reshape {{.*}} [#[[$reshapeD01]], #[[$reshapeD2]]]
649 // CHECK: linalg.reshape {{.*}} [#[[$reshapeD01]], #[[$reshapeD2]]]
651 // CHECK: linalg.reshape {{.*}} [#[[$reshapeD01]], #[[$reshapeD2]]]
653 // CHECK: linalg.reshape {{.*}} [#[[$reshapeD01]], #[[$reshapeD2]]]
660 linalg.batch_matmul ins(%a3, %b3: memref<?x?x?xf32>, memref<?x?x?xf32>)
662 linalg.batch_matmul ins(%ta3, %tb3: tensor<?x?x?xf32>, tensor<?x?x?xf32>)
664 %res1 = linalg.batch_matmul ins(%ta3, %tb3: tensor<?x?x?xf32>, tensor<?x?x?xf32>)
667 %res2 = linalg.batch_matmul ins(%ta3, %b3: tensor<?x?x?xf32>, memref<?x?x?xf32>)
673 // CHECK: linalg.batch_matmul
674 // CHECK: linalg.batch_matmul
675 // CHECK: linalg.batch_matmul
676 // CHECK: linalg.batch_matmul
682 %0 = linalg.tensor_reshape %arg0 [] : tensor<1x1xf32> into tensor<f32>
683 %1 = linalg.tensor_reshape %0 [] : tensor<f32> into tensor<1x1xf32>
687 // CHECK: linalg.tensor_reshape %{{.*}} [] : tensor<1x1xf32> into tensor<f32>
688 // CHECK: linalg.tensor_reshape %{{.*}} [] : tensor<f32> into tensor<1x1xf32>
694 %0 = linalg.reshape %arg0 [] : memref<1x1xf32> into memref<f32>
695 %1 = linalg.reshape %0 [] : memref<f32> into memref<1x1xf32>
699 // CHECK: linalg.reshape %{{.*}} [] : memref<1x1xf32> into memref<f32>
700 // CHECK: linalg.reshape %{{.*}} [] : memref<f32> into memref<1x1xf32>