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[mlir][armSME] Fix integration tests
These tests have been broken since: * llvm#110322 First failing buildbot: * llvm#110322
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4 files changed

+31
-11
lines changed

4 files changed

+31
-11
lines changed

mlir/test/Integration/Dialect/Linalg/CPU/ArmSME/matmul-transpose-a.mlir

Lines changed: 7 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1,5 +1,5 @@
11
// RUN: mlir-opt %s \
2-
// RUN: -transform-interpreter -test-transform-dialect-erase-schedule \
2+
// RUN: -transform-interpreter="debug-payload-root-tag=payload" -test-transform-dialect-erase-schedule \
33
// RUN: -one-shot-bufferize="bufferize-function-boundaries" \
44
// RUN: -test-lower-to-arm-sme -test-lower-to-llvm | \
55
// RUN: %mcr_aarch64_cmd \
@@ -8,6 +8,10 @@
88
// RUN: -shared-libs=%native_mlir_runner_utils,%native_mlir_c_runner_utils,%native_arm_sme_abi_shlib | \
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// RUN: FileCheck %s
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module @payload attributes { transform.target_tag = "payload" } {
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13+
func.func private @printMemrefF32(%ptr : tensor<*xf32>)
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1115
func.func @matmul_transpose_a(%A : tensor<?x?xf32>, %B : tensor<?x?xf32>, %C : tensor<?x?xf32>) {
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%res = linalg.matmul_transpose_a ins(%A, %B: tensor<?x?xf32>, tensor<?x?xf32>)
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outs(%C: tensor<?x?xf32>) -> tensor<?x?xf32>
@@ -54,6 +58,8 @@ func.func @main() {
5458
return
5559
}
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61+
} // end payload
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5763
module attributes {transform.with_named_sequence} {
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transform.named_sequence @__transform_main(%module : !transform.any_op {transform.readonly}) {
5965
%matmul_transpose_a = transform.structured.match ops{["linalg.matmul_transpose_a"]} in %module

mlir/test/Integration/Dialect/Linalg/CPU/ArmSME/matmul.mlir

Lines changed: 7 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -1,12 +1,16 @@
11
// RUN: mlir-opt %s \
2-
// RUN: -transform-interpreter -test-transform-dialect-erase-schedule \
2+
// RUN: -transform-interpreter="debug-payload-root-tag=payload" -test-transform-dialect-erase-schedule \
33
// RUN: -test-lower-to-arm-sme -test-lower-to-llvm | \
44
// RUN: %mcr_aarch64_cmd \
55
// RUN: -e=main -entry-point-result=void \
66
// RUN: -march=aarch64 -mattr="+sve,+sme" \
77
// RUN: -shared-libs=%native_mlir_runner_utils,%native_mlir_c_runner_utils,%native_arm_sme_abi_shlib | \
88
// RUN: FileCheck %s
99

10+
module @payload attributes { transform.target_tag = "payload" } {
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12+
func.func private @printMemrefF32(%ptr : tensor<*xf32>)
13+
1014
func.func @matmul(%A : tensor<?x?xf32>, %B : tensor<?x?xf32>, %C : tensor<?x?xf32>) {
1115
%res = linalg.matmul ins(%A, %B: tensor<?x?xf32>, tensor<?x?xf32>)
1216
outs(%C: tensor<?x?xf32>) -> tensor<?x?xf32>
@@ -52,6 +56,8 @@ func.func @main() {
5256
return
5357
}
5458

59+
} // end payload
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5561
module attributes {transform.with_named_sequence} {
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transform.named_sequence @__transform_main(%module : !transform.any_op {transform.consumed}) {
5763
%matmul = transform.structured.match ops{["linalg.matmul"]} in %module
@@ -101,5 +107,3 @@ module attributes {transform.with_named_sequence} {
101107
transform.yield
102108
}
103109
}
104-
105-
func.func private @printMemrefF32(%ptr : tensor<*xf32>)

mlir/test/Integration/Dialect/Linalg/CPU/ArmSME/multi-tile-matmul-mixed-types.mlir

Lines changed: 8 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -1,6 +1,6 @@
11
// RUN: mlir-opt %s \
2-
// RUN: -transform-interpreter -test-transform-dialect-erase-schedule \
3-
// RUN: -one-shot-bufferize="bufferize-function-boundaries" -canonicalize \
2+
// RUN: -transform-interpreter="debug-payload-root-tag=payload" -test-transform-dialect-erase-schedule \
3+
// RUN: -canonicalize \
44
// RUN: -test-lower-to-arm-sme -convert-vector-to-llvm="enable-arm-sve" \
55
// RUN: -test-lower-to-llvm | \
66
// RUN: %mcr_aarch64_cmd \
@@ -9,6 +9,10 @@
99
// RUN: -shared-libs=%native_mlir_runner_utils,%native_mlir_c_runner_utils,%native_arm_sme_abi_shlib,%native_mlir_arm_runner_utils | \
1010
// RUN: FileCheck %s
1111

12+
module @payload attributes { transform.target_tag = "payload" } {
13+
14+
func.func private @printMemrefF32(%ptr : tensor<*xf32>)
15+
1216
/// This is very similar to the SME multi-tile-matmul.mlir test, except that it
1317
/// tests a mixed i8 to i32 matmul and outer product fusion which fuses 16
1418
/// outer products (four per tile) into four 4-way outer products.
@@ -66,6 +70,8 @@ func.func @main() {
6670
return
6771
}
6872

73+
} // end payload
74+
6975
module attributes {transform.with_named_sequence} {
7076
transform.named_sequence @__transform_main(%module : !transform.any_op {transform.consumed}) {
7177
%matmul = transform.structured.match ops{["linalg.matmul"]} in %module

mlir/test/Integration/Dialect/Linalg/CPU/ArmSME/multi-tile-matmul.mlir

Lines changed: 9 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -1,6 +1,6 @@
11
// RUN: mlir-opt %s \
2-
// RUN: -transform-interpreter -test-transform-dialect-erase-schedule \
3-
// RUN: -one-shot-bufferize="bufferize-function-boundaries" -canonicalize \
2+
// RUN: -transform-interpreter="debug-payload-root-tag=payload" -test-transform-dialect-erase-schedule \
3+
// RUN: -canonicalize \
44
// RUN: -test-lower-to-arm-sme -convert-vector-to-llvm="enable-arm-sve" \
55
// RUN: -test-lower-to-llvm | \
66
// RUN: %mcr_aarch64_cmd \
@@ -9,6 +9,11 @@
99
// RUN: -shared-libs=%native_mlir_runner_utils,%native_mlir_c_runner_utils,%native_arm_sme_abi_shlib,%native_mlir_arm_runner_utils | \
1010
// RUN: FileCheck %s
1111

12+
module @payload attributes { transform.target_tag = "payload" } {
13+
14+
func.func private @printMemrefF32(%ptr : tensor<*xf32>)
15+
func.func private @setArmSVLBits(%bits : i32)
16+
1217
/// This is very similar to the SME matmul.mlir test, except that it uses a tile
1318
/// size of [8]x[8]xf32, which is larger than a 32-bit SME virtual tile, which
1419
/// would be [4]x[4]xf32. The [8]x[8] tile will be decomposed into four
@@ -65,6 +70,8 @@ func.func @main() {
6570
return
6671
}
6772

73+
} // end payload
74+
6875
module attributes {transform.with_named_sequence} {
6976
transform.named_sequence @__transform_main(%module : !transform.any_op {transform.consumed}) {
7077
%matmul = transform.structured.match ops{["linalg.matmul"]} in %module
@@ -107,6 +114,3 @@ module attributes {transform.with_named_sequence} {
107114
transform.yield
108115
}
109116
}
110-
111-
func.func private @printMemrefF32(%ptr : tensor<*xf32>)
112-
func.func private @setArmSVLBits(%bits : i32)

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