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Jun 14, 2024
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[mlir][test] Fix filecheck annotation typos [2/n] #93476

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b01e04e
fix filecheck test typos
May 27, 2024
23048b9
review
May 29, 2024
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8 changes: 4 additions & 4 deletions mlir/test/Analysis/test-liveness.mlir
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Expand Up @@ -40,7 +40,7 @@ func.func @func_simpleBranch(%arg0: i32, %arg1 : i32) -> i32 {
// CHECK-SAME: arg0@0 arg1@0 val_2
// CHECK: return
// CHECK-SAME: val_2
// CHECK-NEXT EndCurrentlyLive
// CHECK-NEXT:EndCurrentlyLive
%result = arith.addi %arg0, %arg1 : i32
return %result : i32
}
Expand Down Expand Up @@ -197,9 +197,9 @@ func.func @func_ranges(%cond : i1, %arg1 : i32, %arg2 : i32, %arg3 : i32) -> i32
// CHECK-NEXT: %2 = arith.addi
// CHECK-NEXT: %3 = arith.muli
// CHECK-NEXT: val_7
// CHECK-NEXT %2 = arith.addi
// CHECK-NEXT %3 = arith.muli
// CHECK-NEXT %4 = arith.muli
// CHECK-NEXT: %2 = arith.addi
// CHECK-NEXT: %3 = arith.muli
// CHECK-NEXT: %4 = arith.muli
// CHECK: val_8
// CHECK-NEXT: %3 = arith.muli
// CHECK-NEXT: %4 = arith.muli
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Conversion/GPUToNVVM/gpu-to-nvvm.mlir
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Expand Up @@ -638,7 +638,7 @@ gpu.module @test_module_30 {
}
// CHECK-LABEL: @subgroup_reduce_xor
gpu.func @subgroup_reduce_xor(%arg0 : i32) {
// CHECK nvvm.redux.sync xor {{.*}}
// CHECK: nvvm.redux.sync xor {{.*}}
%result = gpu.subgroup_reduce xor %arg0 uniform {} : (i32) -> (i32)
gpu.return
}
Expand Down
4 changes: 2 additions & 2 deletions mlir/test/Conversion/MemRefToLLVM/convert-dynamic-memref-ops.mlir
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Expand Up @@ -378,14 +378,14 @@ func.func @memref_cast_ranked_to_unranked(%arg : memref<42x2x?xf32>) {
// CHECK-DAG: %[[p:.*]] = llvm.alloca %[[c]] x !llvm.struct<(ptr, ptr, i64, array<3 x i64>, array<3 x i64>)> : (i64) -> !llvm.ptr
// CHECK-DAG: llvm.store %{{.*}}, %[[p]] : !llvm.struct<(ptr, ptr, i64, array<3 x i64>, array<3 x i64>)>, !llvm.ptr
// CHECK-DAG: %[[r:.*]] = llvm.mlir.constant(3 : index) : i64
// CHECK : llvm.mlir.undef : !llvm.struct<(i64, ptr)>
// CHECK: llvm.mlir.undef : !llvm.struct<(i64, ptr)>
// CHECK-DAG: llvm.insertvalue %[[r]], %{{.*}}[0] : !llvm.struct<(i64, ptr)>
// CHECK-DAG: llvm.insertvalue %[[p]], %{{.*}}[1] : !llvm.struct<(i64, ptr)>
// CHECK32-DAG: %[[c:.*]] = llvm.mlir.constant(1 : index) : i64
// CHECK32-DAG: %[[p:.*]] = llvm.alloca %[[c]] x !llvm.struct<(ptr, ptr, i32, array<3 x i32>, array<3 x i32>)> : (i64) -> !llvm.ptr
// CHECK32-DAG: llvm.store %{{.*}}, %[[p]] : !llvm.struct<(ptr, ptr, i32, array<3 x i32>, array<3 x i32>)>, !llvm.ptr
// CHECK32-DAG: %[[r:.*]] = llvm.mlir.constant(3 : index) : i32
// CHECK32 : llvm.mlir.undef : !llvm.struct<(i32, ptr)>
// CHECK32: llvm.mlir.undef : !llvm.struct<(i32, ptr)>
// CHECK32-DAG: llvm.insertvalue %[[r]], %{{.*}}[0] : !llvm.struct<(i32, ptr)>
// CHECK32-DAG: llvm.insertvalue %[[p]], %{{.*}}[1] : !llvm.struct<(i32, ptr)>
%0 = memref.cast %arg : memref<42x2x?xf32> to memref<*xf32>
Expand Down
10 changes: 5 additions & 5 deletions mlir/test/Conversion/NVGPUToNVVM/nvgpu-to-nvvm.mlir
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Expand Up @@ -11,7 +11,7 @@ func.func @m16n8k16_fp16(%arg0: vector<4x2xf16>, %arg1: vector<2x2xf16>, %arg2:
// CHECK: llvm.extractvalue %{{.*}}[1] : !llvm.array<2 x vector<2xf16>>
// CHECK: llvm.extractvalue %{{.*}}[0] : !llvm.array<2 x vector<2xf16>>
// CHECK: llvm.extractvalue %{{.*}}[1] : !llvm.array<2 x vector<2xf16>>
// CHECK-NOT llvm.extractvalue
// CHECK-NOT: llvm.extractvalue
// CHECK: [[d:%.+]] = nvvm.mma.sync
// CHECK-SAME: shape = #nvvm.shape<m = 16, n = 8, k = 16>
%d = nvgpu.mma.sync (%arg0, %arg1, %arg2) {mmaShape = [16, 8, 16]} : (vector<4x2xf16>, vector<2x2xf16>, vector<2x2xf16>) -> vector<2x2xf16>
Expand Down Expand Up @@ -56,7 +56,7 @@ func.func @m16n8k8_fp16(%arg0: vector<2x2xf16>, %arg1: vector<1x2xf16>, %arg2: v
// CHECK: llvm.extractvalue %{{.*}}[0] : !llvm.array<1 x vector<2xf16>>
// CHECK: llvm.extractvalue %{{.*}}[0] : !llvm.array<2 x vector<2xf16>>
// CHECK: llvm.extractvalue %{{.*}}[1] : !llvm.array<2 x vector<2xf16>>
// CHECK-NOT llvm.extractvalue
// CHECK-NOT: llvm.extractvalue
// CHECK: [[d:%.+]] = nvvm.mma.sync
// CHECK-SAME: shape = #nvvm.shape<m = 16, n = 8, k = 8>
%d = nvgpu.mma.sync (%arg0, %arg1, %arg2) {mmaShape = [16, 8, 8]} : (vector<2x2xf16>, vector<1x2xf16>, vector<2x2xf16>) -> vector<2x2xf16>
Expand Down Expand Up @@ -360,7 +360,7 @@ func.func @mma_sp_sync_f16_16832(%arg0: vector<4x2xf16>,
// CHECK: llvm.extractvalue %{{.*}}[0] : !llvm.array<2 x vector<2xf16>>
// CHECK: llvm.extractvalue %{{.*}}[1] : !llvm.array<2 x vector<2xf16>>

// CHECK-NOT llvm.extractvalue
// CHECK-NOT: llvm.extractvalue

// CHECK: %[[sparseMetadata:.+]] = llvm.bitcast %{{.+}} : vector<2xi16> to i32

Expand Down Expand Up @@ -396,7 +396,7 @@ func.func @mma_sp_sync_f16_16816(%arg0: vector<2x2xf16>,
// CHECK: llvm.extractvalue %{{.*}}[0] : !llvm.array<2 x vector<2xf16>>
// CHECK: llvm.extractvalue %{{.*}}[1] : !llvm.array<2 x vector<2xf16>>

// CHECK-NOT llvm.extractvalue
// CHECK-NOT: llvm.extractvalue

// CHECK: %[[sparseMetadata:.+]] = llvm.bitcast %{{.+}} : vector<2xi16> to i32

Expand Down Expand Up @@ -455,7 +455,7 @@ func.func @mma_sp_sync_i8_16864(%arg0: vector<4x4xi8>,
// CHECK: llvm.extractvalue %{{.*}}[{{.*}}] : !llvm.array<2 x vector<2xi32>>
// CHECK: llvm.extractvalue %{{.*}}[{{.*}}] : !llvm.array<2 x vector<2xi32>>

// CHECK-NOT llvm.extractvalue
// CHECK-NOT: llvm.extractvalue

// CHECK: %[[sparseMetadata:.+]] = llvm.bitcast %{{.+}} : vector<2xi16> to i32

Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/AMX/roundtrip.mlir
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Expand Up @@ -2,7 +2,7 @@

// CHECK-LABEL: tzero
// CHECK: amx.tile_zero : vector<16x16xbf16>
// CHECK amx.tile_store %{{.*}}[%{{.*}}, %{{.*}}], %{{.*}} : memref<?x?xbf16>, vector<16x16xbf16>
// CHECK: amx.tile_store %{{.*}}[%{{.*}}, %{{.*}}], %{{.*}} : memref<?x?xbf16>, vector<16x16xbf16>
func.func @tzero(%arg0: memref<?x?xbf16>) {
%0 = arith.constant 0 : index
%1 = amx.tile_zero : vector<16x16xbf16>
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/Affine/loop-fusion-3.mlir
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Expand Up @@ -889,7 +889,7 @@ func.func @reduce_add_non_innermost(%arg0: memref<64x64xf32, 1>, %arg1: memref<1
// CHECK: affine.for
// CHECK-NEXT: affine.for
// CHECK-NEXT: affine.for
// CHECK affine.for
// CHECK: affine.for



Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/Affine/unroll.mlir
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Expand Up @@ -616,7 +616,7 @@ func.func @loop_nest_non_trivial_multiple_upper_bound_alt(%M : index, %N : index
// UNROLL-BY-4-NEXT: "foo"
// UNROLL-BY-4-NEXT: "foo"
// UNROLL-BY-4-NEXT: "foo"
// UNROLL-BY-4-NOT for
// UNROLL-BY-4-NOT: for
// UNROLL-BY-4: return
return
}
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/ArmSME/tile-allocation-liveness.mlir
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Expand Up @@ -406,7 +406,7 @@ func.func @avoidable_spill(%a: vector<[4]xf32>, %b: vector<[4]xf32>, %c: vector<
// CHECK: arm_sme.get_tile {tile_id = 2 : i32} : vector<[4]x[4]xf32>
// CHECK: arm_sme.get_tile {tile_id = 3 : i32} : vector<[4]x[4]xf32>
// CHECK: arm_sme.move_vector_to_tile_slice {{.*}} {tile_id = 0 : i32} : vector<[4]xf32> into vector<[4]x[4]xf32>
// CHECK-NOT tile_id = 16
// CHECK-NOT: tile_id = 16
func.func @cond_branch_with_backedge(%slice: vector<[4]xf32>) {
%tileA = arm_sme.get_tile : vector<[4]x[4]xf32>
%tileB = arm_sme.get_tile : vector<[4]x[4]xf32>
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/Linalg/drop-unit-extent-dims.mlir
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Expand Up @@ -881,7 +881,7 @@ func.func @input_stays_same(%arg0 : memref<?x1x?xf32, strided<[?, 1, 1]>>, %arg1
// CHECK: func @input_stays_same(
// CHECK-SAME: %[[ARG0:.*]]: memref<?x1x?xf32, strided<[?, 1, 1]>>,
// CHECK-SAME: %[[ARG1:.*]]: f32, %[[ARG2:.*]]: memref<?x1x?x1x?xf32>)
// CHECK-SAME -> memref<?x1x?x1x?xf32> {
// CHECK-SAME: -> memref<?x1x?x1x?xf32> {
// CHECK: %[[OUT:.*]] = memref.collapse_shape %[[ARG2]] {{\[}}[0, 1], [2, 3], [4]]
// CHECK-SAME: : memref<?x1x?x1x?xf32> into memref<?x?x?xf32>
// CHECK: linalg.generic
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/Linalg/fusion-elementwise-ops.mlir
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Expand Up @@ -532,7 +532,7 @@ func.func @scalar_generic_fusion
// CHECK-SAME: ins(%[[ARG1]] : tensor<i32>)
// CHECK: tensor.extract %[[ARG0]]
// CHECK: linalg.yield
// CHECK return %[[T0]]
// CHECK: return %[[T0]]

// -----

Expand Down
6 changes: 3 additions & 3 deletions mlir/test/Dialect/Linalg/transform-ops.mlir
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Expand Up @@ -2,17 +2,17 @@

transform.sequence failures(propagate) {
^bb1(%arg0: !transform.any_op):
// CHECK %{{.*}}, %{{.*}}:2 = transform.structured.tile
// CHECK: %{{.*}}, %{{.*}}:2 = transform.structured.tile
%0, %1:2 = transform.structured.tile_using_for %arg0 tile_sizes [2, 0, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
}

// check that the Attributes of `tile_using_for` are preserved through printing
// and parsing with and without use of the optional `interchange` Attribute.
transform.sequence failures(propagate) {
^bb1(%arg0: !transform.any_op):
// CHECK %{{.*}}, %{{.*}}:2 = transform.structured.tile %arg0 [2, 0, 3] interchange = [2, 1] {test_attr1 = 1 : i64, test_attr2}
// CHECK: %{{.*}}, %{{.*}}:2 = transform.structured.tile_using_for %arg0 tile_sizes [2, 0, 3] interchange = [2, 1] {test_attr1 = 1 : i64, test_attr2}
%0, %1:2 = transform.structured.tile_using_for %arg0 tile_sizes [2, 0, 3] interchange = [2, 1] {test_attr1 = 1 : i64, test_attr2}: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
// CHECK %{{.*}}, %{{.*}}:2 = transform.structured.tile %arg0 [4, 5, 3] {test_attr3 = 1 : i64, test_attr4}
// CHECK: %{{.*}}, %{{.*}}:2 = transform.structured.tile_using_for %tiled_linalg_op tile_sizes [0, 5, 3] {test_attr3 = 1 : i64, test_attr4}
%2, %3:2 = transform.structured.tile_using_for %0 tile_sizes [0, 5, 3] {test_attr3 = 1 : i64, test_attr4}: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
}

Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/OpenMP/ops.mlir
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Expand Up @@ -142,7 +142,7 @@ func.func @omp_parallel_pretty(%data_var : memref<i32>, %if_cond : i1, %num_thre
omp.terminator
}

// CHECK omp.parallel if(%{{.*}}) num_threads(%{{.*}} : i32) private(%{{.*}} : memref<i32>) proc_bind(close)
// CHECK: omp.parallel if(%{{.*}}) num_threads(%{{.*}} : i32) proc_bind(close)
omp.parallel num_threads(%num_threads : i32) if(%if_cond: i1) proc_bind(close) {
omp.terminator
}
Expand Down
12 changes: 6 additions & 6 deletions mlir/test/Dialect/SparseTensor/sparse_reshape.mlir
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Expand Up @@ -76,9 +76,9 @@ func.func @sparse_expand(%arg0: tensor<100xf64, #SparseVector>) -> tensor<10x10x
// CHECK: %[[T:.*]] = arith.muli %[[SI0]], %[[C10]] : index
// CHECK: %[[DI:.*]] = arith.addi %[[T]], %[[SI1]] : index
// CHECK: %[[R1:.*]] = tensor.insert %[[SV]] into %[[A1]]{{\[}}%[[DI]]]
// CHECK scf.yield %[[R1]]
// CHECK }
// CHECK scf.yield %[[RET_1]]
// CHECK: scf.yield %[[R1]]
// CHECK: }
// CHECK: scf.yield %[[RET_1]]
// CHECK: }
// CHECK: %[[NT1:.*]] = sparse_tensor.load %[[RET]] hasInserts
// CHECK-NOT: sparse_tensor.convert
Expand Down Expand Up @@ -170,9 +170,9 @@ func.func @dynamic_sparse_expand(%arg0: tensor<?xf64, #SparseVector>, %sz0: inde
// CHECK: %[[T4:.*]] = arith.muli %[[SI1]], %[[T3]] : index
// CHECK: %[[DI:.*]] = arith.addi %[[T2]], %[[T4]] : index
// CHECK: %[[NT:.*]] = tensor.insert %[[SV]] into %[[R1]]{{\[}}%[[DI]]]
// CHECK scf.yield %[[NT]]
// CHECK }
// CHECK scf.yield %[[RET_1]]
// CHECK: scf.yield %[[NT]]
// CHECK: }
// CHECK: scf.yield %[[RET_1]]
// CHECK: }
// CHECK: %[[NT1:.*]] = sparse_tensor.load %[[RET]] hasInserts
// CHECK-NOT: sparse_tensor.convert
Expand Down
4 changes: 2 additions & 2 deletions mlir/test/Dialect/Tensor/canonicalize.mlir
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Expand Up @@ -1120,8 +1120,8 @@ func.func @compose_expand_of_expand_of_zero_dim(%arg0 : tensor<f32>)
// CHECK-LABEL: func.func @collapse_of_cast(
// CHECK-SAME: %[[IN:.*]]: tensor<8x12x32xf32>) -> tensor<?x32xf32> {
// CHECK-NEXT: %[[COLLAPSE:.*]] = tensor.collapse_shape %[[IN]] {{\[}}[0, 1], [2]] : tensor<8x12x32xf32> into tensor<96x32xf32>
// CHECK-NEXT %[[CAST:.*]] = tensor.cast %[[COLLAPSE]] : tensor<96x32xf32> to tensor<?x32xf32>
// CHECK-NEXT return %[[CAST]] : tensor<?x32xf32>
// CHECK-NEXT: %[[CAST:.*]] = tensor.cast %[[COLLAPSE]] : tensor<96x32xf32> to tensor<?x32xf32>
// CHECK-NEXT: return %[[CAST]] : tensor<?x32xf32>
func.func @collapse_of_cast(%t: tensor<8x12x32xf32>) -> tensor<?x32xf32> {
%0 = tensor.cast %t : tensor<8x12x32xf32> to tensor<?x?x?xf32>
%1 = tensor.collapse_shape %0 [[0, 1], [2]] : tensor<?x?x?xf32> into tensor<?x?xf32>
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/Tosa/canonicalize.mlir
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Expand Up @@ -561,7 +561,7 @@ func.func @canonicalize_concat_slice_on_non_concat_axis(%arg0 : tensor<1x12x12xf

// -----

// CHECK-LABEL
// CHECK-LABEL: @fold_log_exp
func.func @fold_log_exp(%arg0: tensor<?x1xf32>) -> tensor<?x1xf32> {
// CHECK: return %arg{{.*}} : tensor<?x1xf32>
%0 = tosa.exp %arg0 : (tensor<?x1xf32>) -> tensor<?x1xf32>
Expand Down
6 changes: 3 additions & 3 deletions mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
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Expand Up @@ -222,13 +222,13 @@ func.func @test_binary_i32(%arg0 : tensor<4xi32>, %arg1 : tensor<i32>) -> () {

// CHECK-LABEL: @test_binary_i1
func.func @test_binary_i1(%arg0 : tensor<4xi1>, %arg1 : tensor<i1>) -> () {
// CHECK tosa.logical_and %arg0, %arg1 : (tensor<4xi1>, tensor<i1>) -> tensor<4xi1>
// CHECK: tosa.logical_and %arg0, %arg1 : (tensor<4xi1>, tensor<i1>) -> tensor<4xi1>
%0 = tosa.logical_and %arg0, %arg1 : (tensor<4xi1>, tensor<i1>) -> tensor<*xi1>

// CHECK tosa.logical_or %arg0, %arg1 : (tensor<4xi1>, tensor<i1>) -> tensor<4xi1>
// CHECK: tosa.logical_or %arg0, %arg1 : (tensor<4xi1>, tensor<i1>) -> tensor<4xi1>
%1 = tosa.logical_or %arg0, %arg1 : (tensor<4xi1>, tensor<i1>) -> tensor<*xi1>

// CHECK tosa.logical_xor %arg0, %arg1 : (tensor<4xi1>, tensor<i1>) -> tensor<*4i1>
// CHECK: tosa.logical_xor %arg0, %arg1 : (tensor<4xi1>, tensor<i1>) -> tensor<4xi1>
%2 = tosa.logical_xor %arg0, %arg1 : (tensor<4xi1>, tensor<i1>) -> tensor<*xi1>

return
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/Vector/vector-dropleadunitdim-transforms.mlir
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Expand Up @@ -241,7 +241,7 @@ func.func @cast_away_contraction_leading_one_dims_nonleadingunitdim_rank4_acctra
// -----

// CHECK-LABEL: func.func @cast_away_contraction_does_not_transpose_leading_unit_dims
// CHECK-NOT vector.transpose
// CHECK-NOT: vector.transpose
// CHECK: vector.contract
func.func @cast_away_contraction_does_not_transpose_leading_unit_dims(%lhs: vector<1x1x8xi32>,
%rhs: vector<1x8x8xi32>,
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30 changes: 15 additions & 15 deletions mlir/test/IR/parser.mlir
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Expand Up @@ -342,40 +342,40 @@ func.func @loop_bounds(%N : index) {

// CHECK-LABEL: func @ifinst(%{{.*}}: index) {
func.func @ifinst(%N: index) {
%c = arith.constant 200 : index // CHECK %{{.*}} = arith.constant 200
affine.for %i = 1 to 10 { // CHECK affine.for %{{.*}} = 1 to 10 {
affine.if #set0(%i)[%N, %c] { // CHECK affine.if #set0(%{{.*}})[%{{.*}}, %{{.*}}] {
%c = arith.constant 200 : index // CHECK: %{{.*}} = arith.constant 200
affine.for %i = 1 to 10 { // CHECK: affine.for %{{.*}} = 1 to 10 {
affine.if #set0(%i)[%N, %c] { // CHECK: affine.if #set(%{{.*}})[%{{.*}}, %{{.*}}] {
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We shouldn't hardcode transient names after #, same as variable and block names.

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Yes, this looks weird, but there won't any better suggestions, so i've done what i've done.

%x = arith.constant 1 : i32
// CHECK: %{{.*}} = arith.constant 1 : i32
%y = "add"(%x, %i) : (i32, index) -> i32 // CHECK: %{{.*}} = "add"(%{{.*}}, %{{.*}}) : (i32, index) -> i32
%z = "mul"(%y, %y) : (i32, i32) -> i32 // CHECK: %{{.*}} = "mul"(%{{.*}}, %{{.*}}) : (i32, i32) -> i32
} else { // CHECK } else {
affine.if affine_set<(i)[N] : (i - 2 >= 0, 4 - i >= 0)>(%i)[%N] { // CHECK affine.if (#set1(%{{.*}})[%{{.*}}]) {
affine.if affine_set<(i)[N] : (i - 2 >= 0, 4 - i >= 0)>(%i)[%N] { // CHECK: affine.if #set1(%{{.*}})[%{{.*}}] {
// CHECK: %{{.*}} = arith.constant 1 : index
%u = arith.constant 1 : index
// CHECK: %{{.*}} = affine.apply #map{{.*}}(%{{.*}}, %{{.*}})[%{{.*}}]
%w = affine.apply affine_map<(d0,d1)[s0] -> (d0+d1+s0)> (%i, %i) [%u]
} else { // CHECK } else {
%v = arith.constant 3 : i32 // %c3_i32 = arith.constant 3 : i32
}
} // CHECK }
} // CHECK }
return // CHECK return
} // CHECK }
} // CHECK: }
} // CHECK: }
return // CHECK: return
} // CHECK:}

// CHECK-LABEL: func @simple_ifinst(%{{.*}}: index) {
func.func @simple_ifinst(%N: index) {
%c = arith.constant 200 : index // CHECK %{{.*}} = arith.constant 200
affine.for %i = 1 to 10 { // CHECK affine.for %{{.*}} = 1 to 10 {
affine.if #set0(%i)[%N, %c] { // CHECK affine.if #set0(%{{.*}})[%{{.*}}, %{{.*}}] {
%c = arith.constant 200 : index // CHECK: %{{.*}} = arith.constant 200
affine.for %i = 1 to 10 { // CHECK: affine.for %{{.*}} = 1 to 10 {
affine.if #set0(%i)[%N, %c] { // CHECK: affine.if #set(%{{.*}})[%{{.*}}, %{{.*}}] {
%x = arith.constant 1 : i32
// CHECK: %{{.*}} = arith.constant 1 : i32
%y = "add"(%x, %i) : (i32, index) -> i32 // CHECK: %{{.*}} = "add"(%{{.*}}, %{{.*}}) : (i32, index) -> i32
%z = "mul"(%y, %y) : (i32, i32) -> i32 // CHECK: %{{.*}} = "mul"(%{{.*}}, %{{.*}}) : (i32, i32) -> i32
} // CHECK }
} // CHECK }
return // CHECK return
} // CHECK }
} // CHECK: }
} // CHECK: }
return // CHECK: return
} // CHECK:}

// CHECK-LABEL: func @attributes() {
func.func @attributes() {
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28 changes: 18 additions & 10 deletions mlir/test/Target/LLVMIR/llvmir.mlir
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Original file line number Diff line number Diff line change
Expand Up @@ -2331,39 +2331,47 @@ llvm.func @streaming_compatible_func() attributes {arm_streaming_compatible} {
// -----

// CHECK-LABEL: @new_za_func
// CHECK: #[[ATTR:[0-9]*]]
// CHECK-SAME: #[[ATTR:[0-9]*]]
llvm.func @new_za_func() attributes {arm_new_za} {
llvm.return
}
// CHECK #[[ATTR]] = { "aarch64_new_za" }
// CHECK: #[[ATTR]] = { "aarch64_new_za" }

// -----

// CHECK-LABEL: @in_za_func
// CHECK: #[[ATTR:[0-9]*]]
// CHECK-SAME: #[[ATTR:[0-9]*]]
llvm.func @in_za_func() attributes {arm_in_za } {
llvm.return
}
// CHECK #[[ATTR]] = { "aarch64_in_za" }
// CHECK: #[[ATTR]] = { "aarch64_in_za" }

// -----

// CHECK-LABEL: @out_za_func
// CHECK: #[[ATTR:[0-9]*]]
// CHECK-SAME: #[[ATTR:[0-9]*]]
llvm.func @out_za_func() attributes {arm_out_za } {
llvm.return
}
// CHECK #[[ATTR]] = { "aarch64_out_za" }
// CHECK: #[[ATTR]] = { "aarch64_out_za" }

// -----

// CHECK-LABEL: @inout_za_func
// CHECK: #[[ATTR:[0-9]*]]
// CHECK-SAME: #[[ATTR:[0-9]*]]
llvm.func @inout_za_func() attributes {arm_inout_za } {
llvm.return
}
// CHECK #[[ATTR]] = { "aarch64_inout_za" }
// CHECK: #[[ATTR]] = { "aarch64_inout_za" }

// -----

// CHECK-LABEL: @preserves_za_func
// CHECK: #[[ATTR:[0-9]*]]
// CHECK-SAME: #[[ATTR:[0-9]*]]
llvm.func @preserves_za_func() attributes {arm_preserves_za} {
llvm.return
}
// CHECK #[[ATTR]] = { "aarch64_preserves_za" }
// CHECK: #[[ATTR]] = { "aarch64_preserves_za" }

// -----

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