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[MLIR][LLVM] Remove typed pointer remnants from integration tests (#71208)

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This commit removes all LLVM dialect typed pointers from the integration
tests. Typed pointers have been deprecated for a while now and it's
planned to soon remove them from the LLVM dialect.

Related PSA:
https://discourse.llvm.org/t/psa-removal-of-typed-pointers-from-the-llvm-dialect/74502
This commit is contained in:
Christian Ulmann
2023-11-03 21:21:25 +01:00
committed by GitHub
parent a682a9cfd0
commit 52491c99fa
21 changed files with 28 additions and 29 deletions
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2
mlir/test/Integration/Dialect/SparseTensor/CPU/block.mlir
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@@ -25,7 +25,7 @@
// REDEFINE: %{sparse_compiler_opts} = enable-runtime-library=false
// R_UN: %{compile} | env %{env} %{run} | FileCheck %s
!Filename = !llvm.ptr<i8>
!Filename = !llvm.ptr
#BSR = #sparse_tensor.encoding<{
map = (i, j) ->

2
mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output.mlir
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@@ -31,7 +31,7 @@
// Do the same run, but now with direct IR generation and VLA vectorization.
// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | env %{env} %{run_sve} | FileCheck %s %}
!Filename = !llvm.ptr<i8>
!Filename = !llvm.ptr
#DenseMatrix = #sparse_tensor.encoding<{
map = (d0, d1) -> (d0 : dense, d1 : dense)

2
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_ds.mlir
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@@ -25,7 +25,7 @@
// REDEFINE: %{sparse_compiler_opts} = enable-runtime-library=false
// R_UN: %{compile} | env %{env} %{run} | FileCheck %s
!Filename = !llvm.ptr<i8>
!Filename = !llvm.ptr
#CSR = #sparse_tensor.encoding<{
map = (i, j) -> ( i : dense, j : compressed)

2
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_flatten.mlir
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@@ -31,7 +31,7 @@
// Do the same run, but now with direct IR generation and VLA vectorization.
// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | env %{env} %{run_sve} | FileCheck %s %}
!Filename = !llvm.ptr<i8>
!Filename = !llvm.ptr
#SparseTensor = #sparse_tensor.encoding<{
// Note that any dimToLvl permutation should give the same results

2
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_matvec.mlir
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@@ -40,7 +40,7 @@
// vectorization.
// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | env %{env} %{run_sve} | FileCheck %s %}
!Filename = !llvm.ptr<i8>
!Filename = !llvm.ptr
#SparseMatrix = #sparse_tensor.encoding<{
map = (d0, d1) -> (d0 : dense, d1 : compressed),

2
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_mttkrp.mlir
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@@ -32,7 +32,7 @@
// vectorization.
// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | env %{env} %{run_sve} | FileCheck %s %}
!Filename = !llvm.ptr<i8>
!Filename = !llvm.ptr
#SparseTensor = #sparse_tensor.encoding<{
map = (d0, d1, d2) -> (d0 : compressed, d1 : compressed, d2 : compressed)

2
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_out_simple.mlir
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@@ -28,7 +28,7 @@
// vectorization.
// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | env %{env} %{run_sve} | FileCheck %s %}
!Filename = !llvm.ptr<i8>
!Filename = !llvm.ptr
#DCSR = #sparse_tensor.encoding<{
map = (d0, d1) -> (d0 : compressed, d1 : compressed)

2
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sampled_matmul.mlir
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@@ -32,7 +32,7 @@
// vectorization.
// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | env %{env} %{run_sve} | FileCheck %s %}
!Filename = !llvm.ptr<i8>
!Filename = !llvm.ptr
#SparseMatrix = #sparse_tensor.encoding<{
map = (d0, d1) -> (d0 : compressed, d1 : compressed),

2
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sorted_coo.mlir
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@@ -32,7 +32,7 @@
// Do the same run, but now with VLA vectorization.
// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | env %{env} %{run_sve} | FileCheck %s %}
!Filename = !llvm.ptr<i8>
!Filename = !llvm.ptr
#SortedCOO = #sparse_tensor.encoding<{
map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)

2
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_spmm.mlir
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@@ -31,7 +31,7 @@
// Do the same run, but now with VLA vectorization.
// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | env %{env} %{run_sve} | FileCheck %s %}
!Filename = !llvm.ptr<i8>
!Filename = !llvm.ptr
#SparseMatrix = #sparse_tensor.encoding<{
map = (d0, d1) -> (d0 : dense, d1 : compressed)

2
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum.mlir
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@@ -34,7 +34,7 @@
// TODO: The test currently only operates on the triangular part of the
// symmetric matrix.
!Filename = !llvm.ptr<i8>
!Filename = !llvm.ptr
#SparseMatrix = #sparse_tensor.encoding<{
map = (d0, d1) -> (d0 : compressed, d1 : compressed)

2
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_bf16.mlir
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@@ -31,7 +31,7 @@
// UNSUPPORTED: target=aarch64{{.*}}
!Filename = !llvm.ptr<i8>
!Filename = !llvm.ptr
#SparseMatrix = #sparse_tensor.encoding<{
map = (d0, d1) -> (d0 : compressed, d1 : compressed)

2
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_c32.mlir
View File

@@ -34,7 +34,7 @@
// TODO: The test currently only operates on the triangular part of the
// symmetric matrix.
!Filename = !llvm.ptr<i8>
!Filename = !llvm.ptr
#SparseMatrix = #sparse_tensor.encoding<{
map = (d0, d1) -> (d0 : compressed, d1 : compressed)

2
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_f16.mlir
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@@ -30,7 +30,7 @@
// Do the same run, but now with VLA vectorization.
// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | %{run_sve} | FileCheck %s %}
!Filename = !llvm.ptr<i8>
!Filename = !llvm.ptr
#SparseMatrix = #sparse_tensor.encoding<{
map = (d0, d1) -> (d0 : compressed, d1 : compressed)

2
mlir/test/Integration/Dialect/SparseTensor/GPU/CUDA/sparse-sampled-matmul-lib.mlir
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@@ -26,7 +26,7 @@
// RUNNOT: %{compile} enable-runtime-library=false gpu-data-transfer-strategy=zero-copy" | %{run}
//
!Filename = !llvm.ptr<i8>
!Filename = !llvm.ptr
#CSR = #sparse_tensor.encoding<{
map = (d0, d1) -> (d0 : dense, d1 : compressed)

2
mlir/test/Integration/Dialect/SparseTensor/GPU/CUDA/sparse-sddmm-lib.mlir
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@@ -21,7 +21,7 @@
// R_UN: %{compile} enable-runtime-library=false" | %{run}
//
!Filename = !llvm.ptr<i8>
!Filename = !llvm.ptr
#CSR = #sparse_tensor.encoding<{
map = (d0, d1) -> (d0 : dense, d1 : compressed)

4
mlir/test/Integration/Dialect/SparseTensor/python/test_output.py
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@@ -19,11 +19,11 @@ from tools import sparse_compiler
def boilerplate(attr: st.EncodingAttr):
"""Returns boilerplate main method."""
return f"""
func.func @main(%p : !llvm.ptr<i8>) -> () attributes {{ llvm.emit_c_interface }} {{
func.func @main(%p : !llvm.ptr) -> () attributes {{ llvm.emit_c_interface }} {{
%d = arith.constant sparse<[[0, 0], [1, 1], [0, 9], [9, 0], [4, 4]],
[1.0, 2.0, 3.0, 4.0, 5.0]> : tensor<10x10xf64>
%a = sparse_tensor.convert %d : tensor<10x10xf64> to tensor<10x10xf64, {attr}>
sparse_tensor.out %a, %p : tensor<10x10xf64, {attr}>, !llvm.ptr<i8>
sparse_tensor.out %a, %p : tensor<10x10xf64, {attr}>, !llvm.ptr
return
}}
"""

8
mlir/test/Integration/Dialect/Vector/CPU/ArmSME/load-store-128-bit-tile.mlir
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@@ -37,10 +37,10 @@ func.func @vector_copy_i128(%src: memref<?x?xi128>, %dst: memref<?x?xi128>) {
}
func.func @test_load_store_zaq0() {
%init_a_str = llvm.mlir.addressof @init_tile_a : !llvm.ptr<array<17 x i8>>
%init_b_str = llvm.mlir.addressof @init_tile_b : !llvm.ptr<array<17 x i8>>
%final_a_str = llvm.mlir.addressof @final_tile_a : !llvm.ptr<array<17 x i8>>
%final_b_str = llvm.mlir.addressof @final_tile_b : !llvm.ptr<array<17 x i8>>
%init_a_str = llvm.mlir.addressof @init_tile_a : !llvm.ptr
%init_b_str = llvm.mlir.addressof @init_tile_b : !llvm.ptr
%final_a_str = llvm.mlir.addressof @final_tile_a : !llvm.ptr
%final_b_str = llvm.mlir.addressof @final_tile_b : !llvm.ptr
%c0 = arith.constant 0 : index
%min_elts_q = arith.constant 1 : index

9
mlir/test/Integration/Dialect/Vector/CPU/X86Vector/test-inline-asm-vector-avx512.mlir
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@@ -13,18 +13,17 @@ module {
llvm.func @entry() -> i32 {
%c0 = llvm.mlir.constant(0 : index) : i64
%1 = llvm.mlir.addressof @const16 : !llvm.ptr<array<16 x i32>>
%1 = llvm.mlir.addressof @const16 : !llvm.ptr
%ptr = llvm.getelementptr %1[%c0, %c0]
: (!llvm.ptr<array<16 x i32>>, i64, i64) -> !llvm.ptr<i32>
%ptr2 = llvm.bitcast %ptr : !llvm.ptr<i32> to !llvm.ptr<vector<16xi32>>
: (!llvm.ptr, i64, i64) -> !llvm.ptr, !llvm.array<16 x i32>
// operand_attrs of *m operands need to be piped through to LLVM for
// verification to pass.
%v = llvm.inline_asm
asm_dialect = intel
operand_attrs = [{ elementtype = vector<16xi32> }]
"vmovdqu32 $0, $1", "=x,*m" %ptr2
: (!llvm.ptr<vector<16xi32>>) -> vector<16xi32>
"vmovdqu32 $0, $1", "=x,*m" %ptr
: (!llvm.ptr) -> vector<16xi32>
// CHECK: 0
%v0 = vector.extract %v[0]: i32 from vector<16xi32>

2
mlir/test/Integration/GPU/CUDA/sm90/tma_load_128x64_swizzle128b.mlir
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@@ -31,7 +31,7 @@
module @mymod {
func.func private @printMemrefF32(memref<*xf32>)
memref.global "private" @bufferLhsGlobal : !shmemlhs
llvm.func @printf(!llvm.ptr<i8>, ...) -> i32
llvm.func @printf(!llvm.ptr, ...) -> i32
func.func @main() {
%c8192 = arith.constant 8192 : index
%c-1_i32 = arith.constant -1 : i32

2
mlir/test/Integration/GPU/CUDA/sm90/tma_load_64x64_swizzle128b.mlir
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@@ -41,7 +41,7 @@ module @mymod {
func.func private @printMemrefF32(memref<*xf32>)
memref.global "private" @bufferLhsGlobal : !shmemlhs
memref.global "private" @bufferRhsGlobal : !shmemrhs
llvm.func @printf(!llvm.ptr<i8>, ...) -> i32
llvm.func @printf(!llvm.ptr, ...) -> i32
func.func @main() {
%c32768 = arith.constant 32768 : index
%c-1_i32 = arith.constant -1 : i32