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

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

Author: Dinistro

mlir/test/Integration/Dialect/SparseTensor/CPU/block.mlir

@@ -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) ->

mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output.mlir

@@ -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)

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_ds.mlir

@@ -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)

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_flatten.mlir

@@ -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

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_matvec.mlir

@@ -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),

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_mttkrp.mlir

@@ -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)

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_out_simple.mlir

@@ -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)

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sampled_matmul.mlir

@@ -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),

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sorted_coo.mlir

@@ -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)

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_spmm.mlir

@@ -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)

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum.mlir

@@ -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)

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_bf16.mlir

@@ -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)

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_c32.mlir

@@ -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)

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_f16.mlir

@@ -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)

mlir/test/Integration/Dialect/SparseTensor/GPU/CUDA/sparse-sampled-matmul-lib.mlir

@@ -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)

mlir/test/Integration/Dialect/SparseTensor/GPU/CUDA/sparse-sddmm-lib.mlir

@@ -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)

mlir/test/Integration/Dialect/SparseTensor/python/test_output.py

@@ -19,11 +19,11 @@
 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
 }}
 """

mlir/test/Integration/Dialect/Vector/CPU/ArmSME/load-store-128-bit-tile.mlir

@@ -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

mlir/test/Integration/Dialect/Vector/CPU/X86Vector/test-inline-asm-vector-avx512.mlir

@@ -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>

mlir/test/Integration/GPU/CUDA/sm90/tma_load_128x64_swizzle128b.mlir

@@ -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

mlir/test/Integration/GPU/CUDA/sm90/tma_load_64x64_swizzle128b.mlir

@@ -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