[MLIR] Switch lit tests to %mlir_lib_dir and %mlir_src_dir replacements.

The old replacements will be removed soon:
- `%linalg_test_lib_dir`
- `%cuda_wrapper_library_dir`
- `%spirv_wrapper_library_dir`
- `%vulkan_wrapper_library_dir`
- `%mlir_runner_utils_dir`
- `%mlir_integration_test_dir`

Reviewed By: herhut

Differential Revision: https://reviews.llvm.org/D133270

mlir/test/CMakeLists.txt

@@ -35,15 +35,6 @@ if (MLIR_INCLUDE_INTEGRATION_TESTS)
     message(FATAL_ERROR "MLIR_INCLUDE_INTEGRATION_TESTS requires a native target")
   endif()
 
-  # Copy test data over.
-  # TODO: drop copy and load files relative to MLIR_SOURCE_DIR / %mlir_src_root.
-  file(COPY ${CMAKE_CURRENT_SOURCE_DIR}/Integration/data/mttkrp_b.tns
-            ${CMAKE_CURRENT_SOURCE_DIR}/Integration/data/test.mtx
-            ${CMAKE_CURRENT_SOURCE_DIR}/Integration/data/test_symmetric.mtx
-            ${CMAKE_CURRENT_SOURCE_DIR}/Integration/data/test_symmetric_complex.mtx
-            ${CMAKE_CURRENT_SOURCE_DIR}/Integration/data/test.tns
-            ${CMAKE_CURRENT_SOURCE_DIR}/Integration/data/wide.mtx
-          DESTINATION ${MLIR_LIB_DIR}/data/)
 endif()
 
 llvm_canonicalize_cmake_booleans(

mlir/test/Integration/Dialect/Async/CPU/microbench-linalg-async-parallel-for.mlir

@@ -14,9 +14,9 @@
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN: -e entry -entry-point-result=void -O3                                  \
-// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext  \
-// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext\
-// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext \
+// RUN: -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext  \
+// RUN: -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext\
+// RUN: -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext \
 // RUN: | FileCheck %s --dump-input=always
 
 // RUN:   mlir-opt %s                                                          \
@@ -28,9 +28,9 @@
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN: -e entry -entry-point-result=void -O3                                  \
-// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext  \
-// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext\
-// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext \
+// RUN: -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext  \
+// RUN: -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext\
+// RUN: -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext \
 // RUN: | FileCheck %s --dump-input=always
 
 #map0 = affine_map<(d0, d1) -> (d0, d1)>

mlir/test/Integration/Dialect/Async/CPU/microbench-scf-async-parallel-for.mlir

@@ -14,9 +14,9 @@
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN: -e entry -entry-point-result=void -O3                                  \
-// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext  \
-// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext\
-// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext \
+// RUN: -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext  \
+// RUN: -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext\
+// RUN: -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext \
 // RUN: | FileCheck %s --dump-input=always
 
 // RUN:   mlir-opt %s                                                          \
@@ -35,9 +35,9 @@
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN: -e entry -entry-point-result=void -O3                                  \
-// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext  \
-// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext\
-// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext \
+// RUN: -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext  \
+// RUN: -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext\
+// RUN: -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext \
 // RUN: | FileCheck %s --dump-input=always
 
 // RUN:   mlir-opt %s                                                          \
@@ -49,9 +49,9 @@
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN: -e entry -entry-point-result=void -O3                                  \
-// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext  \
-// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext\
-// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext \
+// RUN: -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext  \
+// RUN: -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext\
+// RUN: -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext \
 // RUN: | FileCheck %s --dump-input=always
 
 #map0 = affine_map<(d0, d1) -> (d0, d1)>

mlir/test/Integration/Dialect/Async/CPU/test-async-parallel-for-1d.mlir

@@ -11,8 +11,8 @@
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:  -e entry -entry-point-result=void -O0                                 \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext\
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext\
 // RUN: | FileCheck %s --dump-input=always
 
 // RUN:   mlir-opt %s -async-parallel-for                                      \
@@ -27,8 +27,8 @@
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:  -e entry -entry-point-result=void -O0                                 \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext\
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext\
 // RUN: | FileCheck %s --dump-input=always
 
 // RUN:   mlir-opt %s -async-parallel-for="async-dispatch=false                \
@@ -46,8 +46,8 @@
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:  -e entry -entry-point-result=void -O0                                 \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext\
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext\
 // RUN: | FileCheck %s --dump-input=always
 
 // Suppress constant folding by introducing "dynamic" zero value at runtime.

mlir/test/Integration/Dialect/Async/CPU/test-async-parallel-for-2d.mlir

@@ -10,8 +10,8 @@
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:  -e entry -entry-point-result=void -O0                                 \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext\
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext\
 // RUN: | FileCheck %s --dump-input=always
 
 // RUN:   mlir-opt %s -async-parallel-for                                      \
@@ -25,8 +25,8 @@
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:  -e entry -entry-point-result=void -O0                                 \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext\
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext\
 // RUN: | FileCheck %s --dump-input=always
 
 // RUN:   mlir-opt %s -async-parallel-for="async-dispatch=false                \
@@ -43,8 +43,8 @@
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:  -e entry -entry-point-result=void -O0                                 \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext\
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext\
 // RUN: | FileCheck %s --dump-input=always
 
 func.func @entry() {

mlir/test/Integration/Dialect/Complex/CPU/correctness.mlir

@@ -6,7 +6,7 @@
 // RUN:   -convert-func-to-llvm -reconcile-unrealized-casts |\
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext |\
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext |\
 // RUN: FileCheck %s
 
 func.func @test_unary(%input: tensor<?xcomplex<f32>>,

mlir/test/Integration/Dialect/LLVMIR/CPU/X86/test-inline-asm-vector.mlir

@@ -1,6 +1,6 @@
 // RUN: mlir-opt %s -convert-vector-to-llvm |  \
 // RUN: mlir-cpu-runner -e entry_point_with_all_constants -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext
 
 module {
   llvm.func @function_to_run(%a: vector<8xf32>, %b: vector<8xf32>)  {

mlir/test/Integration/Dialect/LLVMIR/CPU/X86/test-inline-asm.mlir

@@ -1,5 +1,5 @@
 // RUN: mlir-cpu-runner %s -e entry -entry-point-result=void  \
-// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 module {

mlir/test/Integration/Dialect/LLVMIR/CPU/test-vector-reductions-fp.mlir

@@ -1,5 +1,5 @@
 // RUN: mlir-cpu-runner %s -e entry -entry-point-result=void  \
-// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 // End-to-end test of all fp reduction intrinsics (not exhaustive unit tests).

mlir/test/Integration/Dialect/LLVMIR/CPU/test-vector-reductions-int.mlir

@@ -1,5 +1,5 @@
 // RUN: mlir-cpu-runner %s -e entry -entry-point-result=void  \
-// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 // End-to-end test of all int reduction intrinsics (not exhaustive unit tests).

mlir/test/Integration/Dialect/Linalg/CPU/matmul-vs-matvec.mlir

@@ -1,6 +1,6 @@
 // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -O3 -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 func.func private @printMemrefF32(memref<*xf32>)

mlir/test/Integration/Dialect/Linalg/CPU/rank-reducing-subview.mlir

@@ -1,6 +1,6 @@
 // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -O3 -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 func.func private @printMemrefF32(memref<*xf32>)

mlir/test/Integration/Dialect/Linalg/CPU/test-collapse-tensor.mlir

@@ -3,7 +3,7 @@
 // RUN: -finalizing-bufferize -buffer-deallocation -convert-linalg-to-llvm \
 // RUN: -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 

mlir/test/Integration/Dialect/Linalg/CPU/test-conv-1d-call.mlir

@@ -1,12 +1,12 @@
 // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 // RUN: mlir-opt %s -linalg-tile="tile-sizes=4" -convert-linalg-to-loops -convert-scf-to-cf \
 // RUN:   -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 func.func private @printMemrefF32(memref<*xf32>)

mlir/test/Integration/Dialect/Linalg/CPU/test-conv-1d-nwc-wcf-call.mlir

@@ -1,12 +1,12 @@
 // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,4" -convert-linalg-to-loops -convert-scf-to-cf \
 // RUN:   -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 func.func private @printMemrefF32(memref<*xf32>)

mlir/test/Integration/Dialect/Linalg/CPU/test-conv-2d-call.mlir

@@ -1,12 +1,12 @@
 // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,2" -convert-linalg-to-loops -convert-scf-to-cf \
 // RUN:   -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 func.func private @printMemrefF32(memref<*xf32>)

mlir/test/Integration/Dialect/Linalg/CPU/test-conv-2d-nhwc-hwcf-call.mlir

@@ -1,12 +1,12 @@
 // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,3,3,2" -convert-linalg-to-loops -convert-scf-to-cf \
 // RUN:   -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 func.func private @printMemrefF32(memref<*xf32>)

mlir/test/Integration/Dialect/Linalg/CPU/test-conv-3d-call.mlir

@@ -1,12 +1,12 @@
 // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,2,2" -convert-linalg-to-loops -convert-scf-to-cf \
 // RUN:   -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 func.func private @printMemrefF32(memref<*xf32>)

mlir/test/Integration/Dialect/Linalg/CPU/test-conv-3d-ndhwc-dhwcf-call.mlir

@@ -1,12 +1,12 @@
 // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 // RUN: mlir-opt %s -linalg-tile="tile-sizes=0,5,5,5" -convert-linalg-to-loops -convert-scf-to-cf \
 // RUN:   -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 func.func private @printMemrefF32(memref<*xf32>)

mlir/test/Integration/Dialect/Linalg/CPU/test-elementwise.mlir

@@ -4,7 +4,7 @@
 // RUN: -convert-linalg-to-llvm --convert-memref-to-llvm -convert-func-to-llvm \
 // RUN: -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 func.func @main() {

mlir/test/Integration/Dialect/Linalg/CPU/test-expand-tensor.mlir

@@ -3,7 +3,7 @@
 // RUN: -finalizing-bufferize -buffer-deallocation -convert-linalg-to-llvm \
 // RUN: -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 

mlir/test/Integration/Dialect/Linalg/CPU/test-one-shot-bufferize.mlir

@@ -3,7 +3,7 @@
 // RUN: mlir-opt -pass-pipeline="func.func(canonicalize,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
 
 // RUN: mlir-cpu-runner -O3 -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext,%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext |\
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext,%mlir_lib_dir/libmlir_c_runner_utils%shlibext |\
 // RUN: FileCheck %s
 
 #map0 = affine_map<(d0, d1)[s0] -> ((d1 - d0) ceildiv s0)>

mlir/test/Integration/Dialect/Linalg/CPU/test-padtensor.mlir

@@ -4,7 +4,7 @@
 // RUN: -finalizing-bufferize -buffer-deallocation \
 // RUN: -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext,%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 

mlir/test/Integration/Dialect/Linalg/CPU/test-subtensor-insert-multiple-uses.mlir

@@ -3,7 +3,7 @@
 // RUN: -finalizing-bufferize -buffer-deallocation \
 // RUN: -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext,%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 func.func @main() {

mlir/test/Integration/Dialect/Linalg/CPU/test-subtensor-insert.mlir

@@ -3,7 +3,7 @@
 // RUN: -finalizing-bufferize -buffer-deallocation \
 // RUN: -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 func.func @main() {

mlir/test/Integration/Dialect/Linalg/CPU/test-tensor-e2e.mlir

@@ -2,7 +2,7 @@
 // RUN: -tensor-bufferize -func-bufferize -finalizing-bufferize -buffer-deallocation -convert-linalg-to-loops \
 // RUN: -convert-linalg-to-llvm --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 func.func @foo() -> tensor<4xf32> {

mlir/test/Integration/Dialect/Linalg/CPU/test-tensor-matmul.mlir

@@ -3,7 +3,7 @@
 // RUN: -tensor-bufferize -func-bufferize -finalizing-bufferize -buffer-deallocation -convert-linalg-to-loops -convert-scf-to-cf \
 // RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext,%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 // RUN: mlir-opt %s  -linalg-tile="tile-sizes=1,2,3" -linalg-bufferize \
@@ -12,7 +12,7 @@
 // RUN: -finalizing-bufferize -convert-linalg-to-loops -convert-scf-to-cf -convert-scf-to-cf \
 // RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext,%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext \
 // RUN: | FileCheck %s
 
 func.func @main() {

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #MAT_C_C = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}>

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

@@ -1,8 +1,8 @@
 // RUN: mlir-opt %s --sparse-compiler | \
-// RUN: TENSOR0="%mlir_integration_test_dir/data/test.mtx" \
+// RUN: TENSOR0="%mlir_src_dir/test/Integration/data/test.mtx" \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 !Filename = !llvm.ptr<i8>

mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output_bf16.mlir

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>

mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output_f16.mlir

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }>

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 //
 // Do the same run, but now with SIMDization as well. This should not change the outcome.
@@ -9,7 +9,7 @@
 // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=any-storage-inner-loop vl=2" | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SV = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }>

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_complex32.mlir

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_complex64.mlir

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #Tensor1  = #sparse_tensor.encoding<{

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #Tensor1  = #sparse_tensor.encoding<{

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #DCSR  = #sparse_tensor.encoding<{

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #DCSR  = #sparse_tensor.encoding<{

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conversion_sparse2dense.mlir

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext \
 // RUN:  | \
 // RUN: FileCheck %s
 

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conversion_sparse2sparse.mlir

@@ -1,7 +1,7 @@
 // Force this file to use the kDirect method for sparse2sparse.
 // RUN: mlir-opt %s --sparse-compiler="s2s-strategy=2" | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #Tensor1 = #sparse_tensor.encoding<{

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

@@ -1,6 +1,6 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }>

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_filter_conv2d.mlir

@@ -1,13 +1,13 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 //
 // Do the same run, but now with SIMDization as well. This should not change the outcome.
 //
 // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=any-storage-inner-loop vl=2" | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #DCSR = #sparse_tensor.encoding<{ dimLevelType = [ "compressed", "compressed" ] }>

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

@@ -1,17 +1,17 @@
 // RUN: mlir-opt %s --sparse-compiler | \
-// RUN: TENSOR0="%mlir_integration_test_dir/data/test.tns" \
+// RUN: TENSOR0="%mlir_src_dir/test/Integration/data/test.tns" \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 //
 // Do the same run, but now with SIMDization as well. This should not change the outcome.
 //
 // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=any-storage-inner-loop vl=4" | \
-// RUN: TENSOR0="%mlir_integration_test_dir/data/test.tns" \
+// RUN: TENSOR0="%mlir_src_dir/test/Integration/data/test.tns" \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 !Filename = !llvm.ptr<i8>

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

@@ -1,6 +1,6 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{

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

@@ -1,13 +1,13 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 //
 // Do the same run, but now with SIMDization as well. This should not change the outcome.
 //
 // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=any-storage-inner-loop vl=4" | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{

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

@@ -1,6 +1,6 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #CSR = #sparse_tensor.encoding<{

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #DCSR = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}>

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

@@ -1,18 +1,18 @@
 // RUN: mlir-opt %s --sparse-compiler | \
-// RUN: TENSOR0="%mlir_integration_test_dir/data/wide.mtx" \
+// RUN: TENSOR0="%mlir_src_dir/test/Integration/data/wide.mtx" \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 //
 // Do the same run, but now with SIMDization as well. This should not change the outcome.
 //
 // RUN: mlir-opt %s \
 // RUN:   --sparse-compiler="vectorization-strategy=any-storage-inner-loop vl=16 enable-simd-index32" | \
-// RUN: TENSOR0="%mlir_integration_test_dir/data/wide.mtx" \
+// RUN: TENSOR0="%mlir_src_dir/test/Integration/data/wide.mtx" \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 !Filename = !llvm.ptr<i8>

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

@@ -1,17 +1,17 @@
 // RUN: mlir-opt %s --sparse-compiler | \
-// RUN: TENSOR0="%mlir_integration_test_dir/data/mttkrp_b.tns" \
+// RUN: TENSOR0="%mlir_src_dir/test/Integration/data/mttkrp_b.tns" \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 //
 // Do the same run, but now with SIMDization as well. This should not change the outcome.
 //
 // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=any-storage-inner-loop vl=4" | \
-// RUN: TENSOR0="%mlir_integration_test_dir/data/mttkrp_b.tns" \
+// RUN: TENSOR0="%mlir_src_dir/test/Integration/data/mttkrp_b.tns" \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 !Filename = !llvm.ptr<i8>

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #DCSR = #sparse_tensor.encoding<{

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseMatrix = #sparse_tensor.encoding<{

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

@@ -1,17 +1,17 @@
 // RUN: mlir-opt %s --sparse-compiler | \
-// RUN: TENSOR0="%mlir_integration_test_dir/data/test.mtx" \
+// RUN: TENSOR0="%mlir_src_dir/test/Integration/data/test.mtx" \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 //
 // Do the same run, but now with SIMDization as well. This should not change the outcome.
 //
 // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=any-storage-inner-loop vl=4" | \
-// RUN: TENSOR0="%mlir_integration_test_dir/data/test.mtx" \
+// RUN: TENSOR0="%mlir_src_dir/test/Integration/data/test.mtx" \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 !Filename = !llvm.ptr<i8>

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

@@ -1,13 +1,13 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 //
 // Do the same run, but now with SIMDization as well. This should not change the outcome.
 //
 // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=any-storage-inner-loop vl=2" | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #DCSR = #sparse_tensor.encoding<{ dimLevelType = [ "compressed", "compressed" ] }>

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>

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

@@ -1,13 +1,13 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 //
 // Do the same run, but now with SIMDization as well. This should not change the outcome.
 //
 // RUN: mlir-opt %s -sparse-compiler="vectorization-strategy=any-storage-inner-loop vl=8" | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SV = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }>

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

@@ -1,6 +1,6 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{

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

@@ -1,18 +1,18 @@
 // RUN: mlir-opt %s --sparse-compiler | \
-// RUN: TENSOR0="%mlir_integration_test_dir/data/test.mtx" \
+// RUN: TENSOR0="%mlir_src_dir/test/Integration/data/test.mtx" \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 //
 // Do the same run, but now with SIMDization as well. This should not change the outcome.
 //
 // RUN: mlir-opt %s \
 // RUN:   --sparse-compiler="vectorization-strategy=any-storage-inner-loop vl=4 enable-simd-index32" | \
-// RUN: TENSOR0="%mlir_integration_test_dir/data/test.mtx" \
+// RUN: TENSOR0="%mlir_src_dir/test/Integration/data/test.mtx" \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 //
 

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

@@ -1,13 +1,13 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 //
 // Do the same run, but now with SIMDization as well. This should not change the outcome.
 //
 // RUN: mlir-opt %s -sparse-compiler="vl=8" | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SM = #sparse_tensor.encoding<{ dimLevelType = [ "compressed", "compressed" ] }>

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 //
 // Do the same run, but now with SIMDization as well. This should not change the outcome.
@@ -9,7 +9,7 @@
 // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=any-storage-inner-loop vl=4" | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #CSR = #sparse_tensor.encoding<{ dimLevelType = [ "dense", "compressed" ] }>

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #map = affine_map<(d0, d1, d2) -> (d0, d1, d2)>

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }>

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

@@ -1,17 +1,17 @@
 // RUN: mlir-opt %s --sparse-compiler | \
-// RUN: TENSOR0="%mlir_integration_test_dir/data/wide.mtx" \
+// RUN: TENSOR0="%mlir_src_dir/test/Integration/data/wide.mtx" \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 //
 // Do the same run, but now with SIMDization as well. This should not change the outcome.
 //
 // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=any-storage-inner-loop vl=2" | \
-// RUN: TENSOR0="%mlir_integration_test_dir/data/wide.mtx" \
+// RUN: TENSOR0="%mlir_src_dir/test/Integration/data/wide.mtx" \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 !Filename = !llvm.ptr<i8>

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 //

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

@@ -1,17 +1,17 @@
 // RUN: mlir-opt %s --sparse-compiler | \
-// RUN: TENSOR0="%mlir_integration_test_dir/data/test_symmetric.mtx" \
+// RUN: TENSOR0="%mlir_src_dir/test/Integration/data/test_symmetric.mtx" \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 //
 // Do the same run, but now with SIMDization as well. This should not change the outcome.
 //
 // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=any-storage-inner-loop vl=2" | \
-// RUN: TENSOR0="%mlir_integration_test_dir/data/test_symmetric.mtx" \
+// RUN: TENSOR0="%mlir_src_dir/test/Integration/data/test_symmetric.mtx" \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 !Filename = !llvm.ptr<i8>

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 !Filename = !llvm.ptr<i8>

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

@@ -1,8 +1,8 @@
 // RUN: mlir-opt %s --sparse-compiler | \
-// RUN: TENSOR0="%mlir_integration_test_dir/data/test_symmetric_complex.mtx" \
+// RUN: TENSOR0="%mlir_src_dir/test/Integration/data/test_symmetric_complex.mtx" \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 !Filename = !llvm.ptr<i8>

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 !Filename = !llvm.ptr<i8>

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }>

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #ST = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed", "compressed"]}>

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #ST1 = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed", "compressed"]}>

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

@@ -1,6 +1,6 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #DCSR = #sparse_tensor.encoding<{

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>

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

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --sparse-compiler | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>

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

@@ -1,4 +1,4 @@
-# RUN: SUPPORT_LIB=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext \
+# RUN: SUPPORT_LIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext \
 # RUN:   %PYTHON %s | FileCheck %s
 
 import ctypes
@@ -24,36 +24,36 @@ def sddmm_dsl(
     B=dsl.TensorDef(dsl.T, dsl.S.K, dsl.S.N),
     S=dsl.TensorDef(dsl.T, dsl.S.M, dsl.S.N),
     C=dsl.TensorDef(dsl.T, dsl.S.M, dsl.S.N, output=True)):
-    C[dsl.D.m,
-      dsl.D.n] += S[dsl.D.m, dsl.D.n] * A[dsl.D.m, dsl.D.k] * B[dsl.D.k, dsl.D.n]
+  C[dsl.D.m,
+    dsl.D.n] += S[dsl.D.m, dsl.D.n] * A[dsl.D.m, dsl.D.k] * B[dsl.D.k, dsl.D.n]
 
 
 def build_SDDMM(attr: st.EncodingAttr):
-    """Build SDDMM kernel.
+  """Build SDDMM kernel.
 
   This method generates a linalg op with for matrix multiplication using
   just the Python API. Effectively, a generic linalg op is constructed
   that computes C(i,j) += S(i,j) SUM_k A(i,k) B(k,j) for sparse S.
   """
-    module = ir.Module.create()
-    f64 = ir.F64Type.get()
-    a = ir.RankedTensorType.get([8, 8], f64)
-    b = ir.RankedTensorType.get([8, 8], f64)
-    c = ir.RankedTensorType.get([8, 8], f64)
-    s = ir.RankedTensorType.get([8, 8], f64, attr)
-    arguments = [a, b, s, c]
-    with ir.InsertionPoint(module.body):
+  module = ir.Module.create()
+  f64 = ir.F64Type.get()
+  a = ir.RankedTensorType.get([8, 8], f64)
+  b = ir.RankedTensorType.get([8, 8], f64)
+  c = ir.RankedTensorType.get([8, 8], f64)
+  s = ir.RankedTensorType.get([8, 8], f64, attr)
+  arguments = [a, b, s, c]
+  with ir.InsertionPoint(module.body):
 
-        @func.FuncOp.from_py_func(*arguments)
-        def sddmm(*args):
-            return sddmm_dsl(args[0], args[1], args[2], outs=[args[3]])
+    @func.FuncOp.from_py_func(*arguments)
+    def sddmm(*args):
+      return sddmm_dsl(args[0], args[1], args[2], outs=[args[3]])
 
-    return module
+  return module
 
 
 def boilerplate(attr: st.EncodingAttr):
-    """Returns boilerplate code for main driver."""
-    return f"""
+  """Returns boilerplate code for main driver."""
+  return f"""
 func.func @main(%a: tensor<8x8xf64>,
            %b: tensor<8x8xf64>,
            %c: tensor<8x8xf64>) -> tensor<8x8xf64> attributes {{ llvm.emit_c_interface }} {{
@@ -69,98 +69,97 @@ func.func @main(%a: tensor<8x8xf64>,
 
 
 def build_compile_and_run_SDDMMM(attr: st.EncodingAttr, compiler):
-    # Build.
-    module = build_SDDMM(attr)
-    func = str(module.operation.regions[0].blocks[0].operations[0].operation)
-    module = ir.Module.parse(func + boilerplate(attr))
+  # Build.
+  module = build_SDDMM(attr)
+  func = str(module.operation.regions[0].blocks[0].operations[0].operation)
+  module = ir.Module.parse(func + boilerplate(attr))
 
-    # Compile.
-    engine = compiler.compile_and_jit(module)
+  # Compile.
+  engine = compiler.compile_and_jit(module)
 
-    # Set up numpy input and buffer for output.
-    a = np.array([[1.1, 2.1, 3.1, 4.1, 5.1, 6.1, 7.1, 8.1],
-                  [1.2, 2.2, 3.2, 4.2, 5.2, 6.2, 7.2, 8.2],
-                  [1.3, 2.3, 3.3, 4.3, 5.3, 6.3, 7.3, 8.3],
-                  [1.4, 2.4, 3.4, 4.4, 5.4, 6.4, 7.4, 8.4],
-                  [1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5],
-                  [1.6, 2.6, 3.6, 4.6, 5.6, 6.6, 7.6, 8.6],
-                  [1.7, 2.7, 3.7, 4.7, 5.7, 6.7, 7.7, 8.7],
-                  [1.8, 2.8, 3.8, 4.8, 5.8, 6.8, 7.8, 8.8]], np.float64)
-    b = np.ones((8, 8), np.float64)
-    c = np.zeros((8, 8), np.float64)
+  # Set up numpy input and buffer for output.
+  a = np.array([[1.1, 2.1, 3.1, 4.1, 5.1, 6.1, 7.1, 8.1],
+                [1.2, 2.2, 3.2, 4.2, 5.2, 6.2, 7.2, 8.2],
+                [1.3, 2.3, 3.3, 4.3, 5.3, 6.3, 7.3, 8.3],
+                [1.4, 2.4, 3.4, 4.4, 5.4, 6.4, 7.4, 8.4],
+                [1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5],
+                [1.6, 2.6, 3.6, 4.6, 5.6, 6.6, 7.6, 8.6],
+                [1.7, 2.7, 3.7, 4.7, 5.7, 6.7, 7.7, 8.7],
+                [1.8, 2.8, 3.8, 4.8, 5.8, 6.8, 7.8, 8.8]], np.float64)
+  b = np.ones((8, 8), np.float64)
+  c = np.zeros((8, 8), np.float64)
 
-    mem_a = ctypes.pointer(ctypes.pointer(rt.get_ranked_memref_descriptor(a)))
-    mem_b = ctypes.pointer(ctypes.pointer(rt.get_ranked_memref_descriptor(b)))
-    mem_c = ctypes.pointer(ctypes.pointer(rt.get_ranked_memref_descriptor(c)))
+  mem_a = ctypes.pointer(ctypes.pointer(rt.get_ranked_memref_descriptor(a)))
+  mem_b = ctypes.pointer(ctypes.pointer(rt.get_ranked_memref_descriptor(b)))
+  mem_c = ctypes.pointer(ctypes.pointer(rt.get_ranked_memref_descriptor(c)))
 
-    # Allocate a MemRefDescriptor to receive the output tensor.
-    # The buffer itself is allocated inside the MLIR code generation.
-    ref_out = rt.make_nd_memref_descriptor(2, ctypes.c_double)()
-    mem_out = ctypes.pointer(ctypes.pointer(ref_out))
+  # Allocate a MemRefDescriptor to receive the output tensor.
+  # The buffer itself is allocated inside the MLIR code generation.
+  ref_out = rt.make_nd_memref_descriptor(2, ctypes.c_double)()
+  mem_out = ctypes.pointer(ctypes.pointer(ref_out))
 
-    # Invoke the kernel and get numpy output.
-    # Built-in bufferization uses in-out buffers.
-    # TODO: replace with inplace comprehensive bufferization.
-    engine.invoke('main', mem_out, mem_a, mem_b, mem_c)
+  # Invoke the kernel and get numpy output.
+  # Built-in bufferization uses in-out buffers.
+  # TODO: replace with inplace comprehensive bufferization.
+  engine.invoke('main', mem_out, mem_a, mem_b, mem_c)
 
-    # Sanity check on computed result. Only a few elements
-    # are sampled from the full dense matrix multiplication.
-    full_matmul = np.matmul(a, b)
-    expected = np.zeros((8, 8), np.float64)
-    expected[0, 0] = 1.0 * full_matmul[0, 0]
-    expected[0, 2] = 2.0 * full_matmul[0, 2]
-    expected[4, 1] = 3.0 * full_matmul[4, 1]
-    c = rt.ranked_memref_to_numpy(mem_out[0])
-    if np.allclose(c, expected):
-        pass
-    else:
-        quit(f'FAILURE')
+  # Sanity check on computed result. Only a few elements
+  # are sampled from the full dense matrix multiplication.
+  full_matmul = np.matmul(a, b)
+  expected = np.zeros((8, 8), np.float64)
+  expected[0, 0] = 1.0 * full_matmul[0, 0]
+  expected[0, 2] = 2.0 * full_matmul[0, 2]
+  expected[4, 1] = 3.0 * full_matmul[4, 1]
+  c = rt.ranked_memref_to_numpy(mem_out[0])
+  if np.allclose(c, expected):
+    pass
+  else:
+    quit(f'FAILURE')
 
 
 def main():
-    support_lib = os.getenv('SUPPORT_LIB')
-    assert support_lib is not None, 'SUPPORT_LIB is undefined'
-    if not os.path.exists(support_lib):
-        raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT),
-                                support_lib)
+  support_lib = os.getenv('SUPPORT_LIB')
+  assert support_lib is not None, 'SUPPORT_LIB is undefined'
+  if not os.path.exists(support_lib):
+    raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT),
+                            support_lib)
 
-    # CHECK-LABEL: TEST: testSDDMMM
-    print('\nTEST: testSDDMMM')
-    with ir.Context() as ctx, ir.Location.unknown():
-        count = 0
-        # Loop over various ways to compile and annotate the SDDMM kernel with
-        # a *single* sparse tensor. Note that we deliberate do not exhaustively
-        # search the full state space to reduce runtime of the test. It is
-        # straightforward to adapt the code below to explore more combinations.
-        levels = [[st.DimLevelType.dense, st.DimLevelType.dense],
-                  [st.DimLevelType.dense, st.DimLevelType.compressed],
-                  [st.DimLevelType.compressed, st.DimLevelType.dense],
-                  [st.DimLevelType.compressed, st.DimLevelType.compressed]]
-        orderings = [
-            ir.AffineMap.get_permutation([0, 1]),
-            ir.AffineMap.get_permutation([1, 0])
-        ]
-        vec_strategy = [
+  # CHECK-LABEL: TEST: testSDDMMM
+  print('\nTEST: testSDDMMM')
+  with ir.Context() as ctx, ir.Location.unknown():
+    count = 0
+    # Loop over various ways to compile and annotate the SDDMM kernel with
+    # a *single* sparse tensor. Note that we deliberate do not exhaustively
+    # search the full state space to reduce runtime of the test. It is
+    # straightforward to adapt the code below to explore more combinations.
+    levels = [[st.DimLevelType.dense, st.DimLevelType.dense],
+              [st.DimLevelType.dense, st.DimLevelType.compressed],
+              [st.DimLevelType.compressed, st.DimLevelType.dense],
+              [st.DimLevelType.compressed, st.DimLevelType.compressed]]
+    orderings = [
+        ir.AffineMap.get_permutation([0, 1]),
+        ir.AffineMap.get_permutation([1, 0])
+    ]
+    vec_strategy = [
           'none', 'dense-inner-loop'
-        ]
-        for level in levels:
-            for ordering in orderings:
-                for pwidth in [32]:
-                    for iwidth in [32]:
-                        for vec in vec_strategy:
-                            for e in [True]:
-                                vl = 1 if vec == 0 else 16
-                                attr = st.EncodingAttr.get(level, ordering, pwidth, iwidth)
-                                opt = (f'parallelization-strategy=none '
-                                       f'vectorization-strategy={vec} '
-                                       f'vl={vl} enable-simd-index32={e}')
-                                compiler = sparse_compiler.SparseCompiler(
-                                    options=opt, opt_level=0, shared_libs=[support_lib])
-                                build_compile_and_run_SDDMMM(attr, compiler)
-                                count = count + 1
-    # CHECK: Passed 16 tests
-    print('Passed ', count, 'tests')
+        ]for level in levels:
+      for ordering in orderings:
+        for pwidth in [32]:
+          for iwidth in [32]:
+            for vec in vec_strategy:
+                for e in [True]:
+                  vl = 1 if vec == 0 else 16
+                  attr = st.EncodingAttr.get(level, ordering, pwidth, iwidth)
+                  opt = (f'parallelization-strategy=none '
+                         f'vectorization-strategy={vec} '
+                         f'vl={vl} enable-simd-index32={e}')
+                  compiler = sparse_compiler.SparseCompiler(
+                      options=opt, opt_level=0, shared_libs=[support_lib])
+                  build_compile_and_run_SDDMMM(attr, compiler)
+                  count = count + 1
+  # CHECK: Passed 16 tests
+  print('Passed ', count, 'tests')
 
 
 if __name__ == '__main__':
-    main()
+  main()

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

@@ -1,4 +1,4 @@
-# RUN: SUPPORT_LIB=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext \
+# RUN: SUPPORT_LIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext \
 # RUN:   %PYTHON %s | FileCheck %s
 
 import ctypes
@@ -23,40 +23,40 @@ def matmul_dsl(
     A=dsl.TensorDef(dsl.T, dsl.S.M, dsl.S.K),
     B=dsl.TensorDef(dsl.T, dsl.S.K, dsl.S.N),
     C=dsl.TensorDef(dsl.T, dsl.S.M, dsl.S.N, output=True)):
-    C[dsl.D.m, dsl.D.n] += A[dsl.D.m, dsl.D.k] * B[dsl.D.k, dsl.D.n]
+  C[dsl.D.m, dsl.D.n] += A[dsl.D.m, dsl.D.k] * B[dsl.D.k, dsl.D.n]
 
 
 def build_SpMM(attr: st.EncodingAttr):
-    """Build SpMM kernel.
+  """Build SpMM kernel.
 
   This method generates a linalg op with for matrix multiplication using
   just the Python API. Effectively, a generic linalg op is constructed
   that computes C(i,j) += A(i,k) * B(k,j) for annotated matrix A.
   """
-    module = ir.Module.create()
-    f64 = ir.F64Type.get()
-    a = ir.RankedTensorType.get([3, 4], f64, attr)
-    b = ir.RankedTensorType.get([4, 2], f64)
-    c = ir.RankedTensorType.get([3, 2], f64)
-    arguments = [a, b, c]
-    with ir.InsertionPoint(module.body):
+  module = ir.Module.create()
+  f64 = ir.F64Type.get()
+  a = ir.RankedTensorType.get([3, 4], f64, attr)
+  b = ir.RankedTensorType.get([4, 2], f64)
+  c = ir.RankedTensorType.get([3, 2], f64)
+  arguments = [a, b, c]
+  with ir.InsertionPoint(module.body):
 
-        @func.FuncOp.from_py_func(*arguments)
-        def spMxM(*args):
-            return matmul_dsl(args[0], args[1], outs=[args[2]])
+    @func.FuncOp.from_py_func(*arguments)
+    def spMxM(*args):
+      return matmul_dsl(args[0], args[1], outs=[args[2]])
 
-    return module
+  return module
 
 
 def boilerplate(attr: st.EncodingAttr):
-    """Returns boilerplate main method.
+  """Returns boilerplate main method.
 
   This method sets up a boilerplate main method that takes three tensors
   (a, b, c), converts the first tensor a into s sparse tensor, and then
   calls the sparse kernel for matrix multiplication. For convenience,
   this part is purely done as string input.
   """
-    return f"""
+  return f"""
 func.func @main(%ad: tensor<3x4xf64>, %b: tensor<4x2xf64>, %c: tensor<3x2xf64>) -> tensor<3x2xf64>
   attributes {{ llvm.emit_c_interface }} {{
   %a = sparse_tensor.convert %ad : tensor<3x4xf64> to tensor<3x4xf64, {attr}>
@@ -69,83 +69,84 @@ func.func @main(%ad: tensor<3x4xf64>, %b: tensor<4x2xf64>, %c: tensor<3x2xf64>)
 
 
 def build_compile_and_run_SpMM(attr: st.EncodingAttr, compiler):
-    # Build.
-    module = build_SpMM(attr)
-    func = str(module.operation.regions[0].blocks[0].operations[0].operation)
-    module = ir.Module.parse(func + boilerplate(attr))
+  # Build.
+  module = build_SpMM(attr)
+  func = str(module.operation.regions[0].blocks[0].operations[0].operation)
+  module = ir.Module.parse(func + boilerplate(attr))
 
-    # Compile.
-    engine = compiler.compile_and_jit(module)
+  # Compile.
+  engine = compiler.compile_and_jit(module)
 
-    # Set up numpy input and buffer for output.
-    a = np.array(
-        [[1.1, 0.0, 0.0, 1.4], [0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 3.3, 0.0]],
-        np.float64)
-    b = np.array([[1.0, 2.0], [4.0, 3.0], [5.0, 6.0], [8.0, 7.0]], np.float64)
-    c = np.zeros((3, 2), np.float64)
+  # Set up numpy input and buffer for output.
+  a = np.array(
+      [[1.1, 0.0, 0.0, 1.4], [0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 3.3, 0.0]],
+      np.float64)
+  b = np.array([[1.0, 2.0], [4.0, 3.0], [5.0, 6.0], [8.0, 7.0]], np.float64)
+  c = np.zeros((3, 2), np.float64)
 
-    mem_a = ctypes.pointer(ctypes.pointer(rt.get_ranked_memref_descriptor(a)))
-    mem_b = ctypes.pointer(ctypes.pointer(rt.get_ranked_memref_descriptor(b)))
-    mem_c = ctypes.pointer(ctypes.pointer(rt.get_ranked_memref_descriptor(c)))
-    # Allocate a MemRefDescriptor to receive the output tensor.
-    # The buffer itself is allocated inside the MLIR code generation.
-    ref_out = rt.make_nd_memref_descriptor(2, ctypes.c_double)()
-    mem_out = ctypes.pointer(ctypes.pointer(ref_out))
+  mem_a = ctypes.pointer(ctypes.pointer(rt.get_ranked_memref_descriptor(a)))
+  mem_b = ctypes.pointer(ctypes.pointer(rt.get_ranked_memref_descriptor(b)))
+  mem_c = ctypes.pointer(ctypes.pointer(rt.get_ranked_memref_descriptor(c)))
+  # Allocate a MemRefDescriptor to receive the output tensor.
+  # The buffer itself is allocated inside the MLIR code generation.
+  ref_out = rt.make_nd_memref_descriptor(2, ctypes.c_double)()
+  mem_out = ctypes.pointer(ctypes.pointer(ref_out))
 
-    # Invoke the kernel and get numpy output.
-    # Built-in bufferization uses in-out buffers.
-    # TODO: replace with inplace comprehensive bufferization.
-    engine.invoke('main', mem_out, mem_a, mem_b, mem_c)
+  # Invoke the kernel and get numpy output.
+  # Built-in bufferization uses in-out buffers.
+  # TODO: replace with inplace comprehensive bufferization.
+  engine.invoke('main', mem_out, mem_a, mem_b, mem_c)
 
-    # Sanity check on computed result.
-    expected = np.matmul(a, b);
-    c = rt.ranked_memref_to_numpy(mem_out[0])
-    if np.allclose(c, expected):
-        pass
-    else:
-        quit(f'FAILURE')
+  # Sanity check on computed result.
+  expected = np.matmul(a, b);
+  c = rt.ranked_memref_to_numpy(mem_out[0])
+  if np.allclose(c, expected):
+    pass
+  else:
+    quit(f'FAILURE')
 
 
 def main():
-    support_lib = os.getenv('SUPPORT_LIB')
-    assert support_lib is not None, 'SUPPORT_LIB is undefined'
-    if not os.path.exists(support_lib):
-        raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), support_lib)
+  support_lib = os.getenv('SUPPORT_LIB')
+  assert support_lib is not None, 'SUPPORT_LIB is undefined'
+  if not os.path.exists(support_lib):
+    raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), support_lib)
 
-    # CHECK-LABEL: TEST: testSpMM
-    print('\nTEST: testSpMM')
-    with ir.Context() as ctx, ir.Location.unknown():
-        count = 0
-        # Loop over various ways to compile and annotate the SpMM kernel with
-        # a *single* sparse tensor. Note that we deliberate do not exhaustively
-        # search the full state space to reduce runtime of the test. It is
-        # straightforward to adapt the code below to explore more combinations.
-        vl = 1
-        e = False
-        opt = (f'parallelization-strategy=none '
-               f'vectorization-strategy=none '
-               f'vl={vl} enable-simd-index32={e}')
-        levels = [[st.DimLevelType.dense, st.DimLevelType.dense],
-                  [st.DimLevelType.dense, st.DimLevelType.compressed],
-                  [st.DimLevelType.compressed, st.DimLevelType.dense],
-                  [st.DimLevelType.compressed, st.DimLevelType.compressed]]
-        orderings = [
-            ir.AffineMap.get_permutation([0, 1]),
-            ir.AffineMap.get_permutation([1, 0])
-        ]
-        bitwidths = [0]
-        compiler = sparse_compiler.SparseCompiler(
-            options=opt, opt_level=0, shared_libs=[support_lib])
-        for level in levels:
-            for ordering in orderings:
-                for pwidth in bitwidths:
-                    for iwidth in bitwidths:
-                        attr = st.EncodingAttr.get(level, ordering, pwidth, iwidth)
-                        build_compile_and_run_SpMM(attr, compiler)
-                        count = count + 1
-        # CHECK: Passed 8 tests
-        print('Passed ', count, 'tests')
+  # CHECK-LABEL: TEST: testSpMM
+  print('\nTEST: testSpMM')
+  with ir.Context() as ctx, ir.Location.unknown():
+    count = 0
+    # Loop over various ways to compile and annotate the SpMM kernel with
+    # a *single* sparse tensor. Note that we deliberate do not exhaustively
+    # search the full state space to reduce runtime of the test. It is
+    # straightforward to adapt the code below to explore more combinations.
+
+    vl = 1
+    e = False
+    opt = (f'parallelization-strategy=none '
+           f'vectorization-strategy=none '
+           f'vl={vl} enable-simd-index32={e}')
+    levels = [[st.DimLevelType.dense, st.DimLevelType.dense],
+              [st.DimLevelType.dense, st.DimLevelType.compressed],
+              [st.DimLevelType.compressed, st.DimLevelType.dense],
+              [st.DimLevelType.compressed, st.DimLevelType.compressed]]
+    orderings = [
+        ir.AffineMap.get_permutation([0, 1]),
+        ir.AffineMap.get_permutation([1, 0])
+    ]
+    bitwidths = [0]
+    compiler = sparse_compiler.SparseCompiler(
+        options=opt, opt_level=0, shared_libs=[support_lib])
+    for level in levels:
+      for ordering in orderings:
+        for pwidth in bitwidths:
+          for iwidth in bitwidths:
+            attr = st.EncodingAttr.get(level, ordering, pwidth, iwidth)
+            build_compile_and_run_SpMM(attr, compiler)
+            count = count + 1
+    # CHECK: Passed 8 tests
+    print('Passed ', count, 'tests')
 
 
 if __name__ == '__main__':
-    main()
+  main()

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

@@ -1,4 +1,4 @@
-# RUN: SUPPORT_LIB=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: SUPPORT_LIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
 
 import ctypes
 import numpy as np

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

@@ -1,4 +1,4 @@
-# RUN: SUPPORT_LIB=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext \
+# RUN: SUPPORT_LIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext \
 # RUN:   %PYTHON %s | FileCheck %s
 
 import ctypes
@@ -18,8 +18,8 @@ from tools import sparse_compiler
 
 # TODO: move more into actual IR building.
 def boilerplate(attr: st.EncodingAttr):
-    """Returns boilerplate main method."""
-    return f"""
+  """Returns boilerplate main method."""
+  return f"""
 func.func @main(%p : !llvm.ptr<i8>) -> () 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>
@@ -31,13 +31,13 @@ func.func @main(%p : !llvm.ptr<i8>) -> () attributes {{ llvm.emit_c_interface }}
 
 
 def expected():
-    """Returns expected contents of output.
+  """Returns expected contents of output.
 
   Regardless of the dimension ordering, compression, and bitwidths that are
   used in the sparse tensor, the output is always lexicographically sorted
   by natural index order.
   """
-    return f"""; extended FROSTT format
+  return f"""; extended FROSTT format
 2 5
 10 10
 1 1 1
@@ -49,53 +49,53 @@ def expected():
 
 
 def build_compile_and_run_output(attr: st.EncodingAttr, compiler):
-    # Build and Compile.
-    module = ir.Module.parse(boilerplate(attr))
-    engine = compiler.compile_and_jit(module)
+  # Build and Compile.
+  module = ir.Module.parse(boilerplate(attr))
+  engine = compiler.compile_and_jit(module)
 
-    # Invoke the kernel and compare output.
-    with tempfile.TemporaryDirectory() as test_dir:
-        out = os.path.join(test_dir, 'out.tns')
-        buf = out.encode('utf-8')
-        mem_a = ctypes.pointer(ctypes.pointer(ctypes.create_string_buffer(buf)))
-        engine.invoke('main', mem_a)
+  # Invoke the kernel and compare output.
+  with tempfile.TemporaryDirectory() as test_dir:
+    out = os.path.join(test_dir, 'out.tns')
+    buf = out.encode('utf-8')
+    mem_a = ctypes.pointer(ctypes.pointer(ctypes.create_string_buffer(buf)))
+    engine.invoke('main', mem_a)
 
-        actual = open(out).read()
-        if actual != expected():
-            quit('FAILURE')
+    actual = open(out).read()
+    if actual != expected():
+      quit('FAILURE')
 
 
 def main():
-    support_lib = os.getenv('SUPPORT_LIB')
-    assert support_lib is not None, 'SUPPORT_LIB is undefined'
-    if not os.path.exists(support_lib):
-        raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT),
-                                support_lib)
+  support_lib = os.getenv('SUPPORT_LIB')
+  assert support_lib is not None, 'SUPPORT_LIB is undefined'
+  if not os.path.exists(support_lib):
+    raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT),
+                            support_lib)
 
-    # CHECK-LABEL: TEST: test_output
-    print('\nTEST: test_output')
-    count = 0
-    with ir.Context() as ctx, ir.Location.unknown():
-        # Loop over various sparse types: CSR, DCSR, CSC, DCSC.
-        levels = [[st.DimLevelType.dense, st.DimLevelType.compressed],
-                  [st.DimLevelType.compressed, st.DimLevelType.compressed]]
-        orderings = [
-            ir.AffineMap.get_permutation([0, 1]),
-            ir.AffineMap.get_permutation([1, 0])
-        ]
-        bitwidths = [8, 16, 32, 64]
-        compiler = sparse_compiler.SparseCompiler(
-            options='', opt_level=2, shared_libs=[support_lib])
-        for level in levels:
-            for ordering in orderings:
-                for bwidth in bitwidths:
-                    attr = st.EncodingAttr.get(level, ordering, bwidth, bwidth)
-                    build_compile_and_run_output(attr, compiler)
-                    count = count + 1
+  # CHECK-LABEL: TEST: test_output
+  print('\nTEST: test_output')
+  count = 0
+  with ir.Context() as ctx, ir.Location.unknown():
+    # Loop over various sparse types: CSR, DCSR, CSC, DCSC.
+    levels = [[st.DimLevelType.dense, st.DimLevelType.compressed],
+              [st.DimLevelType.compressed, st.DimLevelType.compressed]]
+    orderings = [
+        ir.AffineMap.get_permutation([0, 1]),
+        ir.AffineMap.get_permutation([1, 0])
+    ]
+    bitwidths = [8, 16, 32, 64]
+    compiler = sparse_compiler.SparseCompiler(
+        options='', opt_level=2, shared_libs=[support_lib])
+    for level in levels:
+      for ordering in orderings:
+        for bwidth in bitwidths:
+          attr = st.EncodingAttr.get(level, ordering, bwidth, bwidth)
+          build_compile_and_run_output(attr, compiler)
+          count = count + 1
 
-    # CHECK: Passed 16 tests
-    print('Passed', count, 'tests')
+  # CHECK: Passed 16 tests
+  print('Passed', count, 'tests')
 
 
 if __name__ == '__main__':
-    main()
+  main()

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

@@ -1,4 +1,4 @@
-# RUN: SUPPORT_LIB=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext \
+# RUN: SUPPORT_LIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext \
 # RUN:   %PYTHON %s | FileCheck %s
 
 import ctypes

mlir/test/Integration/Dialect/SparseTensor/taco/test_MTTKRP.py

@@ -1,4 +1,4 @@
-# RUN: SUPPORTLIB=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
 
 import numpy as np
 import os

mlir/test/Integration/Dialect/SparseTensor/taco/test_SDDMM.py

@@ -1,4 +1,4 @@
-# RUN: SUPPORTLIB=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
 
 import filecmp
 import numpy as np

mlir/test/Integration/Dialect/SparseTensor/taco/test_SpMM.py

@@ -1,4 +1,4 @@
-# RUN: SUPPORTLIB=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
 
 import filecmp
 import numpy as np

mlir/test/Integration/Dialect/SparseTensor/taco/test_SpMV.py

@@ -1,4 +1,4 @@
-# RUN: SUPPORTLIB=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
 
 import numpy as np
 import os

mlir/test/Integration/Dialect/SparseTensor/taco/test_Tensor.py

@@ -1,4 +1,4 @@
-# RUN: SUPPORTLIB=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
 
 import filecmp
 import numpy as np

mlir/test/Integration/Dialect/SparseTensor/taco/test_scalar_tensor_algebra.py

@@ -1,4 +1,4 @@
-# RUN: SUPPORTLIB=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
 
 import numpy as np
 import os

mlir/test/Integration/Dialect/SparseTensor/taco/test_simple_tensor_algebra.py

@@ -1,4 +1,4 @@
-# RUN: SUPPORTLIB=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
 
 import numpy as np
 import os

mlir/test/Integration/Dialect/SparseTensor/taco/test_tensor_complex.py

@@ -1,4 +1,4 @@
-# RUN: SUPPORTLIB=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
 import numpy as np
 import os
 import sys

mlir/test/Integration/Dialect/SparseTensor/taco/test_tensor_types.py

@@ -1,4 +1,4 @@
-# RUN: SUPPORTLIB=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
 
 import numpy as np
 import os

mlir/test/Integration/Dialect/SparseTensor/taco/test_tensor_unary_ops.py

@@ -1,4 +1,4 @@
-# RUN: SUPPORTLIB=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
 
 import numpy as np
 import os

mlir/test/Integration/Dialect/SparseTensor/taco/test_true_dense_tensor_algebra.py

@@ -1,4 +1,4 @@
-# RUN: SUPPORTLIB=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
 
 import numpy as np
 import os

mlir/test/Integration/Dialect/SparseTensor/taco/unit_test_tensor_core.py

@@ -1,4 +1,4 @@
-# RUN: SUPPORTLIB=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
 
 from string import Template
 

mlir/test/Integration/Dialect/SparseTensor/taco/unit_test_tensor_io.py

@@ -1,4 +1,4 @@
-# RUN: SUPPORTLIB=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
 
 from string import Template
 

mlir/test/Integration/Dialect/SparseTensor/taco/unit_test_tensor_utils.py

@@ -1,4 +1,4 @@
-# RUN: SUPPORTLIB=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
 
 from typing import Sequence
 import dataclasses

mlir/test/Integration/Dialect/Standard/CPU/test-ceil-floor-pos-neg.mlir

@@ -1,6 +1,6 @@
 // RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf,memref-expand,arith-expand),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 func.func @transfer_read_2d(%A : memref<40xi32>, %base1: index) {

mlir/test/Integration/Dialect/Standard/CPU/test_subview.mlir

@@ -1,6 +1,6 @@
 // RUN: mlir-opt %s -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext | FileCheck %s
+// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext | FileCheck %s
 
 memref.global "private" constant @__constant_5x3xf32 : memref<5x3xf32> =
 dense<[[0.0, 1.0, 2.0],

mlir/test/Integration/Dialect/Vector/CPU/AMX/test-mulf-full.mlir

@@ -3,7 +3,7 @@
 // RUN:  -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-translate -mlir-to-llvmir | \
 // RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" \
-// RUN:  --dlopen=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  --dlopen=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 // Note: To run this test, your CPU must support AMX.

mlir/test/Integration/Dialect/Vector/CPU/AMX/test-mulf.mlir

@@ -1,6 +1,6 @@
 // RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf -convert-vector-to-llvm="enable-amx" -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-translate -mlir-to-llvmir | \
-// RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 // Note: To run this test, your CPU must support AMX.