[mlir][sparse][NFC] Add comments to tests that are run for with and without runtime libraries.

[aartbik]

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

8

super, super, nit, but can you add a // after this so it jump out more
(as done elsewhere too)

[bixia]

Add // to connect the commands for the two runs.

mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorRewriting.cpp

if (!isUniqueCOOType(srcTp)) {
             // The resulting COO tensor has identity ordering.
             auto t = builder.create<InsertOp>(loc, v, reduc.front(),
                                               args.slice(0, srcTp.getRank()));
             builder.create<sparse_tensor::YieldOp>(loc, t);
           });
       src = rewriter.create<LoadOp>(loc, foreachOp.getResult(0), true);
     }
 
-    SparseTensorEncodingAttr encSrc = getSparseTensorEncoding(srcTp);
     // Sort the COO tensor so that its elements are ordered via increasing
     // indices for the storage ordering of the dst tensor.
+    SparseTensorEncodingAttr encSrc = getSparseTensorEncoding(srcTp);
     auto dynShape = {ShapedType::kDynamicSize};
     auto indTp =
         MemRefType::get(dynShape, getIndexOverheadType(rewriter, encSrc));
     uint64_t rank = dstTp.getRank();
     // Gather the indices-arrays in the dst tensor storage order.
     SmallVector<Value, 4> xs(rank, Value());
     for (uint64_t i = 0; i < rank; i++) {
       uint64_t orgDim = toOrigDim(encSrc, i);

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

 // RUN: mlir-opt %s --sparse-compiler=enable-runtime-library=true | \
 // 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_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
+// Do the same run, but now with direct IR generation.
 // RUN: mlir-opt %s --sparse-compiler=enable-runtime-library=false | \
 // 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_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 !Filename = !llvm.ptr<i8>

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

 // RUN: mlir-opt %s --sparse-compiler=enable-runtime-library=true | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
+// Do the same run, but now with direct IR generation.
 // RUN: mlir-opt %s --sparse-compiler=enable-runtime-library=false | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 // UNSUPPORTED: aarch64
 

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

 // RUN: mlir-opt %s --sparse-compiler=enable-runtime-library=true | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
+// Do the same run, but now with direct IR generation.
 // RUN: mlir-opt %s --sparse-compiler=enable-runtime-library=false | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>
 #DenseVector = #sparse_tensor.encoding<{dimLevelType = ["dense"]}>

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

 // RUN: mlir-opt %s --sparse-compiler=enable-runtime-library=true | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
+// Do the same run, but now with direct IR generation.
 // RUN: mlir-opt %s --sparse-compiler=enable-runtime-library=false | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #Row = #sparse_tensor.encoding<{
   dimLevelType = [ "compressed", "dense" ]

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

 // RUN: mlir-opt %s --sparse-compiler=enable-runtime-library=true | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
+// Do the same run, but now with direct IR generation.
 // RUN: mlir-opt %s --sparse-compiler="enable-runtime-library=false enable-buffer-initialization=true" | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // 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_conversion_ptr.mlir

 // RUN: mlir-opt %s --sparse-compiler=enable-runtime-library=true | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
+// Do the same run, but now with direct IR generation.
 // RUN: mlir-opt %s --sparse-compiler="enable-runtime-library=false enable-buffer-initialization=true" | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // 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_matrix_ops.mlir

 // RUN: mlir-opt %s --sparse-compiler=enable-runtime-library=true | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
+// Do the same run, but now with direct IR generation.
 // RUN: mlir-opt %s --sparse-compiler=enable-runtime-library=false | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // 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_out_mult_elt.mlir

 // RUN: mlir-opt %s --sparse-compiler=enable-runtime-library=true | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
+// Do the same run, but now with direct IR generation.
 // RUN: mlir-opt %s --sparse-compiler="enable-runtime-library=false enable-buffer-initialization=true"| \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // 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_out_reduction.mlir

 // RUN: mlir-opt %s --sparse-compiler=enable-runtime-library=true | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
+// Do the same run, but now with direct IR generation.
 // RUN: mlir-opt %s --sparse-compiler="enable-runtime-library=false enable-buffer-initialization=true"| \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseMatrix = #sparse_tensor.encoding<{
   dimLevelType = [ "compressed", "compressed" ]

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

 // RUN: mlir-opt %s --sparse-compiler="enable-runtime-library=true" | \
 // RUN: TENSOR0="%mlir_src_dir/test/Integration/data/wide.mtx" \
 // RUN: TENSOR1="%mlir_src_dir/test/Integration/data/mttkrp_b.tns" \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
+// Do the same run, but now with direct IR generation.
 // RUN: mlir-opt %s --sparse-compiler="enable-runtime-library=false enable-buffer-initialization=true" | \
 // RUN: TENSOR0="%mlir_src_dir/test/Integration/data/wide.mtx" \
 // RUN: TENSOR1="%mlir_src_dir/test/Integration/data/mttkrp_b.tns" \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 

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

 // RUN: mlir-opt %s --sparse-compiler=enable-runtime-library=true | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
+// Do the same run, but now with direct IR generation.
 // RUN: mlir-opt %s --sparse-compiler=enable-runtime-library=false | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 //
 // Several common sparse storage schemes.