[mlir][sparse] unifies sparse_tensor.sort_coo/sort into one operation. (#66722)

The use cases of the two operations are largely overlapped, let's
simplify it and only use one of them.

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

@@ -890,8 +890,9 @@ public:
     // If the innermost level is ordered, we need to sort the coordinates
     // in the "added" array prior to applying the compression.
     if (dstType.isOrderedLvl(dstType.getLvlRank() - 1))
-      rewriter.create<SortOp>(loc, count, ValueRange{added}, ValueRange{},
-                              SparseTensorSortKind::HybridQuickSort);
+      rewriter.create<SortCooOp>(
+          loc, count, added, ValueRange{}, rewriter.getMultiDimIdentityMap(1),
+          rewriter.getIndexAttr(0), SparseTensorSortKind::HybridQuickSort);
     // While performing the insertions, we also need to reset the elements
     // of the values/filled-switch by only iterating over the set elements,
     // to ensure that the runtime complexity remains proportional to the
@@ -1486,9 +1487,10 @@ struct SparseNewOpConverter : public OpConversionPattern<NewOp> {
       scf::IfOp ifOp =
           rewriter.create<scf::IfOp>(loc, notSorted, /*else*/ false);
       rewriter.setInsertionPointToStart(&ifOp.getThenRegion().front());
-      rewriter.create<SortCooOp>(
-          loc, nse, xs, ValueRange{ys}, rewriter.getIndexAttr(lvlRank),
-          rewriter.getIndexAttr(0), SparseTensorSortKind::HybridQuickSort);
+      auto xPerm = rewriter.getMultiDimIdentityMap(lvlRank);
+      rewriter.create<SortCooOp>(loc, nse, xs, ValueRange{ys}, xPerm,
+                                 rewriter.getIndexAttr(0),
+                                 SparseTensorSortKind::HybridQuickSort);
       rewriter.setInsertionPointAfter(ifOp);
     }