[mlir][sparse] Change getUnorderedCOOFromType to propagate the overhead types.

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

static RankedTensorType getUnorderedCOOFromType(RankedTensorType src) {
   // TODO: it is actually ordered at the level for ordered input.
   // Followed by unordered non-unique n-2 singleton levels.
   std::fill_n(std::back_inserter(dims), rank - 2,
               SparseTensorEncodingAttr::DimLevelType::SingletonNuNo);
   // TODO: only if all the inputs (for concatentate) are unique at the last
   // level should the COO has a unique level at the end. Ends by a unordered
   // unique singleton level.
   dims.push_back(SparseTensorEncodingAttr::DimLevelType::SingletonNo);
+  SparseTensorEncodingAttr encSrc = getSparseTensorEncoding(src);
   // TODO: Maybe pick the bitwidth based on input/output tensors (probably the
   // largest one among them) in the original operation instead of using the
   // default value.
   auto enc = SparseTensorEncodingAttr::get(
-      ctx, dims, AffineMap::getMultiDimIdentityMap(rank, ctx), AffineMap(), 0,
-      0);
+      ctx, dims, AffineMap::getMultiDimIdentityMap(rank, ctx), AffineMap(),
+      encSrc.getPointerBitWidth(), encSrc.getIndexBitWidth());
   return RankedTensorType::get(src.getShape(), src.getElementType(), enc);
 }
 
 //===---------------------------------------------------------------------===//
 // The actual sparse tensor rewriting rules.
 //===---------------------------------------------------------------------===//
 
 namespace {