[MLIR] Fix use-after-move for DEBUG builds

Fix use-after-move issues that occur only in DEBUG builds.

In one, constructor arguments are moved in the initializer list to initialize member variables, but the function body mistakenly accesses the moved-from arguments instead of the corresponding class members with identical names.
While this is a UB, here it actually renders the affected asserts ineffective, since the comparisons operate on two hollowed-out objects, by implementation.

In a second fix, a variable is moved from within an assert, introducing a side effect that alters its subsequent use and causes divergence between DEBUG and RELEASE builds.

Testing:
ninja check-llvm
ninja check-llvm-unit

Author: noclowns

mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensor.h

@@ -158,16 +158,14 @@ namespace sparse_tensor {
 /// Convenience method to abbreviate casting `getType()`.
 template <typename T>
 inline RankedTensorType getRankedTensorType(T &&t) {
-  assert(static_cast<bool>(std::forward<T>(t)) &&
-         "getRankedTensorType got null argument");
+  assert(static_cast<bool>(t) && "getRankedTensorType got null argument");
   return dyn_cast<RankedTensorType>(std::forward<T>(t).getType());
 }
 
 /// Convenience method to abbreviate casting `getType()`.
 template <typename T>
 inline MemRefType getMemRefType(T &&t) {
-  assert(static_cast<bool>(std::forward<T>(t)) &&
-         "getMemRefType got null argument");
+  assert(static_cast<bool>(t) && "getMemRefType got null argument");
   return cast<MemRefType>(std::forward<T>(t).getType());
 }
 

mlir/lib/Dialect/SparseTensor/Transforms/Utils/IterationGraphSorter.cpp

@@ -159,12 +159,12 @@ IterationGraphSorter::IterationGraphSorter(
       loop2OutLvl(loop2OutLvl), iterTypes(std::move(iterTypes)),
       strategy(strategy) {
   // One map per tensor.
-  assert(loop2InsLvl.size() == ins.size());
+  assert(this->loop2InsLvl.size() == this->ins.size());
   // All the affine maps have the same number of dimensions (loops).
   assert(llvm::all_equal(llvm::map_range(
-      loop2InsLvl, [](AffineMap m) { return m.getNumDims(); })));
+      this->loop2InsLvl, [](AffineMap m) { return m.getNumDims(); })));
   // The number of results of the map should match the rank of the tensor.
-  assert(llvm::all_of(llvm::zip(loop2InsLvl, ins), [](auto mvPair) {
+  assert(llvm::all_of(llvm::zip(this->loop2InsLvl, this->ins), [](auto mvPair) {
     auto [m, v] = mvPair;
     return m.getNumResults() == cast<ShapedType>(v.getType()).getRank();
   }));