p.Pos = p.Pos.WithNotStmt()
	}
	return p
}

// Pc returns the current Prog.
func (s *State) Pc() *obj.Prog {
	return s.pp.Next
}

// SetPos sets the current source position.
func (s *State) SetPos(pos src.XPos) {
	s.pp.Pos = pos
}

// Br emits a single branch instruction and returns the instruction.
// Not all architectures need the returned instruction, but otherwise

	if v < 0 {
		return false
	}
	if (v & 0xFFF) == 0 {
		v >>= 12
	}
	return v <= 0xFFF
}

// setPos sets the position of v to pos, then returns true.
// Useful for setting the result of a rewrite's position to
// something other than the default.
func setPos(v *Value, pos src.XPos) bool {
	v.Pos = pos
	return true

    return CartesianSet.create(sets);
  }

  /**
   * Returns every possible list that can be formed by choosing one element from each of the given
   * sets in order; the "n-ary <a href="http://en.wikipedia.org/wiki/Cartesian_product">Cartesian
   * product</a>" of the sets. For example:
   *
   * <pre>{@code
   * Sets.cartesianProduct(

			manager := newTestVolumeManager(t, tmpDir, podManager, kubeClient, node)

			stopCh := runVolumeManager(manager)
			defer close(stopCh)

			podManager.SetPods([]*v1.Pod{pod})

			// Fake node status update
			go simulateVolumeInUseUpdate(
				v1.UniqueVolumeName(node.Status.VolumesAttached[0].Name),
				stopCh,
				manager)

          if (TF::TensorListSetItemOp set_op =
                  llvm::dyn_cast<TF::TensorListSetItemOp>(use.getOwner())) {
            element_shape = rewriter.create<TF::ShapeOp>(
                op.getLoc(),
                tensorflow::GetTypeFromTFTensorShape({-1}, shape_dtype),
                set_op.getItem());
            element_shape_acquired = true;

  if (!name.empty())
    node_def->set_name(std::string(ParseTensorName(name.str()).node()));
  else
    node_def->set_name(
        std::string(op_to_name_.GetUniqueName(func.getName().str())));

  node_def->set_op(FunctionLibraryDefinition::kArgOp);

  mlir::TensorType arg_type = mlir::cast<mlir::TensorType>(arg.getType());
  if (auto resource_type =
          mlir::dyn_cast<mlir::TF::ResourceType>(arg_type.getElementType())) {