GetObject() runtime.Object
	// GetOldObject is the existing object. Only populated for UPDATE and DELETE requests.
	GetOldObject() runtime.Object
	// GetKind is the type of object being manipulated.  For example: Pod
	GetKind() schema.GroupVersionKind
	// GetUserInfo is information about the requesting user
	GetUserInfo() user.Info

     */
    default void validatePropertyMetadata(PropertyMetadata propertyMetadata, TypeValidationContext validationContext) {}

    /**
     * Returns the kind of properties this handler handles.
     */
    Kind getKind();

    enum Kind {
        INPUT, OUTPUT, OTHER
    }

        return annotatedClassElements
            .flatMap(element -> element.getKind() == ElementKind.METHOD ? Stream.of(element) : element.getEnclosedElements().stream())
            .filter(it -> it.getKind() == ElementKind.METHOD)
            .map(it -> (ExecutableElement) it)

      op->getLoc(), op->getResultTypes(), op->getOperands(),
      while_op.getIsStateless());
  Location loc = while_op->getLoc();
  CreateRegionWithCall(while_op.cond_function(), new_op.getCond(), loc);
  CreateRegionWithCall(while_op.body_function(), new_op.getBody(), loc);

  op->replaceAllUsesWith(new_op.getResults());
  op->erase();
}

void LegalizeWhilePass::RunOnFunction(func::FuncOp func) {

        }
        Set<String> typeNames = new LinkedHashSet<>();
        for (Element element : originatingElements) {
            // TODO: Support for modules
            if (!element.getKind().name().equals("MODULE")) {
                String topLevelTypeName = getTopLevelTypeName(element);
                typeNames.add(topLevelTypeName);
            }
        }
        return typeNames;
    }

        op_builder->create<mlir::arith::ConstantOp>(
            const_op->getLoc(),
            DenseIntElementsAttr::get(
                tensorflow::GetTypeFromTFTensorShape(
                    {splat_elements_attr.getType().getRank()},
                    op_builder->getI64Type()),
                splat_elements_attr.getType().getShape()));
    mlir::arith::ConstantOp fill_value =
        op_builder->create<mlir::arith::ConstantOp>(

public class AnnotationCallInterceptionRequestReaderImpl implements AnnotatedMethodReaderExtension {

    @Override
    public Collection<Result> readRequest(ExecutableElement input) {
        if (input.getKind() != ElementKind.METHOD) {
            return emptyList();
        }

        if (!input.getModifiers().containsAll(Arrays.asList(Modifier.STATIC, Modifier.PUBLIC))) {
            return emptyList();
        }

  // The default debug string includes a shape, dtype and FullType.
  // Implementations are free to override it with something more informative.
  virtual std::string DebugString() const;

  AbstractTensorHandleKind getKind() const { return kind_; }

 private:
  const AbstractTensorHandleKind kind_;
};

namespace internal {
struct AbstractTensorHandleDeleter {
  void operator()(AbstractTensorHandle* p) const {

              mlir::dyn_cast_or_null<ShapedType>(operand.getType());
          return result_type && operand_type && result_type.hasRank() &&
                 operand_type.hasRank() &&
                 result_type.getRank() == operand_type.getRank();
        });
    if (!is_valid_move) return;
  }

  // At this point we checked that we can safely move Transpose node before
  // `op`, and bypass all result transposes.

import java.util.List;

public class TypeMirrorToType extends AbstractTypeVisitor8<Type, Void> {

    @Override
    public Type visitPrimitive(PrimitiveType t, Void unused) {
        TypeKind kind = t.getKind();
        if (kind == TypeKind.INT) {
            return Type.INT_TYPE;
        }
        if (kind == TypeKind.BYTE) {
            return Type.BYTE_TYPE;
        }
        if (kind == TypeKind.BOOLEAN) {