auto func = func::FuncOp::create(
      mlir::NameLoc::get(builder->getStringAttr("fused_func")), "fused_func",
      func_type, {});

  func.addEntryBlock();
  mlir::StringAttr attr_value = builder->getStringAttr("MaxUnpooling2D");
  func->setAttr("tf._implements", attr_value);
  return func;
}

func::FuncOp createMaxUnpoolingFunc(
    mlir::Builder* builder, const SmallVector<int64_t, 4>& input_shape,

#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_attributes.h"

namespace mlir {
namespace TFL {

// Fuse MaxUnpooling2D ops annotated by tf.function to a TFLite custom op.
class ConvertMaxUnpoolingFunc {
 public:
  explicit ConvertMaxUnpoolingFunc(func::FuncOp func, mlir::TF::FuncAttr attr)
      : func_(func), attr_(attr) {}

#include "tensorflow/lite/c/builtin_op_data.h"

namespace mlir {
namespace TFL {

namespace {

constexpr char kTFImplements[] = "tf._implements";
constexpr char kMaxUnpooling[] = "MaxUnpooling2D";
constexpr char kImageWarping[] = "DenseImageWarp";

inline ConstBytesAttr CustomOption(OpBuilder* builder,
                                   const std::string& content) {

// CHECK-SAME:                         %[[VAL_1:.*]]: tensor<1x1x2x1xi32>) -> tensor<1x2x4x1xf32> attributes {tf._implements = "MaxUnpooling2D"} {

  %0 = "tfl.custom"(%arg0, %arg1) {custom_option = #tfl<const_bytes : "0x01000000020000000200000002000000020000000000000000000000000000000000000000000000">, custom_code = "MaxUnpooling2D"} : (tensor<1x8x8x128xf32>, tensor<1x8x8x128xf32>) -> (tensor<1x8x8x128xf32>)
  func.return %0 : tensor<1x8x8x128xf32>
}

// -----

// CHECK-LABEL: testLogistic