return {getTrailingObjects<StringAttr>(), num_attrs};
  }

  unsigned num_attrs;
};

template <typename Derived>
class TFRTypeImpl : public Type::TypeBase<Derived, TFRType, TFRTypeStorage> {
 public:
  using Base = Type::TypeBase<Derived, TFRType, TFRTypeStorage>;
  using TFRBase = TFRTypeImpl<Derived>;
  using Base::Base;

  static Derived get(ArrayRef<StringAttr> attrs, MLIRContext* context) {

class TFTensorType
    : public mlir::Type::TypeBase<TFTensorType, mlir::Type, mlir::TypeStorage> {
 public:
  using Base::Base;
  static constexpr mlir::StringLiteral name = "tensorflow.tf_mlrt.tf_tensor";
};

// The MLIR type represents a tensorflow::Device*
class TFDeviceType
    : public mlir::Type::TypeBase<TFDeviceType, mlir::Type, mlir::TypeStorage> {
 public:
  using Base::Base;

};

// The MLIR type represents a tensorflow::Tensor.
class TFTensorType : public Type::TypeBase<TFTensorType, Type, TypeStorage> {
 public:
  using Base::Base;
  static constexpr StringLiteral name = "tfrt.tf_tensor";
};

// The MLIR type represents a tensorflow::Allocator.
class TFAllocatorType
    : public Type::TypeBase<TFAllocatorType, Type, TypeStorage> {
 public:
  using Base::Base;

// The MLIR type represents a C++ mlrt::Future.
class FutureType
    : public mlir::Type::TypeBase<FutureType, mlir::Type, mlir::TypeStorage> {
 public:
  using Base::Base;
  static constexpr mlir::StringLiteral name = "mlrt.compiler.future";
};

// The MLIR type represents a C++ mlrt::Promise.
class PromiseType
    : public mlir::Type::TypeBase<PromiseType, mlir::Type, mlir::TypeStorage> {
 public:
  using Base::Base;

// The Control type is a token-like value that models control dependencies from
// TensorFlow graphs.
class ControlType : public Type::TypeBase<ControlType, Type, TypeStorage> {
 public:
  using Base::Base;
  static constexpr ::mlir::StringLiteral name = "tf_executor.control";
};

class TokenType : public Type::TypeBase<TokenType, Type, TypeStorage> {
 public:
  using Base::Base;
  static constexpr ::mlir::StringLiteral name = "tf_executor.token";

namespace mlir {
namespace TFL {

typedef TFLDialect TensorFlowLiteDialect;

// The Control type is a token-like value that models control dependencies
class ControlType : public Type::TypeBase<ControlType, Type, TypeStorage> {
 public:
  using Base::Base;
  static constexpr StringLiteral name = "tfl.control";
};

#include "tensorflow/compiler/mlir/lite/ir/tfl_ops_interface.h.inc"

		list = append(list, h[id])
	}
	return list, nil
}

func (s *TestServer) Signed(ctx context.Context) ([]byte, error) {
	s.mu.Lock()
	defer s.mu.Unlock()

	size := int64(len(s.records))
	h, err := tlog.TreeHash(size, s.hashes)
	if err != nil {
		return nil, err
	}
	text := tlog.FormatTree(tlog.Tree{N: size, Hash: h})
	signer, err := note.NewSigner(s.signer)
	if err != nil {
		return nil, err
	}