private static final byte ISOLATABLE_TYPE = (byte) 0;
    private static final byte ARRAY_TYPE = (byte) 1;
    private static final byte OTHER_TYPE = (byte) 2;
    private static final byte NULL_TYPE = (byte) 3;

    private final IsolatableSerializer<?>[] isolatableSerializers = {
        new StringValueSnapshotSerializer(),
        new BooleanValueSnapshotSerializer(),
        new ShortValueSnapshotSerializer(),

	// IntType is equivalent to the CEL 'int' type which is a 64-bit signed int.
	IntType = NewSimpleTypeWithMinSize("int", cel.IntType, types.IntZero, MinNumberSize)

	// NullType is equivalent to the CEL 'null_type'.
	NullType = NewSimpleTypeWithMinSize("null_type", cel.NullType, types.NullValue, 4)

	// StringType is equivalent to the CEL 'string' type which is expected to be a UTF-8 string.

#include "tensorflow/c/tf_datatype.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_status_helper.h"
#include "xla/tsl/c/tsl_status_internal.h"
#include "tensorflow/core/framework/full_type.pb.h"
#include "tensorflow/core/framework/shape_inference.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"

  // Test that full type information can be accessed.
  auto outs = unwrap(add_outputs);
  auto h = outs->outputs[0];
  ASSERT_NE(h, nullptr);
  ASSERT_EQ(h->FullType().type_id(), TFT_UNSET);
  ASSERT_EQ(unwrap(inputs[0])->FullType().type_id(), TFT_UNSET);

  // Clean up operation and inputs.
  TF_DeleteAbstractOp(add_op);

  TF_AbstractFunction* func =

        is DataType.ConstantType<*> -> ObjectReflection.DefaultValue(type, objectOrigin)
        is DataClass -> reflectData(OperationId(-1L, DefaultOperationGenerationId.preExisting), type, objectOrigin, context)
        is DataType.NullType -> error("Null type can't appear in property types")
        is DataType.UnitType -> error("Unit can't appear in property types")
        else -> { error("Unhandled data type: ${type.javaClass.simpleName}") }
    }
}

}

func (v *fakeAuditAnnotationCondition) GetExpression() string {
	return v.ValueExpression
}

func (v *fakeAuditAnnotationCondition) ReturnTypes() []*celgo.Type {
	return []*celgo.Type{celgo.StringType, celgo.NullType}

		{float64(1.2), types.DoubleType},
		{int64(-42), types.IntType},
		{uint64(63), types.UintType},
		{time.Duration(300), types.DurationType},
		{time.Now().UTC(), types.TimestampType},
		{types.NullValue, types.NullType},
		{NewListValue(), types.ListType},
		{NewMapValue(), types.MapType},
		{[]byte("bytes"), types.BytesType},
		{NewObjectValue(objType), objType},
	}
	for i, tc := range tests {
		idx := i
		tst := tc

		return types.Uint(v), UintType, nil
	case time.Duration:
		return types.Duration{Duration: v}, DurationType, nil
	case time.Time:
		return types.Timestamp{Time: v}, TimestampType, nil
	case types.Null:
		return v, NullType, nil
	case *ListValue:
		return v, ListType, nil
	case *MapValue:
		return v, MapType, nil
	case *ObjectValue:
		return v, v.objectType, nil
	default:

    return ptr->getKind() == kMlir;
  }

  // Return default (TFT_UNSET) full type information. This could be updated in
  // the future if full type information is needed.
  tensorflow::FullTypeDef FullType() const override {
    return tensorflow::FullTypeDef();
  }

 private:
  Value value_;
};

class MlirFunctionContext;

class MlirAbstractOp : public TracingOperation {
 public:

			}
		default:
			return nil, fmt.Errorf("expression must return a string or a list of strings")
		}

		if len(result) == 0 {
			return nil, nil
		}

		return result, nil
	case celgo.NullType.TypeName():
		return nil, nil
	default:
		return nil, fmt.Errorf("expression must return a string or a list of strings")
	}
}

// messageFunc is a function that returns a message for a validation rule.