testCloneSeq[testStruct](t, cSeq(8))
}

func cSeq(stringOffsets ...uintptr) cloneSeq {
	return cloneSeq{stringOffsets: stringOffsets}
}

func testCloneSeq[T any](t *testing.T, want cloneSeq) {
	typName := reflect.TypeFor[T]().Name()
	typ := abi.TypeOf(*new(T))
	t.Run(typName, func(t *testing.T) {
		got := makeCloneSeq(typ)
		if !reflect.DeepEqual(got, want) {

    "such as a random number generator.";

// TODO(b/282188914) remove the operations to skip once tests are fixed.
static const DenseSet<mlir::TypeID>* operations_to_skip =
    new DenseSet<mlir::TypeID>{mlir::TypeID::get<mhlo::EinsumOp>()};

class VerifyTFXLALegalization
    : public impl::VerifyTFXLALegalizationBase<VerifyTFXLALegalization> {
 public:

        "The output variant hasn't been initialized");
  }

  if (a.TypeId() != b.TypeId()) {
    return ::tensorflow::errors::Internal(
        "BinaryOpVariants: Variants a and b have different "
        "type ids.  Type names: '",
        a.TypeName(), "' vs. '", b.TypeName(), "'");
  }

  if (a.TypeId() == tensorflow::TypeIndex::Make<::tensorflow::TensorList>()) {

#include "mlir/Support/LLVM.h"  // from @llvm-project

namespace tfrt {
namespace fallback {

FallbackDialect::FallbackDialect(MLIRContext *context)
    : Dialect(/*name=*/"tfrt_fallback", context,
              TypeID::get<FallbackDialect>()) {
  addTypes<TFTensorType, TFAllocatorType>();

  addOperations<
#define GET_OP_LIST
#include "tensorflow/compiler/mlir/tfrt/ir/tfrt_fallback.cpp.inc"
      >();
}

namespace tfrt {
namespace fallback_sync {

FallbackSyncDialect::FallbackSyncDialect(MLIRContext *context)
    : Dialect(/*name=*/"tfrt_fallback_sync", context,
              TypeID::get<FallbackSyncDialect>()) {
  context->getOrLoadDialect<tfrt::fallback::FallbackDialect>();
  context->getOrLoadDialect<compiler::TFRTDialect>();
  context->getOrLoadDialect<corert::CoreRTDialect>();

#include "mlir/IR/PatternMatch.h"  // from @llvm-project
#include "mlir/Pass/Pass.h"  // from @llvm-project
#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#include "mlir/Support/TypeID.h"  // from @llvm-project
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"  // from @llvm-project
#include "stablehlo/dialect/StablehloOps.h"  // from @stablehlo  // IWYU pragma: keep

		s: [2]testStringStruct{testStringStruct{"y"}, testStringStruct{"z"}},
	})
	testHandle[testStruct](t, testStruct{0.5, "184"})
}

func testHandle[T comparable](t *testing.T, value T) {
	name := reflect.TypeFor[T]().Name()
	t.Run(fmt.Sprintf("%s/%#v", name, value), func(t *testing.T) {
		t.Parallel()

		v0 := Make(value)
		v1 := Make(value)

		if v0.Value() != v1.Value() {
			t.Error("v0.Value != v1.Value")
		}

#include "mlir/Pass/PassRegistry.h"  // from @llvm-project
#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#include "mlir/Support/TypeID.h"  // from @llvm-project
#include "mlir/Transforms/DialectConversion.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"

#include "llvm/ADT/DenseSet.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/IR/Visitors.h"  // from @llvm-project
#include "mlir/Pass/Pass.h"  // from @llvm-project
#include "mlir/Support/TypeID.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "tensorflow/compiler/mlir/tf2xla/transforms/legalization_op_config.h"
#include "tensorflow/core/lib/monitoring/counter.h"

    // All mlrt dialect ops can be inlined.
    return true;
  }
};

}  // namespace

MlrtDialect::MlrtDialect(mlir::MLIRContext *context)
    : mlir::Dialect(/*name=*/"mlrt", context,
                    mlir::TypeID::get<MlrtDialect>()) {
  addTypes<FutureType>();
  addTypes<PromiseType>();
  addTypes<AsyncHandleType>();
  addInterfaces<MlrtInlinerInterface>();

  addOperations<
#define GET_OP_LIST