return;
  }

  switch (computation.index()) {
    case 0:
      VLOG(2) << "LegalizeMlirToHlo with MLIR computation input: "
              << std::get<0>(computation).mlir_module;
      break;
    case 1: {
      auto input = std::get<1>(computation);
      Graph g(input.flib_def);
      VLOG(2) << "LegalizeMlirToHlo with FLIB computation input: "
              << DumpGraphToFile(

//   result shapes.
// custom_legalization_passes: passes to run before the default TF legalization
//   passes for backend-specific ops.
ABSL_DEPRECATED("Use v2/legalize_tf.h::LegalizeMlirToHlo instead.")
Status ConvertMLIRToXlaComputation(
    mlir::ModuleOp module_op, llvm::StringRef device_type,
    xla::XlaComputation* xla_computation, bool use_tuple_args,
    bool enable_op_fallback, bool return_tuple,

//  arg_core_mapping - Which args go on which cores.
//  per_core_arg_shapes - For each core, the shapes for each argument.
//  client - The Xla Compilation client.
absl::StatusOr<tensorflow::XlaCompilationResult> LegalizeMlirToHlo(
    const std::variant<tpu::MlirToHloArgs, tpu::FunctionToHloArgs>& computation,
    const tpu::TPUCompileMetadataProto& metadata, bool use_tuple_args,
    llvm::StringRef device_type,

  std::vector<ShardingAndIndex> arg_core_mapping;
  std::vector<std::vector<xla::Shape>> per_core_arg_shapes;
  std::vector<std::unique_ptr<mlir::Pass>> custom_legalization_passes;

  return LegalizeMlirToHlo(mlir_to_hlo_args, metadata_proto, use_tuple_args,
                           /*device_type=*/"XLA_TPU_JIT",
                           custom_legalization_passes,

    std::vector<std::vector<xla::Shape>> per_core_arg_shapes;
    std::vector<std::unique_ptr<mlir::Pass>> custom_legalization_passes;

    TF_EXPECT_OK(tensorflow::tf2xla::v2::LegalizeMlirToHlo(
                     mlir_to_hlo_args, metadata_proto, use_tuple_args,
                     /*device_type=*/"XLA_TPU_JIT", custom_legalization_passes,
                     /*shape_determination_fns=*/{}, arg_shapes,