* The listener will run when the {@code Future}'s computation is {@linkplain Future#isDone()
   * complete} or, if the computation is already complete, immediately.
   *
   * <p>There is no guaranteed ordering of execution of listeners, but any listener added through
   * this method is guaranteed to be called once the computation is complete.
   *

     * the convention computation that is not compatible with Isolated Projects.
     */
    @Nullable
    public IdeaLanguageLevel getRawLanguageLevel() {
        return languageLevel;
    }

    /**
     * Returns the user-defined value for the {@link #getTargetBytecodeVersion()} without triggering
     * the convention computation that is not compatible with Isolated Projects.
     */

  LOG_FIRST_N(INFO, 1) << "Compiling MLIR computation to XLA HLO using the "
                          "Combined MLIR Tf2Xla Bridge.";

  absl::StatusOr<std::string> mlir_compilation =
      internal::CompileFromMlirToXlaHlo(
          /*lower_to_xla_hlo=*/false, computation, metadata, device_type,
          shape_determination_fns, use_tuple_args, compilation_result,

     * the convention computation that is not compatible with Isolated Projects.
     */
    public @Nullable IdeaLanguageLevel getRawLanguageLevel() {
        return languageLevel;
    }

    /**
     * Returns the user-defined value for the {@link #getTargetBytecodeVersion()} without triggering
     * the convention computation that is not compatible with Isolated Projects.
     */

      xla::XlaComputation computation,
      return_value.valid() ? builder.Build(return_value) : builder.Build());
  auto hlo_module = computation.proto();
  xla::HloProto hlo_proto;
  hlo_proto.mutable_hlo_module()->Swap(&hlo_module);

  compilation_result->computation = std::make_shared<xla::XlaComputation>();
  xla::XlaComputation* xla_computation = compilation_result->computation.get();

namespace v1 {

// Compiles the given Tensorflow graph into xla::HLO. The result is in
// compilation_result. If the input computation is in MLIR, it will be
// converted to a Tensorflow graph. Otherwise, the graph compiler will be run.
absl::Status CompileTensorflowGraphToHlo(
    const std::variant<tpu::MlirToHloArgs, tpu::FunctionToHloArgs>& computation,
    const tpu::TPUCompileMetadataProto& metadata, bool use_tuple_args,

// RUN: tf-opt %s --run-tf-graph-optimization --graph-passes=FunctionalizeControlFlowForXlaPass | FileCheck %s

func.func @main() {
  tf_executor.graph {
    %0 = tf_executor.island wraps "tf._TPUReplicate"() {computation = @foo, Tinputs = [], Tbroadcast_inputs = [], NumVariables = 0, Tguaranteed_constants = [], output_types = []} : () -> () loc("_TPUReplicate")
    tf_executor.fetch
  }
  func.return
}

func.func @foo() {
  tf_executor.graph {

   * The listener will run when the {@code Future}'s computation is {@linkplain Future#isDone()
   * complete} or, if the computation is already complete, immediately.
   *
   * <p>There is no guaranteed ordering of execution of listeners, but any listener added through
   * this method is guaranteed to be called once the computation is complete.
   *

   * The listener will run when the {@code Future}'s computation is {@linkplain Future#isDone()
   * complete} or, if the computation is already complete, immediately.
   *
   * <p>There is no guaranteed ordering of execution of listeners, but any listener added through
   * this method is guaranteed to be called once the computation is complete.
   *

    XlaComputation& computation) {
  xla::DebugOptions debug_options;
  TF_ASSIGN_OR_RETURN(auto hlo_module_config,
                      xla::HloModule::CreateModuleConfigFromProto(
                          computation.proto(), debug_options));
  TF_ASSIGN_OR_RETURN(
      std::unique_ptr<xla::HloModule> hlo_module,
      xla::HloModule::CreateFromProto(computation.proto(), hlo_module_config));