while_region.getBody()));
    } else if (auto case_op = dyn_cast<CaseOp>(op)) {
      llvm::SmallVector<func::FuncOp, 4> functions;
      case_op.get_branch_functions(functions);
      AnalyzeFunctionalCaseOrIfOp(case_op, functions, backtrack_analysis);
    } else if (auto if_op = dyn_cast<IfOp>(op)) {
      AnalyzeFunctionalCaseOrIfOp(

  auto block = builder.createBlock(&region);
  SmallVector<Value, 4> new_operands;
  for (Type t : func.getFunctionType().getInputs())
    new_operands.push_back(block->addArgument(t, loc));
  auto call = builder.create<func::CallOp>(loc, func, new_operands);
  builder.create<YieldOp>(loc, call.getResults());
  // Mark old function as private so that it can be DCE'd if not called.
  func.setPrivate();
}

void RunOnWhile(TF::WhileOp while_op) {

              $this: CALL 'public final fun plus (other: kotlin.Int): kotlin.Int [operator] declared in kotlin.Int' type=kotlin.Int origin=PLUS
                $this: CALL 'public final fun callFoo (foo: <root>.Foo): kotlin.Int declared in <root>.ContextKt' type=kotlin.Int origin=null
                  foo: GET_VAR 'p0: <root>.Foo declared in <root>.CodeFragment.run' type=<root>.Foo origin=null

// uses `get_next` to get the next value and calls `reduce_func`.  `body_args`
// is used as pass through of state values for else branch.  `dataset_types` is
// used for constructing the CallOp for `reduce_func`.
IfRegionOp CreateOptionalDatasetIf(
    OpBuilder builder, ReduceDatasetOp reduce_dataset, FuncOp reduce_func,
    IteratorGetNextAsOptionalOp get_next, OptionalHasValueOp optional_has_value,

          op, {if_op.then_function(), if_op.else_function()}, if_op.getInput());
    } else if (auto case_op = dyn_cast<TF::CaseOp>(op)) {
      SmallVector<func::FuncOp, 4> branches;
      case_op.get_branch_functions(branches);
      result =
          CanonicalizeFunctionalIfCase(case_op, branches, case_op.getInput());
    } else if (auto while_op = dyn_cast<TF::WhileOp>(op)) {

	// Create new entry for this inline
	inlinedFn := base.Ctxt.InlTree.InlinedFunction(inlIdx)
	callXPos := base.Ctxt.InlTree.CallPos(inlIdx)
	callPos := base.Ctxt.InnermostPos(callXPos)
	absFnSym := base.Ctxt.DwFixups.AbsFuncDwarfSym(inlinedFn)
	ic := dwarf.InlCall{
		InlIndex:  inlIdx,
		CallPos:   callPos,
		AbsFunSym: absFnSym,
		Root:      parCallIdx == -1,
	}
	dwcalls.Calls = append(dwcalls.Calls, ic)

  SymbolTable symbol_table = SymbolTable(getOperation());
  llvm::SetVector<func::FuncOp> reachable_funcs;
  for (auto func : getOperation().getOps<func::FuncOp>()) {
    auto walk_result = func.walk([&](func::CallOp op) -> WalkResult {
      if (!symbol_table.lookup<func::FuncOp>(op.getCallee()))
        return getOperation().emitError()
               << func.getName() << " is not in the funcs allowlist";

  PopulateLegalizeHloToTFLitePatterns(&patterns, &context);

  ConversionTarget target(context);
  target.addLegalDialect<TFL::TensorFlowLiteDialect, mhlo::MhloDialect>();
  target.addLegalOp<func::CallOp, func::ConstantOp, arith::ConstantOp>();
  target.addDynamicallyLegalOp<mhlo::CustomCallOp>(IsCustomCallLegal);
  target.addDynamicallyLegalOp<mhlo::ReduceOp>(IsReduceOpLegal);

  target.addLegalDialect<arith::ArithDialect>();
  target.addLegalDialect<func::FuncDialect>();
  target.addLegalDialect<tensor::TensorDialect>();
  target.addLegalDialect<shape::ShapeDialect>();
  target.addLegalOp<func::CallOp>();

  if (skip_quantization_ops_) {
    target.addLegalOp<TF::FakeQuantWithMinMaxVarsOp>();
    target.addLegalOp<TF::FakeQuantWithMinMaxVarsPerChannelOp>();
    target.addLegalOp<TF::FakeQuantWithMinMaxArgsOp>();

// that result if so. Otherwise, it will clone and convert the callee function,
// and performs stack ops decomposition on it.
template <typename CallOp>
LogicalResult HandlePartitionedCallOp(
    CallOp call, func::FuncOp callee, ModuleOp module,
    const llvm::SmallDenseMap<Value, Value>& data_var_to_size_var,
    llvm::StringMap<PartitionedCallStackOpsInfo>*