}
        })
        .Case<CallSiteLoc>([&](CallSiteLoc loc) {
          mutable_location->set_type(ConverterErrorData::CALLSITELOC);
          LocationExtractor(loc.getCallee()).Extract(error_data);
          LocationExtractor(loc.getCaller()).Extract(error_data);
        })
        .Case<FusedLoc>([&](FusedLoc loc) {
          auto locations = loc.getLocations();
          size_t num_locs = locations.size();

  return absl::c_all_of(locations, [](Location loc) {
    return isa<NameLoc>(loc) ||
           (isa<CallSiteLoc>(loc) &&
            isa<NameLoc>(mlir::cast<CallSiteLoc>(loc).getCallee()));
  });
}

// Finds the pattern of the location created by `ImporterBase::GetLocation`
// in `tensorflow/compiler/mlir/tensorflow/translate/import_model.cc`.
void FindQuantizationUnitsRecursively(Location loc,

  if (!llvm::isa<CallSiteLoc>(attr)) return false;
  auto callsite_loc = llvm::dyn_cast<CallSiteLoc>(attr);

  if (!mlir::isa<NameLoc>(callsite_loc.getCaller())) return false;
  StringRef caller_name =
      mlir::cast<NameLoc>(callsite_loc.getCaller()).getName().strref();
  return caller_name.starts_with(kQuantizationUnitPrefix) &&
         caller_name.ends_with(kQuantizationUnitSuffix);
}

  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";
      return WalkResult::advance();
    });

    auto users = call_op->getUsers();
    for (auto user : users) {
      if (!llvm::isa<mlir::stablehlo::UniformDequantizeOp>(user)) {
        return failure();
      }
    }
    auto func_name = call_op.getCallee();
    if (!func_name.starts_with("quantized_")) return failure();
    if (call_op->getNumResults() != 1) return failure();
    if (!mlir::isa<UniformQuantizedType>(

      for (auto consumer : op->getResult(0).getUsers()) {
        auto consumer_call = llvm::dyn_cast_or_null<func::CallOp>(consumer);

        if (!consumer_call) continue;

        auto function_name = consumer_call.getCallee();

        // Locate the argument position of the use.
        int argument_index = -1;
        for (int i = 0; i < consumer_call.getNumOperands(); ++i) {

    const llvm::StringMap<Attribute>& derived_attrs) const {
  // Create the new op
  Location loc = call_op.getLoc();
  rewriter.setInsertionPointAfter(call_op);
  std::string tf_op_name = GetTFOpName(call_op.getCallee());
  OperationState new_state(loc, tf_op_name, inputs, output_types, attr_list);
  Operation* new_op = rewriter.create(new_state);
  if (materialize_derived_attrs_) {
    for (const auto& attr : derived_attrs) {

    if (!MatchCallArgs(first_call.value(), second_call.value(), arg_matcher))
      return;

    can_transform = true;
    callee_names = {first_call.value().getCallee(),
                    second_call.value().getCallee()};
  }
};

// Transform IfRegionOp to IfOp.
LogicalResult RegionControlFlowToFunctional::ConvertIfOp(
    SymbolTableCollection& symbol_table, IfRegionOp if_region) {

  new_result_types.push_back(token.getType());
  auto new_call = builder.create<func::CallOp>(
      call.getLoc(), new_result_types,
      new_symbol ? *new_symbol : call.getCallee(), new_operands);

  for (auto results : llvm::zip(call.getResults(), new_call.getResults()))
    std::get<0>(results).replaceAllUsesWith(std::get<1>(results));
  call.erase();
  return new_call.getResults().back();

  // The inliner only inlines the TFR call op.
  bool changed = false;
  auto walk_result = func.walk([&](CallOp call_op) {
    auto callee = table.lookup<TFRFuncOp>(call_op.getCallee());
    if (!callee || callee.isExternal()) return WalkResult::advance();

    // Record the boundary of the inlined operations. The inlined operation will
    // be inserted between these two operations.