// TF graph nodes are imported with one of following location patterns:
//   FusedLoc[NameLoc(op_type:), ..., NameLoc(node_name@func_name)] or
//   FusedLoc[NameLoc(op_type:), ..., CallSiteLoc(node_name@func_name)]. See
// tensorflow/compiler/mlir/tensorflow/translate/import_model.cc for more
// details.
bool IsImportLocPattern(FusedLoc loc) {
  ArrayRef<Location> locations = mlir::cast<FusedLoc>(loc).getLocations();

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

namespace tensorflow {

mlir::Location GetLocationWithoutOpType(mlir::Location loc) {
  if (auto fused_loc = mlir::dyn_cast<mlir::FusedLoc>(loc)) {
    auto locations = fused_loc.getLocations();
    if (!locations.empty()) {
      // Skip locations for propagating op_type metadata.
      if (auto name_loc = mlir::dyn_cast<mlir::NameLoc>(locations[0])) {

          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();
          // Skip the first location if it stores information for propagating
          // op_type metadata.

    QuantizationUnitLoc::QuantizationUnit quant_unit;
    if (quant_unit.ParseFromString(serialized_proto)) {
      return quant_unit;
    }
  } else if (isa<FusedLoc>(loc)) {
    // If the op is rewritten, FusedLoc can be created.
    for (Location child_loc : mlir::cast<FusedLoc>(loc).getLocations()) {
      std::optional<QuantizationUnitLoc::QuantizationUnit> found_unit =
          FindQuantizationUnitFromLoc(child_loc);

  // original const and the qbarrier that led to the quantization.
  auto fusedLoc = rewriter.getFusedLoc(
      {qbarrier.getArg().getDefiningOp()->getLoc(), qbarrier.getLoc()});
  auto newConstOp = rewriter.create<arith::ConstantOp>(
      fusedLoc, newConstValueType, cast<TypedAttr>(newConstValue));
  rewriter.replaceOpWithNewOp<StorageCastOp>(qbarrier, qbarrier.getType(),

    Location loc = tensorflow::GetLocationWithoutOpType(op->getLoc());
    if (auto name = loc.dyn_cast<NameLoc>()) {
      return name.getName().strref();
    } else if (auto fused_name = loc.dyn_cast<FusedLoc>()) {
      for (auto sub_loc : fused_name.getLocations()) {
        if (auto named_sub_loc = sub_loc.dyn_cast<NameLoc>()) {
          return named_sub_loc.getName().strref();
        }
      }
    }

                                rewriter.getStringAttr("NONE"))
                 .getOutput();
    }

    auto fc = rewriter.create<TFL::FullyConnectedOp>(
        FusedLoc::get(fc_op.getContext(), {fc_op.getLoc(), add_op.getLoc()}),
        add_op.getType(),
        /*input=*/fc_op.getInput(),
        /*filter=*/filter,
        /*bias=*/bias,
        /*fused_activation_function=*/

      if (!original_func_name.empty()) {
        debug_info->add_original_func_names(original_func_name.str());
      }
    }
  } else if (auto fused = mlir::dyn_cast<mlir::FusedLoc>(unwrapped_inst_loc)) {
    auto locations = fused.getLocations();
    if (locations.size() <= 1)
      return errors::InvalidArgument("expected experimental debuf info.");

    }

    new_start.push_back(first_start);
    new_limit.push_back(second_limit);
    new_slice_shape.push_back(second_limit - first_start);
  }

  auto new_slice = rewriter.create<mhlo::SliceOp>(
      FusedLoc::get(first->getContext(), {first.getLoc(), second.getLoc()}),
      first.getType().clone(new_slice_shape), first.getOperand(),
      /*start_indices=*/rewriter.getI64TensorAttr(new_start),

  // "original_node_name" in the NodeDef to get the corresponding file location
  // (FileLineColLoc) from the input DebugInfo and returns an CallSiteLoc. If
  // there are multiple "original_node_names", a FusedLoc is returned. If the
  // node name couldn't be found in the input DebugInfo, a NameLoc is used as
  // the location.
  mlir::Location GetLocation(const Node& node);