mirrored_replicate_args.insert(
            mlir::cast<IntegerAttr>(mirrored_index).getInt());
      }
    }
    auto func =
        llvm::cast<func::FuncOp>(m.lookupSymbol(cluster_func.getFunc()));
    for (auto entry : llvm::enumerate(cluster_func.getOperands())) {
      auto operand = SkipIdentityAndReadVariable(entry.value());
      auto block_arg = mlir::dyn_cast<BlockArgument>(operand);

  if (!status->status.ok()) return;
  auto run_metadata = context->ExportRunMetadata();
  status->status = MessageToBuffer(*run_metadata, buf);
}

namespace {
TFE_Op* GetFunc(TFE_Context* ctx, const tensorflow::NameAttrList& func,
                TF_Status* status) {
  TFE_Op* func_op = TFE_NewOp(ctx, func.name().data(), status);
  for (const auto& attr : func.attr()) {

  // Look up function definition from module.
  mlir::func::FuncOp func =
      cluster_func->getParentOfType<ModuleOp>()
          .lookupSymbol<mlir::func::FuncOp>(cluster_func.getFunc());

  bool use_spmd = false;
  if (auto use_spmd_attr = cluster_func->getAttrOfType<BoolAttr>(kUseSpmdAttr))
    use_spmd = use_spmd_attr.getValue();

  auto num_cores_per_replica_attr =

//
// TODO(mdempsky): I suspect there's no need for separate fpos and
// npos.
func NewFunc(fpos, npos src.XPos, sym *types.Sym, typ *types.Type) *Func {
	name := NewNameAt(npos, sym, typ)
	name.Class = PFUNC
	sym.SetFunc(true)

	fn := &Func{Nname: name}
	fn.pos = fpos
	fn.op = ODCLFUNC
	// Most functions are ABIInternal. The importer or symabis
	// pass may override this.
	fn.ABI = obj.ABIInternal
	fn.SetTypecheck(1)