if (wordStart) {
        result.push_back(delimiter);
      }
      wordStart = true;
      continue;
    }
    if (!from_snake && isupper(c)) {
      wordStart = true;
    }

    // add delimiter
    if (wordStart && toSnake && !inputStart) {
      result.push_back(delimiter);
    }

    // add the next letter from the input string (choosing upper/lower case)

  std::vector<Type> input_types;
  std::vector<Type> output_types;

  input_types.reserve(inputs.size());
  for (Value v : inputs) {
    input_types.push_back(v.getType());
  }
  output_types.reserve(outputs.size());
  for (Value v : outputs) {
    output_types.push_back(v.getType());
  }

  // Create the function.
  MLIRContext* context = ops[0]->getContext();

    std::vector<const Edge*> control_edges;
    std::vector<OutEdgeInfo> data_edges;
    for (auto e : n->out_edges()) {
      if (e->IsControlEdge()) {
        control_edges.push_back(e);
      } else {
        data_edges.push_back({e->dst(), e->src_output(), e->dst_input()});
      }
    }
    for (const Edge* e : control_edges) {
      g->AddControlEdge(original_node, e->dst());
      g->RemoveEdge(e);
    }

      control_fetches.push_back(value);
    } else {
      data_fetches.push_back(value);
      data_types.push_back(value.getType());
    }
  }
  auto island = OpBuilder(fetch).create<IslandOp>(
      fetch.getLoc(), data_types,
      /*control=*/ControlType::get(fetch.getContext()),
      /*controlInputs=*/control_fetches);
  island.getBody().push_back(new Block);

      transpose_ops.push_back(transpose);
    }
  }

  // Nothing to do here.
  if (!permutation_op || transpose_ops.empty()) return;
  SmallVector<int64_t, 4> permutation;
  auto perm_attr = mlir::cast<DenseElementsAttr>(permutation_op.getValue());
  for (const auto& value : perm_attr.getValues<APInt>())
    permutation.push_back(value.getSExtValue());

        const std::vector<std::string> indices =
            absl::StrSplit(node_specification, '-');
        for (const std::string& cur_index : indices) {
          custom_op_map[node_name].quantizable_input_indices.push_back(
              std::stoi(cur_index));
        }
        break;
      }
      case CustomOpUpdateOptions::kWeightOnly:
        custom_op_map[node_name].is_weight_only =
            GetBooleanSpecs(node_specification);

      sharding_for_args.push_back(operand_sharding);
      continue;
    }

    if (infer_from_computation) {
      auto arg_sharding = GetXlaShardingFromArg(arg, logical_device_vec);
      if (arg_sharding) {
        sharding_for_args.push_back(arg_sharding.value());
        continue;
      }
    }

    sharding_for_args.push_back(std::nullopt);
  }
}

  builder.setInsertionPoint(call);
  auto new_operands = llvm::to_vector(call.getArgOperands());
  new_operands.push_back(token);
  auto new_result_types = llvm::to_vector(call.getResultTypes());
  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);

      // Add new control input if its defining op is not already a defining
      // op for some other operand. Update defining_ops.
      if (defining_ops.insert(new_control_input.getDefiningOp()).second) {
        operands.push_back(new_control_input);
      }
    }
    state.addOperands(operands);
    Operation* new_op = builder.create(state);
    item.replaceAllUsesWith(new_op);
    new_op->setAttrs(item.getAttrDictionary());

  if (!main_fn) return std::string("");

  flatbuffers::FlatBufferBuilder fb_builder;
  std::vector<mlir::func::FuncOp> funcs;
  funcs.push_back(main_fn);
  module.walk([&](mlir::func::FuncOp fn) {
    if (fn != main_fn) {
      funcs.push_back(fn);
    }
  });

  // Populate the hardware metadata.
  // And collect the hardwares used.
  std::map<std::string, uint8_t> hardware_map;