continue;
    }

    if (node->type_string() == "Const") {
      // Skip Const op with type DT_STRING, since XLA autoclustering doesn't
      // support it.
      const AttrValue* attr = node->attrs().Find("dtype");
      if (attr != nullptr && attr->type() == DT_STRING) {
        continue;
      }
    }

    if (!allowlist.empty() && !allowlist.contains(node->def().op())) {

  const std::string& func_str =
      "    signature {"
      "      name: 'FunctionWith__OP_NAME__'"
      "      output_arg {"
      "        name: 'out'"
      "        type: DT_STRING"
      "      }"
      "    }"
      "    node_def {"
      "      name: 'error_op'"
      "      op: '__OP_NAME__'"
      "    }"
      "    ret {"
      "      key: 'out'"

    return std::nullopt;
  }

  // TensorFlow and TensorFlow Lite use different string encoding formats.
  // Convert to TensorFlow Lite format is it's a constant string tensor.
  if (tensor.dtype() == tensorflow::DT_STRING) {
    ::mlir::TFL::MiniDynamicBuffer dynamic_buffer;
    auto flat = tensor.flat<::tensorflow::tstring>();
    for (int i = 0; i < flat.size(); ++i) {
      const auto& str = flat(i);

  inputs.reserve(assets.size());
  for (const auto& asset : assets) {
    TensorInfo tensor_info;
    tensor_info.set_name(asset.tensor_name);
    tensor_info.set_dtype(DT_STRING);
    tensor_info.mutable_tensor_shape();
    inputs.push_back({asset.tensor_name, tensor_info});
  }

  std::unordered_map<std::string, std::string> tf_name_to_mlir_name;