AttrValue nested_value;
      TF_RETURN_IF_ERROR(ConvertAttribute(attr, &nested_value));
      switch (nested_value.value_case()) {
        case AttrValue::kS:
          list->add_s(nested_value.s());
          break;
        case AttrValue::kType:
          list->add_type(nested_value.type());
          break;
        case AttrValue::kShape:

}

std::pair<string, AttrValue> impl::AttrLiteralHelper(
    const std::pair<string, bool>& bool_attr) {
  AttrValue attr_value;
  attr_value.set_b(bool_attr.second);
  return {bool_attr.first, attr_value};
}

std::pair<string, AttrValue> impl::AttrLiteralHelper(
    const std::pair<string, absl::Span<const int>>& int_list_attr) {
  AttrValue attr_value;
  AttrValue::ListValue* list = attr_value.mutable_list();

                    String attrValue = attrNode.getNodeValue();
                    if (StringUtil.isNotBlank(attrValue)) {
                        // if starting with www, append a protocol
                        if (attrValue.startsWith("www.")) {
                            attrValue = "http://" + attrValue;
                        }
                        return attrValue;
                    }
                }

                          const tensorflow::AttrValue& default_value,
                          const char* attr_name, TF_Status* status) {
  switch (default_value.value_case()) {
    case tensorflow::AttrValue::kS: {
      const string& v = default_value.s();
      TFE_OpSetAttrString(op, attr_name, v.data(), v.size());
      break;
    }
    case tensorflow::AttrValue::kI:

      }
    }
    case AttrValue::kB:
      return attr_value.b() ? "true" : "false";
    case AttrValue::kType:
      return DataType_Name(attr_value.type());
    case AttrValue::kShape:
      return PrintTensorShape(attr_value.shape());
    case AttrValue::kTensor:
      return PrintTensorProto(attr_value.tensor());
    case AttrValue::kList: {
      string ret = "{";

  EXPECT_EQ(shape_inference_graphs.size(), 0);

  // Check host graph: verify we have key placeholder and sequencer.
  std::unique_ptr<FunctionBody> host_fbody;
  AttrValue device_ordinal_temp_value;
  device_ordinal_temp_value.set_i(0);
  protobuf::Map<string, AttrValue> host_func_attrs;
  host_func_attrs["_device_ordinal"] = device_ordinal_temp_value;
  TF_CHECK_OK(FunctionDefToBodyHelper(

      LIST_CASE(tensor, TF_ATTR_FUNC);
#undef LIST_CASE
      break;

    case tensorflow::AttrValue::kPlaceholder:
      *list_size = -1;
      *total_size = -1;
      break;

    case tensorflow::AttrValue::kFunc:
      *list_size = -1;
      *total_size = -1;
      break;

    case tensorflow::AttrValue::VALUE_NOT_SET:
      status->status = absl::InvalidArgumentError(

                boolean attrValue = reader.nextBoolean();
                attributes = attributesFactory.concat(attributes, Attribute.of(attrName, Boolean.class), attrValue);
            } else if (reader.peek() == NUMBER) {
                Integer attrValue = reader.nextInt();
                attributes = attributesFactory.concat(attributes, Attribute.of(attrName, Integer.class), attrValue);
            } else {

                final String attrValue
                @Inject ChangingAttributeRule(String attrValue) { this.attrValue = attrValue }
                void execute(ComponentMetadataContext context) {
                    context.details.allVariants {
                        attributes.attribute(Attribute.of("my.attribute.name", String), attrValue)
                    }
                }
            }

                                                     .begin())>::value>::type>
Status SetTypeAttribute(absl::string_view name, ContainerT types,
                        AttrValueMap* values) {
  AttrValue value;
  auto& type_list = *value.mutable_list();
  for (auto type : types) {
    DataType dtype;
    TF_RETURN_IF_ERROR(ConvertScalarTypeToDataType(type, &dtype));
    type_list.add_type(dtype);
  }