tensorflow::AttrValue attr_value;
  if (!attr_value.ParseFromArray(proto, proto_len)) {
    status->status = InvalidArgument("Unparseable AttrValue proto");
    return;
  }

  if (strcmp(attr_name, tensorflow::kColocationAttrName) == 0) {
    if (attr_value.value_case() != tensorflow::AttrValue::kList &&
        attr_value.value_case() != tensorflow::AttrValue::VALUE_NOT_SET) {
      status->status =

using ::tsl::StatusOr;

namespace {

bool IsOutputShapesAttribute(const AttrValue& attr_value,
                             llvm::StringRef attr_name) {
  return attr_name.compare(kOutputShapesAttrName) == 0 &&
         attr_value.value_case() == AttrValue::kList;
}

bool IsResourceOutputShapesAttribute(const AttrValue& attr_value,
                                     llvm::StringRef attr_name) {

        break;
      }
      case ::tensorflow::AttrValue::kI:
        flex_builder->Int(key, attr.i());
        break;
      case ::tensorflow::AttrValue::kF:
        flex_builder->Float(key, attr.f());
        break;
      case ::tensorflow::AttrValue::kB:
        flex_builder->Bool(key, attr.b());
        break;
      case tensorflow::AttrValue::kList:
        if (attr.list().s_size() > 0) {

        else strides
    )
    strides_attr = attr_value_pb2.AttrValue(
        list=attr_value_pb2.AttrValue.ListValue(i=strides_to_check)
    )

    if enable_per_channel_quantization:
      quantized_axis_attr = attr_value_pb2.AttrValue(i=3)
      quantized_dim_size_attr = attr_value_pb2.AttrValue(
          list=attr_value_pb2.AttrValue.ListValue(
              shape=[