$2 ~ /^(TASKSTATS|TS)_/ ||
		$2 ~ /^CGROUPSTATS_/ ||
		$2 ~ /^GENL_/ ||
		$2 ~ /^STATX_/ ||
		$2 ~ /^RENAME/ ||
		$2 ~ /^UBI_IOC[A-Z]/ ||
		$2 ~ /^UTIME_/ ||
		$2 ~ /^XATTR_(CREATE|REPLACE|NO(DEFAULT|FOLLOW|SECURITY)|SHOWCOMPRESSION)/ ||
		$2 ~ /^ATTR_(BIT_MAP_COUNT|(CMN|VOL|FILE)_)/ ||
		$2 ~ /^FSOPT_/ ||
		$2 ~ /^WDIO[CFS]_/ ||
		$2 ~ /^NFN/ ||
		$2 !~ /^NFT_META_IIFTYPE/ &&
		$2 ~ /^NFT_/ ||
		$2 ~ /^NF_NAT_/ ||

    device: The tensorflow device. eg. "/CPU:0"
    op_attrs: The tensorflow attributes excluding the func attrs.
    op_func_attrs: The func attrs.
    op_name: The tensorflow op name. eg. "tf.AddV2"

    Example:
      %out_ch = tfrt_fallback_async.createop(%in_ch) key(0) device("/CPU:0")
        "some.op"() {attr1 = value, attr2 = value2} {f_attr1 = "fn1", f_attr2 = "fn2"} num_args(1)
  }];

  let arguments = (ins

  for (auto attr : kQuantizationAxisAttrs) {
    if (defining_op->hasAttr(attr)) {
      return defining_op->getAttr(attr);
    }
  }
  // Not found.
  return rewriter.getI64IntegerAttr(-1);
}

LogicalResult CheckIfAttrIs8Bit(const std::string& attr, Operation* op,
                                bool& is_8_bit) {
  Type element_type;

}

LogicalResult ConvertNgrams(func::FuncOp func, llvm::StringRef api,
                            FuncAttr attr) {
  func.eraseBody();
  func.addEntryBlock();
  func->setAttr(kTFImplements, attr);
  OpBuilder builder(func.getBody());
  std::string custom_option_buffer;
  if (failed(CreateNgramsCustomOption(func, attr.getAttrs(),
                                      custom_option_buffer))) {
    return failure();
  }

Attribute RewriteTFRCallOp::ProcessAttributeValue(Attribute attr,
                                                  StringAttr attr_type) const {
  if (!attr_type) return attr;

  if (attr_type.getValue() == "tensor") {
    if (auto f = mlir::dyn_cast<FloatAttr>(attr)) {
      RankedTensorType type = RankedTensorType::get({}, f.getType());
      return DenseFPElementsAttr::get(type, attr);
    }

    llvm::SmallVectorImpl<mlir::NamedAttribute> &output) {
  for (mlir::NamedAttribute attr : attrs) {
    if (attr.getName().strref().contains(
            mlir::tfg::TFGraphDialect::getDeviceAttrKey())) {
      tensorflow::DeviceNameUtils::ParsedName parsed_name;
      if (!tensorflow::DeviceNameUtils::ParseFullName(
              mlir::cast<mlir::StringAttr>(attr.getValue()).getValue().str(),

    }

    def "can serialize/deserialize isolated Attribute values"() {
        Attribute attr1 = Attribute.of("foo", String.class)
        Attribute attr2 = Attribute.of("bar", SomeType.class)
        Isolatable<?>[] isolatables = [isolatableFactory.isolate(attr1), isolatableFactory.isolate(attr2)]

        when:
        serialize(isolatables)

        and:

}

Status ConvertAttribute(const mlir::BoolAttr& attr, AttrValue* value) {
  value->set_b(attr.getValue());
  return absl::OkStatus();
}

Status ConvertAttribute(const mlir::IntegerAttr& attr, AttrValue* value) {
  value->set_i(attr.getInt());
  return absl::OkStatus();
}

Status ConvertAttribute(const mlir::FloatAttr& attr, AttrValue* value) {
  value->set_f(attr.getValueAsDouble());
  return absl::OkStatus();
}

    op_state.addOperands(op.getOperands());
    op_state.addTypes(op.getResultTypes());

    SmallVector<NamedAttribute, 2> attrs;
    std::string parsed_op_name;
    tensorflow::NodeDef node_def;
    if (failed(ParseCustomOption(op.getCustomOption().getValue(), op.getLoc(),
                                 parsed_op_name, attrs, node_def))) {
      return failure();
    }
    if (parsed_op_name != tf_op_name) {
      return op.emitOpError(

    std::vector<NamedAttribute> attrs = contraction->getAttrs();
    ArrayAttr fused_ops_attr = ArrayAttr::get(context, fused_ops);
    attrs.push_back(
        NamedAttribute(StringAttr::get(context, "fused_ops"), fused_ops_attr));
    // Epsilon is used only in fusions with the FusedBatchNorm op, so we zero it
    // here.
    Attribute epsilon = rewriter.getF32FloatAttr(0);
    attrs.push_back(