/*filter_width*/(GetI32At<1> (GetAsVectorAttr<"kernel_size"> $attrs)),
                            /*padding*/(GetAvgPoolOpPadAttr $old_val),
                            /*stride_h*/(GetI32At<0> (GetAsVectorAttr<"stride"> $attrs)),
                            /*stride_w*/(GetI32At<1> (GetAsVectorAttr<"stride"> $attrs)),

  for (const NamedAttribute &attr : from->getAttrs())
    if (P(attr)) to->setAttr(attr.getName(), attr.getValue());
}

// Copies attributes whose name begins with an _ from `from` to `to`.
inline void CopyUnderscoredAttributes(Operation *from, Operation *to) {
  CopyAttributes(from, to, [](const NamedAttribute &attr) {
    return attr.getName().strref().front() == '_';
  });
}

    return mlir::failure();

  int64_t num_results = 0;
  if (succeeded(parser.parseOptionalColon())) {
    mlir::IntegerAttr attr;
    mlir::NamedAttrList attrs;
    if (failed(parser.parseAttribute(attr, "num_results", attrs)))
      return mlir::failure();
    num_results = attr.getValue().getSExtValue();
  }
  if (num_results < 0) return mlir::failure();

  llvm::SmallVector<mlir::Type, 4> operand_types;

    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(),

  for (it = attrs.begin(); it != attrs.end(); it++) {
    if (count == i) {
      return it->first.length();
    }
    count++;
  }
  return -1;
}

void TF_OperationGetAttrName(TF_Operation* oper, int i, char* output,
                             TF_Status* status) {
  auto attrs = oper->node.attrs();
  int count = 0;
  AttrValueMap::const_iterator it;
  for (it = attrs.begin(); it != attrs.end(); it++) {

    }

    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:

bool EnsureAttribute(const DictionaryAttr& composite_attributes,
                     const std::string& attr_name, AttrType* out_attr) {
  Attribute attr = composite_attributes.get(attr_name);
  if (!mlir::isa_and_nonnull<AttrType>(attr)) {
    return false;
  }
  if (AttrType content = mlir::dyn_cast<AttrType>(attr)) {
    *out_attr = content;
    return true;
  } else {
    return false;
  }
}

}

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(