}

string PrintAttrValue(const string& op, const AttrValue& attr_value) {
  switch (attr_value.value_case()) {
    case AttrValue::kS:
      return PrintString(attr_value.s());
    case AttrValue::kI:
      return strings::StrCat(attr_value.i());
    case AttrValue::kF: {
      const float f = attr_value.f();
      if (std::isinf(f)) {
        return strings::StrCat(f < 0.0f ? "-" : "+",

}

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();

  for (const auto& name_attr_pair : n.attrs()) {
    const AttrValue& attr_value = name_attr_pair.second;
    if (attr_value.value_case() == AttrValue::kFunc) {
      result.push_back(attr_value.func());
    } else if (attr_value.value_case() == AttrValue::kList) {
      result.insert(result.end(), attr_value.list().func().begin(),
                    attr_value.list().func().end());
    }
  }

  return result;
}

      *list->add_tensor() = tensor;
    } else if (auto attr = mlir::dyn_cast<mlir::FlatSymbolRefAttr>(a)) {
      AttrValue attr_val;
      TF_RETURN_IF_ERROR(ConvertAttribute(attr, &attr_val));
      *list->add_func() = attr_val.func();
    } else if (auto attr = mlir::dyn_cast<mlir::TypeAttr>(a)) {
      AttrValue attr_val;
      // For type attributes, we only propagate the element type.
      mlir::Type elt_type = attr.getValue();

    for (const auto& name_and_value : node_def.attr()) {
      const std::string& attr_name = name_and_value.first;
      const tensorflow::AttrValue& attr_value = name_and_value.second;
      absl::StatusOr<Attribute> mlir_attr =
          tensorflow::ConvertAttributeValue(attr_value, &builder);
      if (!mlir_attr.ok()) {
        return emitError(loc, mlir_attr.status().message());
      }

                                     IntegerAttr attr_value, Operation* op,
                                     ModuleOp& module) {
  const auto ex_attr_value = module->getAttrOfType<IntegerAttr>(attr_name);
  if (ex_attr_value == nullptr) {
    module->setAttr(attr_name, attr_value);
    return success();
  }
  if (ex_attr_value == attr_value) {
    return success();
  }

Status AppendToListAttr(Node* n, const string& attr_name, const string& value) {
  std::vector<T> attr_value;
  Status s = GetNodeAttr(n->attrs(), attr_name, &attr_value);
  if (!s.ok() && s.code() != error::NOT_FOUND) {
    return s;
  }

  n->ClearAttr(attr_name);
  attr_value.push_back(value);
  n->AddAttr(attr_name, attr_value);
  return absl::OkStatus();
}

// Replaces attribute value.
template <typename T>

                                  const void* proto, size_t proto_len,
                                  TF_Status* status) {
  tensorflow::AttrValue attr_value;
  if (!attr_value.ParseFromArray(proto, proto_len)) {
    status->status = InvalidArgument(
        "Unparseable AttrValue proto passed to "
        "TF_FunctionSetAttrValueProto");
    return;
  }

  auto fdef_or = func->record->mutable_fdef();

  }
  return true;
}

bool HasSymbolRefAttr(Operation* op) {
  for (const auto& attr : op->getAttrs()) {
    Attribute attr_value = attr.getValue();
    if (mlir::isa<SymbolRefAttr>(attr_value)) {
      return true;
    } else if (auto array_attr = mlir::dyn_cast<ArrayAttr>(attr_value)) {
      if (!array_attr.empty() &&
          mlir::isa<SymbolRefAttr>(*array_attr.begin())) {
        return true;
      }
    }

                             const void* proto, size_t proto_len,
                             TF_Status* status) {
  tensorflow::AttrValue attr_value;
  if (!attr_value.ParseFromArray(proto, proto_len)) {
    status->status =
        tensorflow::errors::InvalidArgument("Unparseable AttrValue proto");
    return;
  }
  if (op == nullptr) {
    status->status = tensorflow::errors::InvalidArgument(