}
    if (num_dims_i < 0) {
      proto[i].set_unknown_rank(true);
    } else {
      const int64_t* dims_i = dims[i];
      auto proto_i = &proto[i];
      for (int d = 0; d < num_dims_i; ++d) {
        proto_i->add_dim()->set_size(dims_i[d]);
      }
    }
  }
  forward_op_->attrs.Set(
      attr_name, gtl::ArraySlice<TensorShapeProto>(proto.get(), num_values));

void TF_SetAttrValueProto(TF_OperationDescription* desc, const char* attr_name,
                          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");
    return;
  }

  if (strcmp(attr_name, tensorflow::kColocationAttrName) == 0) {

                             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) {

","keepMinutes","localAdjust","_changeInProgress","parseZone","tZone","hasAlignedHourOffset","isDST","isUtcOffset","zoneAbbr","zoneName","dates","isDSTShifted","_isDSTShifted","array1","array2","dontConvert","lengthDiff","diffs","compareArrays","proto$1","get$1","index","field","setter","listMonthsImpl","out","listWeekdaysImpl","localeSorted","shift","_calendar","_longDateFormat","formatUpper","toUpperCase","tok","_invalidDate","_ordinal","isFuture","_relativeTime","pastFuture","source","_eras",...

                                  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;
  }

// GraphDef type. These functions must be deleted by calling TF_DeleteFunction.
//
// If `mutate_proto_func` is non-NULL, run it over each FunctionDef proto,
// before creating a TF_Function out of the possibly mutated proto.
static std::vector<UniqueFuncPtr> CreateFunctionsFromTextProto(
    const char* text_proto,
    std::function<void(FunctionDef*)>* mutate_proto_func, TF_Status* status) {

	// unit tests do not have host set.
	if r.Host == "" {
		return path.Clean(r.URL.Path)
	}
	proto := handlers.GetSourceScheme(r)
	if proto == "" {
		proto = getURLScheme(globalIsTLS)
	}
	u := &url.URL{
		Host:   r.Host,
		Path:   path.Join(SlashSeparator, bucket, object),
		Scheme: proto,
	}
	// If domain is set then we need to use bucket DNS style.
	for _, domain := range domains {

  string bytes1, bytes2;
  tensorflow::TensorShapeProto proto;

  const int64_t pts1[] = {2, 4, -1, 8};
  tensorflow::PartialTensorShape(pts1).AsProto(&proto);
  proto.SerializeToString(&bytes1);

  const int64_t pts2[] = {1, 3, 5, 7};
  tensorflow::PartialTensorShape(pts2).AsProto(&proto);
  proto.SerializeToString(&bytes2);

  std::unique_ptr<const void*[]> list_ptrs;

}

void TFE_InitializeLocalOnlyContext(TFE_Context* ctx, int keep_alive_secs,
                                    const void* proto, size_t proto_len,
                                    TF_Status* status) {
  tensorflow::ServerDef server_def;
  if (!server_def.ParseFromArray(proto, proto_len)) {
    status->status = tensorflow::errors::InvalidArgument(
        "Invalid tensorflow.ServerDef protocol buffer");
    return;

when dealing with untrusted data. Based on the security history of these
libraries we consider that it is safe to work with untrusted inputs for PNG,
BMP, GIF, WAV, RAW, RAW\_PADDED, CSV and PROTO formats. All other input formats,
including tensorflow-io should be sandboxed if used to process untrusted data.

For example, if an attacker were to upload a malicious video file, they could