status->status = MessageToBuffer(func->record->fdef(), output_func_def);
}

TF_Function* TF_FunctionImportFunctionDef(const void* proto, size_t proto_len,
                                          TF_Status* status) {
  tensorflow::FunctionDef fdef;
  bool success = fdef.ParseFromArray(proto, proto_len);
  if (!success) {
    status->status = InvalidArgument(
        "Invalid FunctionDef given to TF_FunctionImportFunctionDef");

                                size_t proto_len, TF_Status* status) {
  // shape.ParseFromArray takes an int as length, this function takes size_t,
  // make sure there is no information loss.
  if (proto_len > std::numeric_limits<int>::max()) {
    status->status = InvalidArgument(
        "proto_len (", proto_len,
        " bytes) is too large to be parsed by the protocol buffer library");

// `proto` must point to an array of `proto_len` bytes representing a
// binary-serialized TensorShapeProto.
TF_CAPI_EXPORT extern void TF_SetAttrTensorShapeProto(
    TF_OperationDescription* desc, const char* attr_name, const void* proto,
    size_t proto_len, TF_Status* status);
// `protos` and `proto_lens` must point to arrays of length `num_shapes`.

                                                   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;
  }

TF_CAPI_EXPORT extern void TFE_EnableCollectiveOps(TFE_Context* ctx,
                                                   const void* proto,
                                                   size_t proto_len,
                                                   TF_Status* status);

// Aborts all ongoing collectives with the specified status. After abortion,