const string& name = pair.first;
        if ((name == prefix) || absl::StartsWith(name, prefix_cmp)) {
          status->status = InvalidArgument(
              "prefix [", prefix,
              "] conflicts with existing node in the graph named [", name, "]");
          return;
        }
      }
      child_scope_name = prefix;
    }
    tensorflow::Scope scope =

} TF_TriState;

// TF_GrapplerItem represents a combination of a graph, one of more fetch nodes,
// and potentially a set of nodes to feed.
typedef struct TF_GrapplerItem TF_GrapplerItem;

// Flags indicating whether existing optimizers should be turned off.
// It's optional for plugin to set functions to return true/false. If not
// set, proper uses configuration set by user.
typedef struct TP_OptimizerConfigs {
  size_t struct_size;

  if [[ "$TFCI_DOCKER_REBUILD_UPLOAD_ENABLE" == 1 ]]; then
    docker push "$TFCI_DOCKER_IMAGE"
  fi
fi

# Keep the existing "tf" container if it's already present.
# The container is not cleaned up automatically! Remove it with:
# docker rm tf
if ! docker container inspect tf >/dev/null 2>&1 ; then
  # Pass all existing TFCI_ variables into the Docker container
  env_file=$(mktemp)
  env | grep ^TFCI_ > "$env_file"

               char* buffer, TF_Status* status);

  // Validate the given file signature with the existing file signature in the
  // cache. Returns true if the signature doesn't change or the file doesn't
  // exist before. If the signature changes, update the existing signature with
  // the new one and remove the file from cache.
  bool ValidateAndUpdateFileSignature(const std::string& filename,

      /*retries=*/0, status, /*clear_existing_contexts=*/false);
}

// Set server def with timeout.
TF_CAPI_EXPORT extern void TFE_ContextSetServerDefWithTimeout(
    TFE_Context* ctx, int keep_alive_secs, const void* proto, size_t proto_len,
    int64_t init_timeout_in_ms, TF_Status* status,
    bool clear_existing_contexts) {
  TFE_ContextSetServerDefWithTimeoutAndRetries(

  ///
  /// Plugins:
  ///   * Must set `status` to `TF_OK` if `file` was updated.
  ///   * Must set `status` to `TF_NOT_FOUND` if `path` doesn't point to an
  ///     existing file or one of the parent entries in `path` doesn't exist.
  ///   * Must set `status` to `TF_FAILED_PRECONDITION` if `path` points to a
  ///     directory or if it is invalid (e.g., malformed, or has a parent entry

            documented as temporary and to be removed.
            *   Uses of `tensors()` can be replaced by calling the existing
                methods `tensors_size()` and `tensor(int)`.
            *   Uses of the non-const overload of `nodes_and_registration` can
                be replaced by calling the existing methods `nodes_size()` and
                `context()`, and then calling the `GetNodeAndRegistration`

                                     serialized_server_def.size(),
                                     init_timeout_in_ms, status,
                                     /*clear_existing_contexts=*/false);
  EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  TFE_DeleteContextOptions(opts);
  TF_DeleteStatus(status);
  return ctx;
}

tensorflow::ServerDef ReplaceTaskInServerDef(

           TempFile(temp_file_name, std::ios::binary | std::ios::trunc), true,
           0});
    } else {
      return;
    }
  }
  TF_VLog(3, "GcsWritableFile: %s with existing file %s", path,
          temp_file_name.c_str());
  TF_SetStatus(status, TF_OK, "");
}

// TODO(vnvo2409): We could download into a local temporary file and use
// memory-mapping.

  typename std::unordered_map<int64_t, Gradient*>::iterator existing =
      accumulated_gradients_.find(tensor_id);
  vspace_.MarkAsResult(tangent);
  if (existing == accumulated_gradients_.end()) {
    accumulated_gradients_.emplace(tensor_id, tangent);
  } else {
    std::array<Gradient*, 2> to_aggregate;
    to_aggregate[0] = tangent;
    to_aggregate[1] = existing->second;