code: def _enqueue_batch_direct(self, data_input_coordinator):
      data = self._get(data_input_coordinator)
      if data is None:
          return
      if data_input_coordinator.is_active():
          for b, q, c in zip(
              self._input_blob_names, self._queues, data
          ):
              self._enqueue(b, q, c)
  
imports: import queue
  from itertools import chain
  import logging
  import threading
  import numpy
  import time
  from caffe2.python import workspace, core, scope, utils
  from caffe2.proto import caffe2_pb2
  from caffe2.python.parallel_workers import Metrics, State, WorkerCoordinator, GlobalWorkerCoordinator, Worker, run_worker
label_desc: Use image node_id 8 for calling the BatchFeeder obj's underlying member method code with example usage: obj._enqueue_batch_direct(data_input_coordinator) without return types