docstr: Fetch a batch of data without waiting
docstr_tok: ["Fetch","a","batch","of","data","without","waiting"]
code: def fetch_batch(self):
      """Fetch a batch of data without waiting"""
      inp, f = self.queue.get()
      nr_input_var = len(inp)
      batched, futures = [[] for _ in range(nr_input_var)], []
      for k in range(nr_input_var):
          batched[k].append(inp[k])
      futures.append(f)
      while len(futures) < self.batch_size:
          try:
              inp, f = self.queue.get_nowait()
              for k in range(nr_input_var):
                  batched[k].append(inp[k])
              futures.append(f)
          except queue.Empty:
              break  # do not wait
  
      for k in range(nr_input_var):
          batched[k] = np.asarray(batched[k])
      return batched, futures
  
imports: import multiprocessing
  import numpy
  from concurrent.futures import Future
  import tensorflow
  from six.moves import queue, range
  from ..compat import tfv1
  from ..tfutils.model_utils import describe_trainable_vars
  from ..utils import logger
  from ..utils.concurrency import DIE, ShareSessionThread, StoppableThread
  from .base import AsyncPredictorBase, OfflinePredictor, OnlinePredictor
label_desc: Use image node_id 3 for calling the PredictorWorkerThread obj's underlying member method code with example usage: obj.fetch_batch() and returns: batched,  futures