code: def get_from_batch(batch, idx):
      k = max([len(row[idx]) for row in batch])
      return list([NerModel.fill(row[idx], k, 0) for row in batch])
  
imports: import math
  import random
  import sys
  import numpy
  import tensorflow
  from .sentence_grouper import SentenceGrouper
  from ..tf2contrib import *
label_desc: Use image node_id 16 for calling the NerModel obj's underlying member method code with example usage: obj.get_from_batch(batch, idx) and returns: list