code: def get_best_start_end_position(self, start_scores, end_scores):
      answer_start = tf.argmax(start_scores, axis=1).numpy()[0]
      answer_end = (tf.argmax(end_scores, axis=1) + 1).numpy()[0]
      return answer_start, answer_end
  
file_path: neuralqa/neuralqa/reader/bertreader.py
imports: from neuralqa.reader import Reader
  import tensorflow
  import numpy
  import time
  import logging
label_desc: Use image node_id 2 for calling the BERTReader obj's underlying member method code with example usage: obj.get_best_start_end_position(start_scores, end_scores) and returns: answer_start,  answer_end