code: def apply_gradients(self):
      grads = [(g, v) for (v, g) in self.accum_vars.items()]
      with tf.control_dependencies([self.opt.apply_gradients(grads)]):
          return self.total_loss / self.count_loss
  
file_path: gpt-2-simple/gpt_2_simple/src/accumulate.py
imports: import argparse
  import json
  import os
  import numpy
  import tensorflow
  import time
label_desc: Use image node_id 4 for calling the AccumulatingOptimizer obj's underlying member method code with example usage: obj.apply_gradients() and returns: unknown