code: def compute_gradients(self, loss):
      grads = self.opt.compute_gradients(loss, self.var_list)
      updates = [self.accum_vars[v].assign_add(g) for (g, v) in grads]
      updates.append(self.total_loss.assign_add(loss))
      updates.append(self.count_loss.assign_add(1.0))
      with tf.control_dependencies(updates):
          return tf.no_op()
  
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 3 for calling the AccumulatingOptimizer obj's underlying member method code with example usage: obj.compute_gradients(loss) and returns: tf