code: def _merge_train_op_list(train_op_list, no_train_speedup):
      """Merges a train_op list into one train_op."""
      if not train_op_list:
          global_step = tf.compat.v1.train.get_or_create_global_step()
          # Train is 100 times faster. No parameters to train here.
          train_op = tf.compat.v1.assign(
              global_step, global_step + no_train_speedup
          )
      elif len(train_op_list) == 1:
          train_op = train_op_list[0]
      else:
          train_op = tf.group(*train_op_list)
  
      return train_op
  
imports: import collections
  import functools
  import inspect
  from absl import logging
  from model_search import block_builder
  from model_search import ensembler
  from model_search.architecture import architecture_utils
  from model_search.architecture import tower
  from model_search.ensembler import EnsembleLogits
  from model_search.generators import base_tower_generator
  from model_search.generators import trial_utils
  from model_search.meta import distillation
  import numpy
  import tensorflow.compat.v2
label_desc: Use image node_id 6 for calling a global function with example usage: _merge_train_op_list(train_op_list, no_train_speedup) and returns: train_op