code: def variable_on_cpu(name, shape, initializer):
      r"""
      Next we concern ourselves with graph creation.
      However, before we do so we must introduce a utility function ``variable_on_cpu()``
      used to create a variable in CPU memory.
      """
      # Use the /cpu:0 device for scoped operations
      with tf.device(Config.cpu_device):
          # Create or get apropos variable
          var = tfv1.get_variable(
              name=name, shape=shape, initializer=initializer
          )
      return var
  
imports: from __future__ import absolute_import, division, print_function
  import os
  import sys
  import absl.app
  import numpy
  import progressbar
  import shutil
  import tensorflow
  import tensorflow.compat.v1
  import time
  from datetime import datetime
  from ds_ctcdecoder import ctc_beam_search_decoder, Scorer
  from .evaluate import evaluate
  from six.moves import zip, range
  from .util.config import Config, initialize_globals
  from .util.checkpoints import load_or_init_graph_for_training, load_graph_for_evaluation, reload_best_checkpoint
  from .util.evaluate_tools import save_samples_json
  from .util.feeding import create_dataset, audio_to_features, audiofile_to_features
  from .util.flags import create_flags, FLAGS
  from .util.helpers import check_ctcdecoder_version, ExceptionBox
  from .util.logging import create_progressbar, log_debug, log_error, log_info, log_progress, log_warn
  from .util.io import open_remote, remove_remote, listdir_remote, is_remote_path, isdir_remote
label_desc: Use image node_id 1 for calling a global function with example usage: variable_on_cpu(name, shape, initializer) and returns: var