code: def load_data(inference_input_file, hparams=None):
      """Load inference data."""
      with codecs.getreader("utf-8")(
          tf.gfile.GFile(inference_input_file, mode="rb")
      ) as f:
          inference_data = f.read().splitlines()
  
      if hparams and hparams.inference_indices:
          inference_data = [
              inference_data[i] for i in hparams.inference_indices
          ]
  
      return inference_data
  
file_path: nlp-architect/examples/sparse_gnmt/inference.py
imports: from __future__ import print_function
  import codecs
  import os
  import time
  import tensorflow
  from .None import gnmt_model
  from .gnmt import attention_model, model
  from .gnmt import model_helper
  from .gnmt.utils import nmt_utils, misc_utils
label_desc: Use image node_id 2 for calling a global function with example usage: load_data(inference_input_file, hparams) and returns: inference_data