code: def create_basic_features(hparams):
      dataset = hparams.problem.dataset(MODES.TRAIN, hparams=hparams)
      dataset = dataset.batch(hparams.batch_size)
      dataset = dataset.map(fill_infer_targets)
      return dataset.make_one_shot_iterator().get_next()
  
file_path: tensor2tensor/tensor2tensor/models/video/nfg_test_utils.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import tempfile
  import numpy
  from tensor2tensor.data_generators import video_generated
  from tensor2tensor.models.video import next_frame_glow
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 3 for calling a global function with example usage: create_basic_features(hparams) and returns: dataset