code: def to_sparse_tuple(sequence):
      r"""Creates a sparse representention of ``sequence``.
      Returns a tuple with (indices, values, shape)
      """
      indices = np.asarray(
          list(zip([0] * len(sequence), range(len(sequence)))),
          dtype=np.int64,
      )
      shape = np.asarray([1, len(sequence)], dtype=np.int64)
      return indices, sequence, shape
  
file_path: DeepSpeech/training/deepspeech_training/util/feeding.py
imports: from __future__ import absolute_import, division, print_function
  from collections import Counter
  from functools import partial
  import numpy
  import tensorflow
  from tensorflow.python.ops import gen_audio_ops
  from .config import Config
  from .text import text_to_char_array
  from .flags import FLAGS
  from .augmentations import apply_sample_augmentations, apply_graph_augmentations
  from .audio import read_frames_from_file, vad_split, pcm_to_np, DEFAULT_FORMAT
  from .sample_collections import samples_from_sources
  from .helpers import remember_exception, MEGABYTE
label_desc: Use image node_id 4 for calling a global function with example usage: to_sparse_tuple(sequence) and returns: indices,  sequence,  shape