code: def sparse_label(labels):
      maxlen = max(k.shape[0] for k in labels)
      shape = [len(labels), maxlen]  # bxt
      indices = []
      values = []
      for bid, lab in enumerate(labels):
          for tid, c in enumerate(lab):
              indices.append([bid, tid])
              values.append(c)
      indices = np.asarray(indices)
      values = np.asarray(values)
      return (indices, values, shape)
  
file_path: tensorpack/examples/CTC-TIMIT/timitdata.py
imports: import numpy
  from tensorpack import ProxyDataFlow
label_desc: Use image node_id 2 for calling a global function with example usage: sparse_label(labels) and returns: indices,  values,  shape