code: def batch_feature(feats):
      # pad to the longest in the batch
      maxlen = max(k.shape[0] for k in feats)
      bsize = len(feats)
      ret = np.zeros((bsize, maxlen, feats[0].shape[1]))
      for idx, feat in enumerate(feats):
          ret[idx, : feat.shape[0], :] = feat
      return ret
  
file_path: tensorpack/examples/CTC-TIMIT/timitdata.py
imports: import numpy
  from tensorpack import ProxyDataFlow
label_desc: Use image node_id 1 for calling a global function with example usage: batch_feature(feats) and returns: ret