code: def prepare_stop_target(inputs, out_steps):
      """Pad row vectors with 1."""
      max_len = max((x.shape[0] for x in inputs))
      remainder = max_len % out_steps
      pad_len = (
          max_len + (out_steps - remainder)
          if remainder > 0
          else max_len
      )
      return np.stack([_pad_stop_target(x, pad_len) for x in inputs])
  
file_path: TTS/TTS/tts/utils/data.py
imports: import numpy
label_desc: Use image node_id 6 for calling a global function with example usage: prepare_stop_target(inputs, out_steps) and returns: np