code: def random_feed_dict(rng, placeholders):
    
  
    output = {}
  
    for placeholder in placeholders:
      if placeholder.dtype != 'float32':
        raise NotImplementedError()
      value = rng.randn(*placeholder.shape).astype('float32')
      output[placeholder] = value
  
    return output
docs: Returns random data to be used with `feed_dict`.
    :param rng: A numpy.random.RandomState instance
    :param placeholders: List of tensorflow placeholders
    :return: A dict mapping placeholders to random numpy values