code: def model_loss(y, model, mean=True):
    
    warnings.warn("This function is deprecated and will be removed on or after"
                  " 2019-04-05. Switch to cleverhans.train.train.")
    op = model.op
    if op.type == "Softmax":
      logits, = op.inputs
    else:
      logits = model
  
    out = softmax_cross_entropy_with_logits(logits=logits, labels=y)
  
    if mean:
      out = reduce_mean(out)
    return out
docs: Define loss of TF graph
    :param y: correct labels
    :param model: output of the model
    :param mean: boolean indicating whether should return mean of loss
                 or vector of losses for each input of the batch
    :return: return mean of loss if True, otherwise return vector with per
             sample loss