tensorflow_ranking/python/keras/losses.py [31:38]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  SOFTMAX_LOSS = 'softmax_loss'
  UNIQUE_SOFTMAX_LOSS = 'unique_softmax_loss'
  SIGMOID_CROSS_ENTROPY_LOSS = 'sigmoid_cross_entropy_loss'
  MEAN_SQUARED_LOSS = 'mean_squared_loss'
  LIST_MLE_LOSS = 'list_mle_loss'
  APPROX_NDCG_LOSS = 'approx_ndcg_loss'
  APPROX_MRR_LOSS = 'approx_mrr_loss'
  GUMBEL_APPROX_NDCG_LOSS = 'gumbel_approx_ndcg_loss'
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



tensorflow_ranking/python/losses.py [38:45]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  SOFTMAX_LOSS = 'softmax_loss'
  UNIQUE_SOFTMAX_LOSS = 'unique_softmax_loss'
  SIGMOID_CROSS_ENTROPY_LOSS = 'sigmoid_cross_entropy_loss'
  MEAN_SQUARED_LOSS = 'mean_squared_loss'
  LIST_MLE_LOSS = 'list_mle_loss'
  APPROX_NDCG_LOSS = 'approx_ndcg_loss'
  APPROX_MRR_LOSS = 'approx_mrr_loss'
  GUMBEL_APPROX_NDCG_LOSS = 'gumbel_approx_ndcg_loss'
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -