6bf3f51cd0a312da842157665663c2dad9983248,tensorflow_ranking/python/losses_impl.py,ClickEMLoss,_compute_latent_prob,#ClickEMLoss#Any#Any#Any#,914

Before Change

              tf.compat.v1.where(is_clicked, tf.ones_like(prob), prob))
          for prob in [exam_prob_given_non_clicks, rel_prob_given_non_clicks]
      ]
      return exam_prob_given_non_clicks, rel_prob_given_non_clicks

  def compute_unreduced_loss(self, labels, logits):
    Computes the loss for each element.

After Change

    
    with tf.compat.v1.name_scope(name="compute_latent_prob"):
      is_clicked = tf.greater_equal(tf.cast(clicks, tf.float32), 1.0)
      exam_logits_posterior = exam_logits - tf.math.softplus(rel_logits)
      rel_logits_posterior = rel_logits - tf.math.softplus(exam_logits)
      exam_prob_posterior = tf.compat.v1.where(
          is_clicked, tf.ones_like(exam_logits_posterior),
          tf.sigmoid(exam_logits_posterior))
      rel_prob_posterior = tf.compat.v1.where(
          is_clicked, tf.ones_like(rel_logits_posterior),
          tf.sigmoid(rel_logits_posterior))
      return tf.stop_gradient(exam_prob_posterior), tf.stop_gradient(
          rel_prob_posterior)

  def compute_unreduced_loss(self, labels, logits):
    Computes the loss for each element.

Instances