1357ce1904eb522f7fbfa46f7edcf091162287b7,official/nlp/bert/bert_models.py,BertPretrainLossAndMetricLayer,call,#BertPretrainLossAndMetricLayer#Any#Any#Any#Any#Any#,69

Before Change

    if sentence_labels is not None:
      sentence_output = tf.cast(sentence_output, tf.float32)
      sentence_loss = losses.weighted_sparse_categorical_crossentropy_loss(
          labels=sentence_labels, predictions=sentence_output)
      loss = mask_label_loss + sentence_loss
    else:
      sentence_loss = None
      loss = mask_label_loss

After Change

    if sentence_labels is not None:
      sentence_output_logits = tf.cast(sentence_output_logits, tf.float32)
      sentence_loss = tf.keras.losses.sparse_categorical_crossentropy(
          sentence_labels, sentence_output_logits, from_logits=True)
      sentence_loss = tf.reduce_mean(sentence_loss)
      loss = mask_label_loss + sentence_loss
    else:
      sentence_loss = None

Instances