39fba153bae06e7c6528e1d0a87d19ecfac72c57,official/nlp/tasks/sentence_prediction.py,SentencePredictionTask,build_model,#SentencePredictionTask#,69

Before Change

  def build_model(self):
    if self._hub_module:
      encoder_from_hub = utils.get_encoder_from_hub(self._hub_module)
      return bert.instantiate_bertpretrainer_from_cfg(
          self.task_config.model, encoder_network=encoder_from_hub)
    else:
      return bert.instantiate_bertpretrainer_from_cfg(self.task_config.model)

  def build_losses(self, labels, model_outputs, aux_losses=None) -> tf.Tensor:

After Change

    if self._hub_module:
      encoder_network = utils.get_encoder_from_hub(self._hub_module)
    else:
      encoder_network = encoders.instantiate_encoder_from_cfg(
          self.task_config.model.encoder)

    // Currently, we only supports bert-style sentence prediction finetuning.
    return models.BertClassifier(
        network=encoder_network,
        num_classes=self.task_config.model.num_classes,
        initializer=tf.keras.initializers.TruncatedNormal(
            stddev=self.task_config.model.encoder.initializer_range),
        use_encoder_pooler=self.task_config.model.use_encoder_pooler)

  def build_losses(self, labels, model_outputs, aux_losses=None) -> tf.Tensor:
    loss = tf.keras.losses.sparse_categorical_crossentropy(
        labels, tf.cast(model_outputs, tf.float32), from_logits=True)

Instances