a9eb2fd38180b5affbd30ec78f33f6ef16ef9c20,src/gluonnlp/model/bert.py,BERTModel,_apply_pooling,#BERTModel#Any#,462

Before Change

        This is used for pre-training or fine-tuning a BERT model.
        
        outputs = sequence[:, 0, :]
        return self.pooler(outputs)

    def _decode(self, sequence, masked_positions):
        Generate unnormalized prediction for the masked language model task.

After Change

        This is used for pre-training or fine-tuning a BERT model.
        
        outputs = sequence.slice(begin=(0, 0, 0), end=(None, 1, None))
        outputs = outputs.reshape(shape=(-1, self._units))
        return self.pooler(outputs)

    def _arange_like(self, F, inputs):
        Helper function to generate int32 indices of a range

Instances