3c874575bf40e8b1fa2280371131a8f29ebb3e98,src/gluonnlp/models/mobilebert.py,MobileBertModel,hybrid_forward,#MobileBertModel#Any#Any#Any#Any#,484

Before Change

        embedding = self.get_initial_embedding(F, inputs, token_types)

        contextual_embeddings, additional_outputs = self.encoder(embedding, valid_length)
        outputs = []
        outputs.append(contextual_embeddings)
        if self.use_pooler:
            pooled_out = self.apply_pooling(contextual_embeddings)
            outputs.append(pooled_out)
        return tuple(outputs) if len(outputs) > 1 else outputs[0]

    def get_initial_embedding(self, F, inputs, token_types=None, trigram_embed=True):
        Get the initial token embeddings that considers the token type and positional embeddings

After Change

        
        embedding = self.get_initial_embedding(F, inputs, token_types)

        if self._compute_layout != self._layout:
            contextual_embeddings, additional_outputs = self.encoder(F.np.swapaxes(embedding, 0, 1),
                                                                     valid_length)
            contextual_embeddings = F.np.swapaxes(contextual_embeddings, 0, 1)
        else:
            contextual_embeddings, additional_outputs = self.encoder(embedding, valid_length)
        if self.use_pooler:
            pooled_out = self.apply_pooling(contextual_embeddings)
            return contextual_embeddings, pooled_out
        else:

Instances