2409ca833031ab770e68a334cf2686d1d8d930d1,jiant/proj/main/modeling/taskmodels.py,,get_output_from_encoder,#Any#Any#Any#Any#,288

Before Change

    output = encoder(input_ids=input_ids, token_type_ids=segment_ids, attention_mask=input_mask)
    if len(output) == 2:
        return EncoderOutput(pooled=output[1], unpooled=output[0],)
    elif len(output) > 2:
        // Extend later with attention, hidden_acts, etc
        return EncoderOutput(pooled=output[1], unpooled=output[0], other=output[2:])
    else:
        raise RuntimeError()


def compute_mlm_loss(logits, masked_lm_labels):
    vocab_size = logits.shape[-1]

After Change

        pooled, unpooled, other = get_output_from_electra(
            encoder=encoder, input_ids=input_ids, segment_ids=segment_ids, input_mask=input_mask,
        )
    elif model_arch in [
        ModelArchitectures.BART,
        ModelArchitectures.MBART,
    ]:
        pooled, unpooled, other = get_output_from_bart_models(
            encoder=encoder, input_ids=input_ids, input_mask=input_mask,
        )

Instances