d63abb86304d5ceca8ec14109a4812258f9839ea,scripts/bert/finetune_classifier.py,,evaluate,#Any#Any#Any#,544

Before Change

    tic = time.time()
    for batch_id, seqs in enumerate(loader_dev):
        input_ids, valid_len, type_ids, label = seqs
        out = model(
            input_ids.as_in_context(ctx), type_ids.as_in_context(ctx),
            valid_len.astype("float32").as_in_context(ctx))
        ls = loss_function(out, label.as_in_context(ctx)).mean()

        step_loss += ls.asscalar()
        metric.update([label], [out])

After Change

    for batch_id, seqs in enumerate(loader_dev):
        input_ids, valid_length, segment_ids, label = seqs
        input_ids = input_ids.as_in_context(ctx)
        valid_length = valid_length.as_in_context(ctx).astype("float32")
        label = label.as_in_context(ctx)
        if use_roberta:
            out = model(input_ids, valid_length)
        else:
            out = model(input_ids, segment_ids.as_in_context(ctx), valid_length)
        ls = loss_function(out, label).mean()

        step_loss += ls.asscalar()
        metric.update([label], [out])

Instances