Example #1
0
def _run_crossencoder(crossencoder,
                      dataloader,
                      logger,
                      context_len,
                      device="cuda"):
    crossencoder.model.eval()
    accuracy = 0.0
    crossencoder.to(device)

    res = evaluate(crossencoder,
                   dataloader,
                   device,
                   logger,
                   context_len,
                   zeshel=False,
                   silent=False)
    accuracy = res["normalized_accuracy"]
    logits = res["logits"]

    if accuracy > -1:
        predictions = np.argsort(logits, axis=1)
    else:
        predictions = []

    return accuracy, predictions, logits
Example #2
0
def _run_crossencoder(crossencoder,
                      dataloader,
                      logger,
                      context_len,
                      device="cpu"):
    crossencoder.model.eval()
    accuracy = 0.0
    crossencoder.to(device)

    res = evaluate(crossencoder,
                   dataloader,
                   device,
                   logger,
                   context_len,
                   silent=True)
    accuracy = res["normalized_accuracy"]
    logits = res["logits"]

    predictions = np.argsort(logits, axis=1)
    return accuracy, predictions, logits