Function evaluate

fun_text_processing/text_normalization/data_loader_utils.py:108–134

Evaluates accuracy given predictions and labels. Args: preds: predictions labels: labels input: optional, only needed for verbosity verbose: if true prints [input], golden labels and predictions Returns accuracy

(
    preds: List[str], labels: List[str], input: Optional[List[str]] = None, verbose: bool = True
)

def evaluate(
    preds: List[str], labels: List[str], input: Optional[List[str]] = None, verbose: bool = True
) -> float:
    """
    Evaluates accuracy given predictions and labels.

    Args:
        preds: predictions
        labels: labels
        input: optional, only needed for verbosity
        verbose: if true prints [input], golden labels and predictions

    Returns accuracy
    """
    acc = 0
    nums = len(preds)
    for i in range(nums):
        pred_norm = clean_generic(preds[i])
        label_norm = clean_generic(labels[i])
        if pred_norm == label_norm:
            acc = acc + 1
        else:
            if input:
                print(f"inpu: {json.dumps(input[i])}")
            print(f"gold: {json.dumps(label_norm)}")
            print(f"pred: {json.dumps(pred_norm)}")
    return acc / nums


def training_data_to_tokens(