def load_criterion()

in models.py [0:0]

• 29 lines of code
• 6 McCabe index (conditional complexity)

def load_criterion(criterion_type, preprocessor, config):
    num_tokens = preprocessor.num_tokens
    if criterion_type == "asg":
        num_replabels = config.get("num_replabels", 0)
        use_garbage = config.get("use_garbage", True)
        return (
            ASG(num_tokens, num_replabels, use_garbage),
            num_tokens + num_replabels + int(use_garbage),
        )
    elif criterion_type == "ctc":
        use_pt = config.get("use_pt", True) # use pytorch implementation
        return CTC(num_tokens, use_pt), num_tokens + 1  # account for blank
    elif criterion_type == "transducer":
        blank = config.get("blank", "none")
        transitions = config.get("transitions", None)
        if transitions is not None:
            transitions = gtn.load(transitions)
        criterion = transducer.Transducer(
            preprocessor.tokens,
            preprocessor.graphemes_to_index,
            ngram=config.get("ngram", 0),
            transitions=transitions,
            blank=blank,
            allow_repeats=config.get("allow_repeats", True),
            reduction="mean",
        )
        return criterion, num_tokens + int(blank != "none")
    else:
        raise ValueError(f"Unknown model type {criterion_type}")