def EMA(beta: float = 1):
    """
    Exponential Moving Average callback.
    Returns a single function that can be called to repeatidly update the EMA
    with a dict of metrics. The callback will return
    the new averaged dict of metrics.

    Note that for `beta=1`, this is just plain averaging.
    """
    fix: tp.Dict[str, float] = defaultdict(float)
    total: tp.Dict[str, float] = defaultdict(float)

    def _update(metrics: dict, weight: float = 1) -> dict:
        nonlocal total, fix
        for key, value in metrics.items():
            total[key] = total[key] * beta + weight * float(value)
            fix[key] = fix[key] * beta + weight
        return {key: tot / fix[key] for key, tot in total.items()}
    return _update
Exponential Moving Average callback.
Returns a single function that can be called to repeatidly update the EMA
with a dict of metrics. The callback will return
the new averaged dict of metrics.

Note that for `beta=1`, this is just plain averaging.
demucs/utils.py