6453091b8ab3713e2d58bad7acc9a4345dc5d10b,pytorch_lightning/metrics/metric.py,MetricCollection,__init__,#MetricCollection#Any#,564

Before Change

    def __init__(self, metrics: Union[List[Metric], Tuple[Metric], Dict[str, Metric]]):
        super().__init__()
        if isinstance(metrics, dict):
            // Check all values are metrics
            for name, metric in metrics.items():
                if not isinstance(metric, Metric):
                    raise ValueError(
                        f"Value {metric} belonging to key {name}"
                        " is not an instance of `pl.metrics.Metric`"
                    )
                self[name] = metric
        elif isinstance(metrics, (tuple, list)):
            for metric in metrics:
                if not isinstance(metric, Metric):
                    raise ValueError(
                        f"Input {metric} to `MetricCollection` is not a instance"
                        " of `pl.metrics.Metric`"
                    )
                name = metric.__class__.__name__
                if name in self:
                    raise ValueError(f"Encountered two metrics both named {name}")
                self[name] = metric
        else:
            raise ValueError("Unknown input to MetricCollection.")

    def forward(self, *args, **kwargs) -> Dict[str, Any]:  // pylint: disable=E0202
        
        Iteratively call forward for each metric. Positional arguments (args) will
        be passed to every metric in the collection, while keyword arguments (kwargs)

After Change

    

    def __init__(self, metrics: Union[List[Metric], Tuple[Metric], Dict[str, Metric]]):
        rank_zero_warn(
            "This `MetricCollection` was deprecated since v1.3.0 in favor of `torchmetrics.MetricCollection`."
            " It will be removed in v1.5.0", DeprecationWarning
        )
        super().__init__(metrics=metrics)

Instances