Concatenation¶
Module Interface¶
- class torchmetrics.aggregation.CatMetric(nan_strategy='warn', **kwargs)[source]¶
Concatenate a stream of values.
As input to
forwardandupdatethe metric accepts the following inputAs output of forward and compute the metric returns the following output
agg(Tensor): scalar float tensor with concatenated values over all input received
- Parameters:
nan_strategy¶ (
Union[Literal['error','warn','ignore','disable'],float]) – options: -'error': if any nan values are encountered will give a RuntimeError -'warn': if any nan values are encountered will give a warning and continue -'ignore': all nan values are silently removed -'disable': disable all nan checks - a float: if a float is provided will impute any nan values with this valuekwargs¶ (
Any) – Additional keyword arguments, see Advanced metric settings for more info.
- Raises:
ValueError – If
nan_strategyis not one oferror,warn,ignore,disableor a float
Example
>>> from torch import tensor >>> from torchmetrics.aggregation import CatMetric >>> metric = CatMetric() >>> metric.update(1) >>> metric.update(tensor([2, 3])) >>> metric.compute() tensor([1., 2., 3.])