Concatenation
Module Interface
- class torchmetrics.aggregation.CatMetric(nan_strategy='warn', **kwargs)[source]
Concatenate a stream of values.
As input to
forward
andupdate
the 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_strategy
is not one oferror
,warn
,ignore
,disable
or 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.])