Mean¶
Module Interface¶
- class torchmetrics.MeanMetric(nan_strategy='warn', **kwargs)[source]
Aggregate a stream of value into their mean value.
As input to
forward
andupdate
the metric accepts the following inputvalue
(float
orTensor
): a single float or an tensor of float values with arbitary shape(...,)
.weight
(float
orTensor
): a single float or an tensor of float value with arbitary shape(...,)
. Needs to be broadcastable with the shape ofvalue
tensor.
As output of forward and compute the metric returns the following output
agg
(Tensor
): scalar float tensor with aggregated (weighted) mean over all inputs received
- Parameters
nan_strategy¶ (
Union
[str
,float
]) –- options:
'error'
: if any nan values are encounted will give a RuntimeError'warn'
: if any nan values are encounted will give a warning and continue'ignore'
: all nan values are silently removeda float: if a float is provided will impude any nan values with this value
kwargs: Additional keyword arguments, see Advanced metric settings for more info.
- Raises
ValueError – If
nan_strategy
is not one oferror
,warn
,ignore
or a float
Example
>>> from torchmetrics import MeanMetric >>> metric = MeanMetric() >>> metric.update(1) >>> metric.update(torch.tensor([2, 3])) >>> metric.compute() tensor(2.)
Initializes internal Module state, shared by both nn.Module and ScriptModule.