>>> from torchmetrics.regression import SpearmanCorrCoef
>>> n = 10
>>> x = torch.randn((n,))
>>> y = torch.randn((n,))
>>> corr = SpearmanCorrCoef()(x, y)
/home/monodme1/.conda/envs/rad-env/lib/python3.10/site-packages/torchmetrics/utilities/prints.py:43: UserWarning: Metric `SpearmanCorrcoef` will save all targets and predictions in the buffer. For large datasets, this may lead to large memory footprint.
warnings.warn(*args, **kwargs) # noqa: B028
What's the best practice to remove this warning?