Comments (6)
@SkafteNicki mind have look? :]
from torchmetrics.
Definitely an lack of support from pytorch side, but seems to be on track to be solved:
Issue: pytorch/pytorch#49889
PR with fix: pytorch/pytorch#49895
I can try to see if the code can be rewritten with operations that support float16
Probably should also add test for float16
in general for metrics.
from torchmetrics.
Just a follow up: the following metrics does not work with float16 CPU because of lack of support from a list of pytorch operations (in parentheses)
- SSIM (torch.arange)
- PSNR (torch.pow)
- MeanSquaredLogError (torch.logp1 & torch.pow)
- MeanSquaredError (torch.pow)
- ExplainedVariance (torch.pow)
- PrecisionRecallCurve (torch.flip)
- AveragePrecision (torch.flip)
@Borda how to move forward with this? I think some of these can be converted in operations that support float16 CPU (pow can be made to multiplication) but I am not sure about all of them
from torchmetrics.
from torchmetrics.
Hi! thanks for your contribution!, great first issue!
from torchmetrics.
looks like this was fixed in pytorch/pytorch@5d93e2b
from torchmetrics.
Related Issues (20)
- Multiple threshold for Multilabel metrics HOT 1
- Cannot import the "clustering" module HOT 5
- Potentially Misleading Error Message for multiclass_precision HOT 2
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- procrustes alignment HOT 6
- Please don't make us specify the number of outputs for R2Score HOT 1
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from torchmetrics.