Bugfix: handle case where 'losses' is a list of tensors #1357
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jdb78
reviewed
Sep 10, 2023
| @@ -822,6 +822,9 @@ def mask_losses(self, losses: torch.Tensor, lengths: torch.Tensor, reduction: st | |||
| """ | |||
| if reduction is None: | |||
| reduction = self.reduction | |||
|
|
|||
| if isinstance(losses, list): losses = losses[0] | |||
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Should that not be something like
losses = [self.mask_losses(loss, lengths, reduction=reduction) for loss in losses]?
|
BTW: Would be great to have a test for this! |
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Description
This PR fixes an issue I came across when applying NHiTS and TFT on my use case, namely that
lossescan be tensors within a list. In that case, the functionmask_losseswill fail. It is just a one-liner in base_metrics.py.