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Bugfix: initializing all tensors and parameters of the ConditionalRandomField model on the proper device
#5335
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…ndomField` in the proper device
dirkgr
suggested changes
Aug 18, 2021
| @@ -364,7 +364,7 @@ def viterbi_tags( | |||
| # Augment transitions matrix with start and end transitions | |||
| start_tag = num_tags | |||
| end_tag = num_tags + 1 | |||
| transitions = torch.Tensor(num_tags + 2, num_tags + 2).fill_(-10000.0) | |||
| transitions = torch.empty(num_tags + 2, num_tags + 2, device=logits.device).fill_(-10000.0) | |||
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This should use torch.full(), so we can create the tensor in one go.
|
Ah, it also needs an entry in the changelog. So two little changes I guess. |
dirkgr
approved these changes
Aug 18, 2021
|
Thank you! |
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Bugfix:
crf_taggerwas doing most of the computations on the CPU, as theConditionalRandomFieldmodel's parameters and some necessary tensors were initialized on the wrong device.Fixes #2884 .
Changes proposed in this pull request:
ConditionalRandomField'stransitionsandtag_sequencetensors are initialized on the proper deviceBefore submitting
section of the
CONTRIBUTINGdocs.Writing docstrings section of the
CONTRIBUTINGdocs.After submitting
codecov/patchreports high test coverage (at least 90%).You can find this under the "Actions" tab of the pull request once the other checks have finished.