[Bug Fix] numericalize doesn't create cuda tensor #302
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
Good fix! I also encounter the same problem. Wish to see the update. |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
the fixes to pytorch 0.4 compatibility issues stop creating cuda tensor due to:
tensor_type is torch.LongTensor by default which doesn't accept a
deviceargument. as suggested by migration guide, i change it totorch.tensorfor numericalization.pytorch 0.4 also decouples type, device, layout from creation of tensors. i changed
tensor_typetodtype, because the tensor_type liketorch.LongTensorexplicitly creates a CPU dense tensor of type long, which means more than just a type.