Fast, differentiable sorting and ranking without custom C++ or CUDA extensions. This is a lightweight implementation of Fast Differentiable Sorting and Ranking (Blondel et al.) based on fast-soft-sort and inspired by torchsort. Unlike torchsort, this version requires no custom C++ or CUDA extensions, making it easy to install and portable across platforms. While optimized C++/CUDA implementations may have a performance advantage for extremely large sequence lengths, this version is optimized for typical deep learning workflows. Try it here:
Installation
pip install torchpsort
1 maintainer
Metadata
1 maintainer
Release files for torchpsort 0.1.8
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| torchpsort-0.1.8.tar.gz | 6.7 kB | Without provenance | Details for torchpsort-0.1.8.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| torchpsort-0.1.8-py3-none-any.whl | Python 3 | none | any | Details for torchpsort-0.1.8-py3-none-any.whl |
Total release size: 15.4 kB
Release files / torchpsort-0.1.8.tar.gz
| Download URL | torchpsort-0.1.8.tar.gz |
|---|---|
| Size | 6.7 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / torchpsort-0.1.8-py3-none-any.whl
| Download URL | torchpsort-0.1.8-py3-none-any.whl |
|---|---|
| Size | 8.7 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Security for torchpsort 0.1.8
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