Common utils for deep learning
Documentation: https://utilsd.readthedocs.io/en/stable/
pip install utilsd
What is utilsd?
I'm collecting common utils that are used in at least 2 of the projects I have been working on. I expect most of the utils are in the corner of logging, experiment setup, config management, log analysis, and etc. As I almost always use PyTorch and most of the projects are featuring vision tasks, it will be built upon PyTorch.
Why it is named utilsd?
To join the D-universe that is powered by several ambitious system researchers.
Is it a stable toolkit I can use?
Not really. It is still a draft and being tested against multiple internal projects. I will try to write documentation for this project within a couple of months (or give up on it forever).
Metadata
Release files for utilsd 0.0.18.post0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| utilsd-0.0.18.post0.tar.gz | 36.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| utilsd-0.0.18.post0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 81.6 kB
Release files / utilsd-0.0.18.post0.tar.gz
| Download URL | utilsd-0.0.18.post0.tar.gz |
|---|---|
| Size | 36.9 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/4.0.2 CPython/3.11.4
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Release files / utilsd-0.0.18.post0-py3-none-any.whl
| Download URL | utilsd-0.0.18.post0-py3-none-any.whl |
|---|---|
| Size | 44.7 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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| Uploaded via |
twine/4.0.2 CPython/3.11.4
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