PyExML
pyexlab Extension using torch for Machine Learning
Author: Blake Wilson
Overview
Running machine learning experiments can be a huge hassle. Optimizing hyper parameters, saving off specific data throughout epochs, and modifying models without breaking code are just a few of the headaches I come across on a daily basis. pyexml simplifies the design process for machine learning experimentation by building on top of the pyexlab package.
1 maintainer
Metadata
1 maintainer
Release files for pyexml 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pyexml-0.0.1.tar.gz | 11.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pyexml-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 29.7 kB
Release files / pyexml-0.0.1.tar.gz
| Download URL | pyexml-0.0.1.tar.gz |
|---|---|
| Size | 11.8 kB |
| Tags | Source |
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Release files / pyexml-0.0.1-py3-none-any.whl
| Download URL | pyexml-0.0.1-py3-none-any.whl |
|---|---|
| Size | 17.8 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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twine/4.0.1 CPython/3.10.7
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