Archived
This project has been archived by its maintainers, and is no longer receiving any updates.
InterpretSR allows you to approximate the behaviour of multi-layer perceptrons (MLPs) in deep learning models with symbolic equations using PySR.
Installation
pip install interpretsr
Documentation
Full documentation is available at ReadTheDocs.
License
MIT License
1 maintainer
Metadata
1 maintainer
Release files for interpretsr 1.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| interpretsr-1.0.2.tar.gz | 26.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| interpretsr-1.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 33.4 kB
Release files / interpretsr-1.0.2.tar.gz
| Download URL | interpretsr-1.0.2.tar.gz |
|---|---|
| Size | 26.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.11.13
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Release files / interpretsr-1.0.2-py3-none-any.whl
| Download URL | interpretsr-1.0.2-py3-none-any.whl |
|---|---|
| Size | 6.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.11.13
|
