A PyTorch implementation of Scalable Training of Artificial Neural Networks with Adaptive Sparse Connectivity inspired by Network Science by Mocanu et al. (https://arxiv.org/abs/1707.04780) Uses sparse data structures. Not super fast yet, but less memory-intensive than the masked dense weight matrices used in the proof-of-concept code released with the paper.
1 maintainer
Metadata
1 maintainer
Release files for synapses 0.0.14
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| synapses-0.0.14.tar.gz | 3.7 kB | Without provenance | Details for synapses-0.0.14.tar.gz |
Release files / synapses-0.0.14.tar.gz
| Download URL | synapses-0.0.14.tar.gz |
|---|---|
| Size | 3.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
bf70e5768b9de90d30477f0468f925b67de8893497a5dae15eb73a4c69d811c4
|
|
BLAKE2b-256 checksum How to use checksums |
352f82bb5e5154bcdd83fafb8540ec3b1577236bcbedc8dea37888fa4d4b1747
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
Python-urllib/3.6
|
Security for synapses 0.0.14
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
