snn_bench

A Project for independently testable components for data ingestion, ANN training, ANN to SNN conversion, evaluation and results visualization.

Installation

pip install git+https://github.com/fangwei123456/spikingjelly.git
pip install snn-bench

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution for snn-bench 0.1.73
File	Size	Uploaded
snn_bench-0.1.73.tar.gz	8.5 MB	Sep 25, 2026	Details

Table of built distributions (wheels) for snn-bench 0.1.73
File	Interpreter	ABI	Platform	Reset
snn_bench-0.1.73-py3-none-any.whl 74.6 kB Sep 25, 2026	Python 3	none	any	Details

Total release size: 8.6 MB

Download URL	snn_bench-0.1.73.tar.gz
Size	8.5 MB
Tags	Source
SHA-256 checksum How to use checksums	`6387b32844530c5a259bc0fe6bf8ef155abf08a399862aa779775764f5336b17`
BLAKE2b-256 checksum How to use checksums	`11ba1aa9ac0f01fb89800185d1ef525e0bd89d5f95549c2a5d2cfca6d12207ef`
Upload date	Sep 25, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.14.0`

Download URL	snn_bench-0.1.73-py3-none-any.whl
Size	74.6 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`017d9ec3ca80e3e5490c656223549f357bec7d453dd61980340441722e129f29`
BLAKE2b-256 checksum How to use checksums	`fcdbc8ad9de757d8a4170bdb2d4230b55e38cc393dcdea490c17e533b8e99b8e`
Upload date	Sep 25, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.14.0`