Providing reproducibility in deep learning frameworks
Project description
This package provides patches and tools related to determinism (bit-accurate, run-to-run reproducibility) in deep learning frameworks, with a focus on determinism when running on GPUs, and a tool (Seeder) for reducing variance in deep learning frameworks.
For further information, see the documentation in the associated open-source repository: GitHub/NVIDIA/framework-reproducibility
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file framework-reproducibility-0.6.0.tar.gz.
File metadata
- Download URL: framework-reproducibility-0.6.0.tar.gz
- Upload date:
- Size: 8.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.15.0 pkginfo/1.5.0.1 requests/2.18.4 setuptools/44.1.1 requests-toolbelt/0.9.1 tqdm/4.19.5 CPython/2.7.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 7b10bf8963da47bb7b7afb63de8622fb3f925cdb25bda1400b4f49870166e253 |
|
| MD5 | 542e1537dc80f76ae2dc0236d551c3bc |
|
| BLAKE2b-256 | a1e5cfb093bbf90c810d521f117cd576504844993e9c4f8635c1942ce43d289c |
File details
Details for the file framework_reproducibility-0.6.0-py2.py3-none-any.whl.
File metadata
- Download URL: framework_reproducibility-0.6.0-py2.py3-none-any.whl
- Upload date:
- Size: 19.2 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.15.0 pkginfo/1.5.0.1 requests/2.18.4 setuptools/44.1.1 requests-toolbelt/0.9.1 tqdm/4.19.5 CPython/2.7.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 68b75c67ac9ad8558ee66490fce509ace43f2243a86d50d13dd9f1564b4f02e4 |
|
| MD5 | 53afd5d1809317438115e0a6503ee4c0 |
|
| BLAKE2b-256 | e6247f260b16f913baa88feeb34134a9004bcc0b69352f45b3d210f72e3b512a |
