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][1]
[1]: https://github.com/NVIDIA/framework-reproducibility
Raw data
{
"_id": null,
"home_page": "https://github.com/NVIDIA/framework-reproducibility",
"name": "framework-reproducibility",
"maintainer": "",
"docs_url": null,
"requires_python": "",
"maintainer_email": "",
"keywords": "framework tensorflow gpu deep-learning determinism reproducibility pytorch seed seeder noise noise-reduction variance-reduction atomics ngc gpu-determinism deterministic-ops frameworks gpu-support d9m r13y fwr13y",
"author": "NVIDIA",
"author_email": "duncan@nvidia.com",
"download_url": "https://files.pythonhosted.org/packages/af/58/03759a430b36ff7ef0693a086d9b6c0f92cf0fc43611bcbce10384735e51/framework-reproducibility-0.5.0.tar.gz",
"platform": "TensorFlow",
"description": "This package provides patches and tools related to determinism\n(bit-accurate, run-to-run reproducibility) in deep learning frameworks, with a\nfocus on determinism when running on GPUs, and a tool (Seeder) for reducing\nvariance in deep learning frameworks.\n\nFor further information, see the documentation in the associated open-source\nrepository: [GitHub/NVIDIA/framework-reproducibility][1]\n\n[1]: https://github.com/NVIDIA/framework-reproducibility",
"bugtrack_url": null,
"license": "Apache 2.0",
"summary": "Providing reproducibility in deep learning frameworks",
"version": "0.5.0",
"project_urls": {
"Homepage": "https://github.com/NVIDIA/framework-reproducibility"
},
"split_keywords": [
"framework",
"tensorflow",
"gpu",
"deep-learning",
"determinism",
"reproducibility",
"pytorch",
"seed",
"seeder",
"noise",
"noise-reduction",
"variance-reduction",
"atomics",
"ngc",
"gpu-determinism",
"deterministic-ops",
"frameworks",
"gpu-support",
"d9m",
"r13y",
"fwr13y"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "17107390ea54c10d6e0250d980f2b07aec1571a97f315327102eeeb936c22ed9",
"md5": "741ddeefaafcc9f465f8e41bb833d292",
"sha256": "591b5dcc61e805d5ef934ba0c1dd376f51290096d4b9f9f56fd1c01c262a8f66"
},
"downloads": -1,
"filename": "framework_reproducibility-0.5.0-py2.py3-none-any.whl",
"has_sig": false,
"md5_digest": "741ddeefaafcc9f465f8e41bb833d292",
"packagetype": "bdist_wheel",
"python_version": "py2.py3",
"requires_python": null,
"size": 18301,
"upload_time": "2023-06-22T22:58:59",
"upload_time_iso_8601": "2023-06-22T22:58:59.340710Z",
"url": "https://files.pythonhosted.org/packages/17/10/7390ea54c10d6e0250d980f2b07aec1571a97f315327102eeeb936c22ed9/framework_reproducibility-0.5.0-py2.py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "af5803759a430b36ff7ef0693a086d9b6c0f92cf0fc43611bcbce10384735e51",
"md5": "c1b9aed0a86e08f0abfdc9c3ffaf043c",
"sha256": "0c62f7b42be2af1cdde9cc8a6b32a6441235fd0c1c31ad057bbf2e868cfa1a09"
},
"downloads": -1,
"filename": "framework-reproducibility-0.5.0.tar.gz",
"has_sig": false,
"md5_digest": "c1b9aed0a86e08f0abfdc9c3ffaf043c",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 8079,
"upload_time": "2023-06-22T22:58:38",
"upload_time_iso_8601": "2023-06-22T22:58:38.816725Z",
"url": "https://files.pythonhosted.org/packages/af/58/03759a430b36ff7ef0693a086d9b6c0f92cf0fc43611bcbce10384735e51/framework-reproducibility-0.5.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-06-22 22:58:38",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "NVIDIA",
"github_project": "framework-reproducibility",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"lcname": "framework-reproducibility"
}