Metadata-Version: 2.1
Name: framework-reproducibility
Version: 0.4.0
Summary: Providing reproducibility in deep learning frameworks
Home-page: https://github.com/NVIDIA/framework-reproducibility
Author: NVIDIA
Author-email: duncan@nvidia.com
License: Apache 2.0
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][1]
        
        [1]: https://github.com/NVIDIA/framework-reproducibility
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
Platform: TensorFlow
Platform: PyTorch
Platform: PaddlePaddle
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python
Description-Content-Type: text/markdown
