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In many domains of computer vision, generative adversarial networks (GANs) have achieved great success, among which the fam- ily of Wasserstein GANs (WGANs) is considered to be state-of-the-art due to the theoretical contributions and competitive qualitative performance
pip install wgandiv-pytorch
PyPI declares 1 unique dependency rule for this release. Environment markers are shown when supplied by the project.
wgandiv-pytorch publishes 1 wheel and 1 source archive for version 0.1.2. Wheel platform tags: any.
Declared Python classifiers: 3.7.
PyPI lists 2 releases with files. The first dated release is ; 2 releases fall within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .