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Fixes from running .gitignore:python/nx-cugraph/objects.inv
docs/nx-cugraph/source/nx_cugraph/how-it-works.md:The latest list of algorithms supported by nx-cugraph can be found [here](https://github.com/rapidsai/cugraph/blob/HEAD/python/nx-cugraph/README.md#algorithms) or in the next section. docs/nx-cugraph/source/nx_cugraph/index.rst:By simply `installing and enabling nx-cugraph <https://github.com/rapidsai/cugraph/blob/HEAD/python/nx-cugraph/README.md#install>`_, users can see significant speedup on workflows where performance is hindered by the default NetworkX implementation. With ``nx-cugraph``, users can have GPU-based, large-scale performance **without** changing their familiar and easy-to-use NetworkX code.
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