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Deep Learning library that extends the mlr3 framework by building upon the 'torch' package. It allows to conveniently build, train, and evaluate deep learning models without having to worry about low level details. Custom architectures can be created using the graph language defined in 'mlr3pipelines'.

Options

  • mlr3torch.cache: Whether to cache the downloaded data (TRUE) or not (FALSE, default). This can also be set to a specific folder on the file system to be used as the cache directory.

Author

Maintainer: Sebastian Fischer sebf.fischer@gmail.com (ORCID)

Authors:

Other contributors: