[New artifacts] Pre-built (alpha version) pip installable wheels for linux will be made available as part of this release. The pip wheels are compatible from python 3.8 through 3.12. The source builds will continue to work as expected.
[Documentation] We are updating our contribution policy and will be accepting small PRs targetting improving the cudnn-frontend. For full contribution guide refer to our contribution policy.
[API updates] [Python] The graph.execute function in python now takes an optional handle. This is to help user provide a custom handle to the execute function(and achieve parity with the C++ API).
[API updates] Pointwise ops can now take scalars directly as an argument. This simplifies the graph creation process in general. For eg.
auto C = graph.pointwise(A,
graph.tensor(5.0f),
fe::graph::Pointwise_attributes()
.set_mode(fe::PointwiseMode_t::ADD)
.set_compute_data_type(fe::DataType_t::FLOAT));
[Installation] Addresses RFE #64 to provide installation as cmake install
[Installation] Addresses RFE #63 to provide custom installation of catch2. If catch2 is not found, cudnn frontend fetches it automatically from the upstream github repository.
[Logging] Improved logging to print legible tensor names. We will be working on further improvements in future releases to make the logging more streamlined.
[Samples] Add a sample for showcasing auto-tuning to select the best plan among the ones returned from heuristics.
[Samples] As part of v1.2 release, we have created new Jupyter notebooks, showcasing the python API usage. At this point, these will work on A100 and H100 cards only as mentioned in the notebooks. With future releases, we plan to simplify the installation process and elaborate the API usage. Please refer to samples/python directory.
[Bug fixes] Fixed issues related to auto-tuning when the always plan 0 was executed, even though a different plan was chosen as the best candidate.
[Unit Tests] We are adding some unit tests which will provide a way for developers to test parts of the their code before submitting the pull requests. It is highly encouraged to add unit-tests and samples before submitting a pull request.
Note on source installation of python bindings:
In Ubuntu 22.04 debian based systems, when installing without the virtual environment, set ENV DEB_PYTHON_INSTALL_LAYOUT=deb_system. See related issue