cudnn frontend v1.2.0 release #68
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
…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.
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
[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.
[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/pythondirectory.[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