Comments (6)
Sorry I was talking about the https://pypi.org/project/kmedoids/ package, which is using a very similar CI pipeline to build the wheels. I've added a pull request to add those features (arm64 OSX and linux support) to fast-ctc-decode
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Hey! We pretty much copied the fast-ctc-decode CI pipeline (nice work!) for python-kmedoids and recently added arm64 support. Have a look at kno10/python-kmedoids#18, if you would like to publish a pull request yourself.
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I'm not sure that this will work, because Azure does not have Apple Silicon hosts.
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Ah sorry, I missed the OSX part. We already publish arm64 OSX wheels using Github Actions and it appears to be working well. Additionally, we now publish for linux arm64 to enable e.g. using AWS Graviton processors.
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OSX packages are available only for Intel processors https://pypi.org/project/fast-ctc-decode/#files
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thanks @davnn - I've just published v0.3.5 to PyPi.
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Related Issues (20)
- How to use on windows? HOT 2
- RuntimeError: Ran out of search space (beam_cut_threshold too high) HOT 1
- slow running in arm HOT 2
- blank symbol HOT 2
- Any plans to further extend/maintain this project? HOT 2
- How to use search2D? I found the search 1D is default
- Is there an easy way to get the probability of the best path? HOT 2
- crf_beam_search
- Unable to compile code HOT 4
- beam search call result in Killed HOT 2
- how to get text score? HOT 1
- Install on jetson tx2 HOT 6
- could I use the last character/label as the blank label?
- version published to crates.io HOT 3
- what's the difference between viterbi and beam search? HOT 2
- batch beam search? HOT 1
- Compilation error arm64 HOT 1
- could beam search build as a C static library?
- Do the alphabet and shape include the blank symbol? HOT 1
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