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Tensorflow pluggable device #387
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Resolves issue 381. |
In order for the experimental feature to work properly on an Apple M1 chip, it is necessary to satisfy these dependencies:
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Please ensure that |
Can you rerun the checks @adamcrume? I don't remember what was wrong :) |
Closes #402 |
I tested code by running workflow in my repository. |
I believe I resolved all the issues. Can you please trigger the workflow run, @adamcrume? |
I am happy to see all the checks pass :) |
There was another pull request for this (#402), but it didn't have the macOS test. Could you rebase? It would still be nice to use this PR for the test. |
@@ -59,6 +59,7 @@ compiled library will be picked up. | |||
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**macOS Note**: Via [Homebrew](https://brew.sh/), you can just run | |||
`brew install libtensorflow`. | |||
[tensorflow metal plugin]: https://developer.apple.com/metal/tensorflow-plugin/ |
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This doesn't render properly (https://github.com/Apurer/rust/tree/feature/experimental/tensorflow-sys). It also needs some explanation. Do users need to follow that link and do anything specific?
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I'll fix the rendering issue. Yes, users need to click on the provided link to set up the TensorFlow plugin on Apple computers. I considered including the steps listed on developer.apple.com, but I was unsure if the steps would be updated.
I will rebase my pull request and possibly refactor. |
This is support for pluggable device using experimental TensorFlow feature.
Motivated by the desire to use the M1 Chip GPU cores.
Thanks to gists of @lnshi, @wangjia184 and my own trial and error.