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❌ 21 New Failures

As of commit 93c6d68 with merge base bdd9c72 ():

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Note: this commit now depends on the dtype and is_cpu methods of stable::Tensor in pytorch, which have yet to be merged in. I will keep this PR in draft state until they make their way to nightly.

This PR passes all tests for forced_align on CPU except expected failures. This is because the correct handling of the expected failures requires porting the amax and item ops to the stable ABI. I will port these ops next.

Hello, is there a chance to get any features or improvements from #3787 merged? on the other side, I managed to remove the torch dependency completely from the FA api, so I guess it's doable, only the input log_probs array needs to be a torch tensor, all other arrays can be vectors or regular arrays, check https://github.com/MahmoudAshraf97/ctc-forced-aligner/blob/main/ctc_forced_aligner/forced_align_impl.cpp for reference

Hi @MahmoudAshraf97 , we're currently trying to migrate these ops to be ABI-stable, which is our current top priority. Unfortunately, we won't have the bandwidth to consider improvements like in #3787 at the moment, sorry. It's possible that we'll be able to re-consider in the future, but the near-term goal is for torchaudio to be stable while minimizing maintenance requirements.

The CI used to run fine. A recent change to the stable ABI now leads to stable::Tensor::scalar_type() being defined twice, which gives all the errors. Perhaps there's a new preferred way of importing the stable API headers?