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It seems that running the code in 2023 is extremely difficult because the versions of numpy, librosa, and numba create those well-known dependency hells that one runs into with pip.
This is no complain about the code itself, which is wonderful and well-written. Thank you so much for it and the instructions to run it.
In case it is helpful to anyone, I managed to find a winning combination of packages using conda. I leave the environment.yml here, which might be useful to make this code future-proof (hopefully), as all of these libraries will continue to update in the future.
Here it is. What you need to do, instead of the regular pip install -r requirements.txt is the following:
Hi @napulen, thank you for digging into this issue. The proposed fix makes sense to me.
We'll keep this issue open for posterity. I'm not actively maintaining this repository any more, but perhaps we can also add this to the README with updated instructions; I will take care of this once I have more bandwidth.
Hello,
It seems that running the code in 2023 is extremely difficult because the versions of
numpy
,librosa
, andnumba
create those well-known dependency hells that one runs into with pip.This is no complain about the code itself, which is wonderful and well-written. Thank you so much for it and the instructions to run it.
In case it is helpful to anyone, I managed to find a winning combination of packages using conda. I leave the
environment.yml
here, which might be useful to make this code future-proof (hopefully), as all of these libraries will continue to update in the future.Here it is. What you need to do, instead of the regular
pip install -r requirements.txt
is the following:And the contents of
environment.yml
are these:The text was updated successfully, but these errors were encountered: