Add sepreformer example#5472
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vfdev-5
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Jun 2, 2026
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| # Building a Choral Source Separator with SepReformer in JAX | ||
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| This tutorial demonstrates how to perform audio source separation using the `SepReformer` |
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Please put a link to SepReformer paper/project/code
| # Building a Choral Source Separator with SepReformer in JAX | ||
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| This tutorial demonstrates how to perform audio source separation using the `SepReformer` | ||
| architecture. We'll use `flax.nnx` for the neural network, with `beartype` for runtime type checking. |
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If you are using any 3rd party packages, please put a line on how to install them.
| def __len__(self) -> int: | ||
| return len(self.songs) | ||
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| dataset = JaCappellaDataset("/space/samanklesaria/data/jacappella") |
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Maybe, we can use some temporary folder instead of your specific folder, e.g. /tmp/data/jacappella?
| if epoch % 20 == 0: | ||
| log_audio_samples(model, loader, writer, epoch) | ||
| writer.close() | ||
| ``` |
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Make a conclusion section to recap the tutorial, otherwise it ends a bit weirdly
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This PR adds a guide showing how to use NNX for an audio task (source separation). Examples of the audio files are embedded in the notebook, as myst-nb makes it difficult to copy static files to the html build dir.