Fix: Set dtype to 'float32' in sf.read to prevent PyTorch type mismatch#1
Fix: Set dtype to 'float32' in sf.read to prevent PyTorch type mismatch#1Miyoko076 wants to merge 1 commit intojhj0517:mainfrom
Conversation
Summary of ChangesHello, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request addresses a critical compatibility issue arising from the default data type returned by Highlights
🧠 New Feature in Public Preview: You can now enable Memory to help Gemini Code Assist learn from your team's feedback. This makes future code reviews more consistent and personalized to your project's style. Click here to enable Memory in your admin console. Changelog
Activity
Using Gemini Code AssistThe full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips. Invoking Gemini You can request assistance from Gemini at any point by creating a comment using either
Customization To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a Limitations & Feedback Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments. If you're interested in giving your feedback about your experience with Gemini Code Assist for Github and other Google products, sign up here. You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension. Footnotes
|
![gemini-code-assist[bot]](https://avatars.githubusercontent.com/in/956858?s=60&v=4){kind=small}
There was a problem hiding this comment.
Code Review
This pull request addresses a RuntimeError in PyTorch-based pipelines by ensuring that soundfile.read returns audio data with float32 dtype, which is consistent with other audio reading libraries used in the function. The change is correct and well-justified. My main feedback is to add a unit test to verify this fix and prevent future regressions, as the corresponding test file is currently empty.
| if signal is None: | ||
| try: | ||
| signal, sampling_rate = sf.read(path) | ||
| signal, sampling_rate = sf.read(path, dtype='float32') |
There was a problem hiding this comment.
This change correctly addresses the data type mismatch. To ensure this fix is robust and to prevent future regressions, it would be beneficial to add a unit test. The test file tests/utils/test_fastio.py is currently empty. A test case could be added there to specifically verify that when soundfile.read is used as a fallback, the resulting audio data has the float32 dtype.
1 participant
Description
This PR explicitly sets
dtype='float32'when falling back tosoundfile.read()inutils/fastio.py.Why is this needed?
By default,
soundfile.read()returns afloat64(Double) array. Whenultimatevocalremover_apiis used as a dependency in PyTorch-based pipelines (like Whisper-WebUI), this default behavior causes a crash (RuntimeError: expected scalar type Double but found Float) during downstream operations such as audio resampling.Explicitly requesting
float32fromsoundfilefixes this crash and avoids unnecessary memory overhead from allocating a Double array.Related Issue
RuntimeError: expected scalar type Double but found Floatduring BGM Separation (caused byultimatevocalremover_api) Whisper-WebUI#634