ExecuTorch kernels for native_batch_norm ops do not support mixing float16/bfloat16 input and float32 params
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module: kernels
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Description
🕵️♂️ Detected with FACTO
In torch, native_batch_norm ops support float16/bfloat16 input, even when params are float32. However, ExecuTorch kernels requires all dtypes to be the same. Expand the support of ExecuTorch kernels to match torch's.
cc @larryliu0820
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the ExecuTorch kernels for the native_batch_norm ops and compare their dtype handling with PyTorch's behavior. Use the FACTO-detected mixed float16/bfloat16 input with float32 parameters as the reproduction case; done means the kernels support the mixed dtypes rather than requiring every value to share one dtype.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- pytorch
- Domain
- embedded-iot, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 48/100