Slow training
Open
- Dominant language
- Python
- Stars
- 584
- Forks
- 108
- PR merge metrics
- No merged PRs in 30d
Description
Hi everyone
Is it expected behavior that the quantization-aware training in QKeras is much slower than normal training in Keras? And if so, out of interest, where does the overhead come from? From the quantization-dequantization operation?
Thank you for your help!
Contributor guide
Research direction
The issue names no files, tests, or entry points. Compare QKeras quantization-aware training with normal Keras training, profile the quantization and dequantization operations, and document whether the slowdown is expected and where the overhead comes from.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, tensorflow
- Domain
- machine-learning, performance
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100