tensorflow / tensorflow/model-optimization
Is there a way to do symmetric quantization for activations in post-training quantization
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Description
https://tensorflow.google.cn/lite/performance/quantization_spec
from this document we can see the post-training quantization do asymmetric quantization for activations, do symmetric quantization for wieghts.
I follow this guide: https://tensorflow.google.cn/lite/performance/post_training_integer_quant do full int8 quantization for my network mode is OK, as the above said the weights is symmetric , the feature is asymmetric.
My question is I also want the activations also is symmetric, How to do that?
thanks!
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First steps
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Research direction
Start by reading the linked post-training quantization guide and quantization specification, then inspect the model-optimization quantization entry points for activation configuration. The issue does not name files or tests; completion would require establishing whether symmetric activation quantization is supported and documenting or implementing a defined path for it.
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Assessment
- Tech stack
- python, tensorflow
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100