Comments (3)
bcm-at-zama
commented on July 29, 2024
Was an issue @c-gamble had when working on S6 Concrete ML bounty, zama-ai/bounty-program#127 (comment)
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jfrery
commented on July 29, 2024
Hi @c-gamble,
Do you use brevitas by any chance? If so, make sure you start the model by a QuantIdentity as in https://github.com/zama-ai/concrete-ml/blob/main/docs/advanced_examples/QuantizationAwareTraining.ipynb.
If that's not it, I will probably need more info about your implementation. We can dm on discord if needed.
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RomanBredehoft
commented on July 29, 2024
You could also check out the answer to the following issue as you seem to face the same kind of problem : #729
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Related Issues (20)
- RuntimeError: Can't compile: Cannot find crypto parameters HOT 1
- Can not install concrete-ml on Linux system HOT 7
- ValueError: Please either set all three 'ordered_module_input_names', 'ordered_module_output_names' and 'quant_layers_dict' or none of them. HOT 4
- Feature Request: Add support for embedding layers HOT 4
- [Question] How exactly the HybridFHE functions HOT 1
- [Question] FHE inference over a single image time HOT 2
- installation error HOT 7
- [Question] Discord link in explanation HOT 2
- High accuracy variance during the training with SGDClassifier HOT 1
- Feature Request : Implement LogSoftmax, Softmax, ReduceMax HOT 3
- Performance Issues HOT 1
- Two consecutive Unsqueeze operations in QAT model throws error at compilation time HOT 2
- LLVM symbolizer error with LogisticRegression example HOT 15
- [Question] What HE algorithm is used? HOT 6
- [Question] AssertionError: Values must be float if value_is_float is set to True, got int64: [1] HOT 3
- RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! HOT 7
- Python 3.12 HOT 1
- Adding encrypted training for other ML models and DL models HOT 5
- quantized_module.forward() occured an error in "execute" mode HOT 8
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