Comments (7)
pip freeze | grep concrete
concrete-compiler==0.10.0
concrete-ml==0.3.0
concrete-numpy==0.7.0
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Hello @sbzgyxzm ,
Are you on a linux machine ? If so, could you run ldd --version
and share me the output ?
Else, could you tell me which OS and architecture you are using ?
Thanks !
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Distributor ID: Ubuntu
Description: Ubuntu 18.04.6 LTS
Release: 18.04
ldd --version
ldd (GNU libc) 2.28
python :3.8.19
Hello @sbzgyxzm , Are you on a linux machine ? If so, could you run
ldd --version
and share me the output ?Else, could you tell me which OS and architecture you are using ?
Thanks !
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I try to install concrete-python manually, but it is not supported. (In vmware)
ERROR: concrete_python-2.6.0-cp38-cp38-manylinux_2_28_x86_64.whl is not a supported wheel on this platform.
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So there might be an issue with the fact that you have glibc 2.28 (we don't support any lower versions) and Ubuntu 18 (which we don't test as it starts to be a bit old). I would suggest you to try one of the following :
- use docker
- update to ubuntu 20
Tell me how it goes !
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now i install it in ubuntu20, python3.10, glibc2.31. I'm wondering if i could train an encrypted model using encrypted mnist dataset.
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Hello again @sbzgyxzm , great to know that it works on Ubuntu 20 !
If I understand your question well, you are looking at a way of doing encrypted training (meaning the data-set is encrypted) using a model for the mnist data-set, am I right ?
If so, here's the documentation section for this feature. For now, we've only given an example for training an encrypted logistic regression model so you want might to check if this could work for you. Note that we are planning on going further and add new examples in the future.
If you are only interested in encrypted inference, here's an example we have with a CNN on MNIST.
Besides, if you have any other questions, please feel free to ask them in a new issue !
Hope that helps 😉
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Related Issues (20)
- [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
- AssertionError: Values must be float if value_is_float is set to True, got int64: [[[[102 14 188 ... 85 205 46] 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 2
- Adding encrypted training for other ML models and DL models HOT 5
- quantized_module.forward() occured an error in "execute" mode HOT 8
- Feature request: Support Unfold torch operator HOT 10
- LLVM symbolizer error when running FHE in 'execute' mode HOT 7
- [Question] How does ReLU work in the new NN example HOT 6
- Feature request: support more padding method HOT 1
- Accuracy of XGBClassifier of disable mode HOT 2
- GPU acceleration in concrete-ml ? HOT 3
- Making a fast satellite image classification use case [was: Some questions about GPU acceleration] HOT 24
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