Comments (9)
Hello,
Great to know that you are trying out Concrete-ML !
It's a bit hard to know what could be the issue here, the notebook works fine on our side. Could you give us more information on the configuration you're using (for example, by running the top
command) ?
Also, what Concrete-Numpy and Concrete-Compiler are you currently using ? You can run pip show concrete-numpy
and pip show concrete-compiler
.
Thanks !
from concrete-ml.
$pip show concrete-compiler
Name: concrete-compiler
Version: 0.23.4
Summary: Concrete Compiler
Home-page: https://github.com/zama-ai/concrete-compiler
Author: Zama Team
Author-email: [email protected]
License: BSD-3
Location: /home/mahmoud/anaconda3/envs/fhe/lib/python3.9/site-packages
Requires: numpy, PyYAML, setuptools
Required-by: concrete-numpy
(fhe) ~$pip show concrete-numpy
Name: concrete-numpy
Version: 0.9.0
Summary: Concrete Numpy is an open-source library which simplifies the use of fully homomorphic encryption (FHE).
Home-page: https://zama.ai/concrete/
Author: Zama
Author-email: [email protected]
License: BSD-3-Clause
Location: /home/mahmoud/anaconda3/envs/fhe/lib/python3.9/site-packages
Requires: concrete-compiler, matplotlib, networkx, numpy, Pillow, torch
Required-by: concrete-ml
from concrete-ml.
Thanks ! These dependencies look good. Maybe you can give us more information on the configuration you're using then (for example, by running top
?
from concrete-ml.
I have 10GB ram
Intel(R) Core(TM) i7 CPU 920 @ 2.67GHz
from concrete-ml.
Could you now try to put the following code in a .py file and then run it (using the same environment you're using) :
from sklearn.model_selection import train_test_split
from sklearn.datasets import make_regression
from concrete.ml.sklearn import LinearRegression
X, y = make_regression(
n_samples=200, n_features=8, n_targets=1, bias=5.0, noise=30.0, random_state=42
)
x_train, x_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=42)
concrete_model = LinearRegression()
concrete_model.fit(x_train, y_train)
circuit = concrete_model.compile(x_train)
circuit.keygen()
y_pred = concrete_model.predict(x_test, execute_in_fhe=True)
Do you encounter the same issue ? If so, could you give me the error/crash's complete traceback ? Thanks !
from concrete-ml.
shell Stack dump without symbol names (ensure you have llvm-symbolizer in your PATH or set the environment var
LLVM_SYMBOLIZER_PATHto point to it): /home/mahmoud/anaconda3/envs/fhe/lib/python3.9/site-packages/mlir/_mlir_libs/libConcretelangBindingsPythonCAPI.so(+0x10c2821)[0x7f3714bc3821] /home/mahmoud/anaconda3/envs/fhe/lib/python3.9/site-packages/mlir/_mlir_libs/libConcretelangBindingsPythonCAPI.so(+0x10c0024)[0x7f3714bc1024] /lib/x86_64-linux-gnu/libpthread.so.0(+0x14420)[0x7f379e5f0420] /home/mahmoud/anaconda3/envs/fhe/lib/python3.9/site-packages/mlir/_mlir_libs/../../concrete_compiler.libs/libConcretelangRuntime-aaaa6abd.so(+0x23eab9)[0x7f3799dc1ab9] /home/mahmoud/anaconda3/envs/fhe/lib/python3.9/site-packages/mlir/_mlir_libs/../../concrete_compiler.libs/libConcretelangRuntime-aaaa6abd.so(new_default_engine+0x148)[0x7f3799e1f6e8] /home/mahmoud/anaconda3/envs/fhe/lib/python3.9/site-packages/mlir/_mlir_libs/libConcretelangBindingsPythonCAPI.so(_ZN12concretelang9clientlib6KeySet8generateERNS0_16ClientParametersEmm+0x208)[0x7f3718877b98] /home/mahmoud/anaconda3/envs/fhe/lib/python3.9/site-packages/mlir/_mlir_libs/libConcretelangBindingsPythonCAPI.so(_ZN12concretelang9clientlib11KeySetCache8generateESt10shared_ptrIS1_ERNS0_16ClientParametersEmm+0x2e)[0x7f371888605e] /home/mahmoud/anaconda3/envs/fhe/lib/python3.9/site-packages/mlir/_mlir_libs/libConcretelangBindingsPythonCAPI.so(+0xebd13c)[0x7f37149be13c] /home/mahmoud/anaconda3/envs/fhe/lib/python3.9/site-packages/mlir/_mlir_libs/libConcretelangBindingsPythonCAPI.so(_Z7key_setN12concretelang9clientlib16ClientParametersEN4llvm8OptionalINS0_11KeySetCacheEEE+0x50)[0x7f37149d1790] /home/mahmoud/anaconda3/envs/fhe/lib/python3.9/site-packages/mlir/_mlir_libs/_concretelang.cpython-39-x86_64-linux-gnu.so(+0x2feed)[0x7f379a185eed] /home/mahmoud/anaconda3/envs/fhe/lib/python3.9/site-packages/mlir/_mlir_libs/_concretelang.cpython-39-x86_64-linux-gnu.so(+0x1ca12)[0x7f379a172a12] python[0x507507] python(_PyObject_MakeTpCall+0x2ec)[0x4f049c] python(_PyEval_EvalFrameDefault+0x52ab)[0x4ec99b] python[0x4e67ea] python(_PyFunction_Vectorcall+0xd5)[0x4f7be5] python(_PyEval_EvalFrameDefault+0x4d74)[0x4ec464] python[0x4e67ea] python(_PyFunction_Vectorcall+0xd5)[0x4f7be5] python(_PyEval_EvalFrameDefault+0x689)[0x4e7d79] python[0x4e67ea] python(_PyFunction_Vectorcall+0xd5)[0x4f7be5] python(_PyEval_EvalFrameDefault+0x689)[0x4e7d79] python[0x4e67ea] python(_PyEval_EvalCodeWithName+0x47)[0x4e6477] python(PyEval_EvalCodeEx+0x39)[0x4e6429] python(PyEval_EvalCode+0x1b)[0x593ccb] python[0x5c1077] python[0x5bd080] python[0x4564f6] python(PyRun_SimpleFileExFlags+0x1a2)[0x5b6d62] python(Py_RunMain+0x37e)[0x5b42de] python(Py_BytesMain+0x39)[0x587d79] /lib/x86_64-linux-gnu/libc.so.6(__libc_start_main+0xf3)[0x7f379e2b4083] python[0x587c2e] PLEASE submit a bug report to https://github.com/llvm/llvm-project/issues/ and include the crash backtrace. Instruction non permise (core dumped)
from concrete-ml.
Thanks a lot, we are currently investigating the issue !
from concrete-ml.
The issue seems to come from the fact that we rely on aes instructions during keygen, and that your CPU doesn't support that (You can see that in "Security & Reliability). Newer CPUs (starting from 2010 I guess) should support that.
We are currently thinking of checking the availability of such instructions at runtime, and fallback to a software variant if not available. We could potentially support older versions in that case, but for the time being, the fastest solution is to use a CPU that supports aes instructions.
from concrete-ml.
Thank you for instructions. I will try to upgrade my CPU.
from concrete-ml.
Related Issues (20)
- Comparison over encrypted integers HOT 3
- Add a fhe or concrete-ml as a tag in HF compiled models HOT 2
- Test Hugging Face Endpoints on Azure HOT 2
- 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
- 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
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from concrete-ml.