Git Product home page Git Product logo

she's People

Contributors

privacylq avatar qianlou avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar

she's Issues

Getting build errors

$ make shiftNet

g++ --std=c++11 -fopenmp -c alu.cpp -ltfhe-spqlios-fma -ltfhe-spqlios-avx -I/home/jay/tfhe/src/include/
alu.cpp: In function ‘void bootsCOPYPointer(LweSample*, LweSample*)’:
alu.cpp:344:16: error: use of deleted function ‘LweSample& LweSample::operator=(const LweSample&)’
      *result= *a;
                ^
In file included from /home/jay/tfhe/src/include/lwe-functions.h:10:0,
                 from /home/jay/tfhe/src/include/tfhe.h:14,
                 from alu.hpp:9,
                 from alu.cpp:1:
/home/jay/tfhe/src/include/lwesamples.h:18:15: note: declared here
    LweSample& operator=(const LweSample&)=delete;
               ^~~~~~~~
Makefile:19: recipe for target 'alu.o' failed
make: *** [alu.o] Error 1

Regarding the source code

I just find the shiftDotProduction, ReLU, and max pooling operations code, but where is the source code of NN models of MNIST,CIFAR-10 ?

Segmentation fault

When I clone the repository and follow the execution instructions, the program runs correctly.

However, whenever I try to execute the program after making some changes in SHE.cpp file and following the execution instruction again, the program terminates abruptly by giving a segmentation fault.

For example, I get the following output when running the program after some changes:

######## 1. shiftDot(A[0:input_size-1], Be[0:input_size-1]) Verification#######
A=[ 0 1 2 3 4 5 6 7]
Be=[ 1 1 1 1 1 1 1 1]
Segmentation fault (core dumped)

I could not understand why this is happening. Can someone point me in the right direction?

Query on negative weight

Hi,

From SHE paper, the dot product is mentioned as summation(input_i×2^WeightQi).
It seems the weight is assumed to be always positive.

How do you handle weights which are negative (e.g. -0.25 = -(2^-2))?

Thanks.

regarding leveled TFHE

I cannot find code regard of leveled TFHE that mentioned in your paper.
It seems like your code used bootstrapping gates such as bootsAND.
Moreover, it seems like TFHE library does not support Leveled TFHE.
Thus, would you give any information of LTFHE?
Thanks.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo 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.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.