Coder Social home page Coder Social logo

riejohnson / context Goto Github PK

View Code? Open in Web Editor NEW
124.0 10.0 14.0 39.24 MB

ConText v4: Neural networks for text categorization

Home Page: http://riejohnson.com/cnn_download.html

License: GNU General Public License v3.0

C++ 85.25% Cuda 14.14% C 0.13% Makefile 0.25% Roff 0.24%
text-categorization text-classification neural-network gpu convolutional-neural-networks lstm deep-learning dpcnn sentiment-classification sentiment-analysis

context's People

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  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  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  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  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

context's Issues

No support for n-gram sequential

I get the following error after generating the vocabulary with n=3 and then generating regions. If I leave n to the default value of 1, then this error doesn't show, but does that mean trigrams aren't supported? Is this an architecture-specific error?

!Input error!: (Detected in AzPrepText::gen_regions)NO SUPPORT for n-gram sequential

DPCNN: weight sharing of convolution units

Thank you very much for releasing the code.

I'm having a hard time reading https://github.com/riejohnson/ConText/blob/master/examples/dpcnn-functions.sh are the weight of the convolution units intended to be shared across the different layers ?

There's no hint about this in the paper so I think it should not be shared, but this random independent implementation: https://github.com/Cheneng/DPCNN/blob/master/model/DPCNN.py made it so (but I found a few other errors within this repo).

make not working

I have an NVIDIA GeForce 940MX GPU on my machine and also have gcc fully functional, as well as CUDA 9.1 installed. I've followed the README instructions and added the custom CUDA path to the makefile but I'm getting the following error on running make

/bin/rm -f bin/reNet
/usr/local/cuda-9.1  /bin/nvcc src/com/AzDmat.cpp src/com/AzParam.cpp src/com/AzSmat.cpp src/com/AzStrPool.cpp src/com/AzTextMat.cpp src/com/AzTools.cpp src/com/AzUtil.cpp src/nnet/AzpPatchDflt.cpp src/nnet/AzpReNet.cpp src/nnet/AzpReLayer.cpp src/nnet/AzMultiConn.cpp src/nnet/AzpMain_reNet.cpp src/nnet/AzpLmSgd.cpp src/nnet/AzPmat.cpp src/nnet/AzPmatSpa.cpp src/nnet/AzPmatApp.cpp src/nnet/AzPmat_gpu.cu src/nnet/AzPmatSpa_gpu.cu src/nnet/AzCuda_Pmat.cu src/nnet/AzCuda_PmatSpa.cu src/nnet/AzCuda_PmatApp.cu src/nnet/AzpEv.cpp src/nnet/AzpLossDflt.cpp src/nnet/driv_reNet.cpp -Isrc/com -Isrc/data -Isrc/nnet  -D__AZ_SMAT_SINGLE__ -D__AZ_GPU__  -I/usr/local/cuda-9.1  /include -O2 -gencode arch=compute_20,code=sm_20 -gencode arch=compute_20,code=sm_21 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_32,code=sm_32 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_53,code=sm_53 -o bin/reNet -L/usr/local/cuda-9.1  /lib64 -lcudart -lcublas -lcurand -lcusparse
make: execvp: /usr/local/cuda-9.1: Permission denied
makefile:84: recipe for target 'bin/reNet' failed
make: *** [bin/reNet] Error 127

Recommend Projects

  • React photo React

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

  • Vue.js photo Vue.js

    ๐Ÿ–– 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. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

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 โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.