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Last pushed: 5 months ago
Short Description
ubuntu16.04 cuda enabled nvida_docker with caffe tensorflow keras scikit_learn opencv
Full Description

This is a Nvidia-docker image contains Machine learning tools I used. Build on ubuntu16.04 , CUDA 8.0. It will fit any Ubuntu computers with Nvidia-driver installed.

To use

To use this docker, you must have the latest docker and nvidia-docker and driver installed, please check out this.

Installed ML packages:

  1. cuda 8.0, cudnn 5110
  2. theano
  3. caffe
  4. tensorflow_gpu
  5. opencv 3.2
  6. xgboost
  7. keras
  8. scikit-learn
  9. numpy scipy

Updating via apt and pip

If you found the updating via apt/pip is too slow, you have to reconfigure the source in

/etc/apt/sources.list  
or
~/.pip/pip.conf

Known problem

When you use caffe, you many encounter (error == cudaSuccess (8 vs. 0) invalid device function) , though theano, tensorflow, keras could use GPU with no problem. I have no idea what causes this error but rebuild caffe could help:

pip uninstall protobuf
cd ~/downloads/caffe/build
rm -rf ./*
cmake ../
make -j 4
make all
make install
pip install protobuf

to verify

cd ~/downloads/caffe/
./examples/mnist/train_lenet.sh
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Owner
stevendu

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