Previously I have written about 在Ubuntu 安裝 TensorFlow 的紀錄 (Installing TensorFlow on Ubuntu). Years have passed, and even though Ubuntu is still on 16.04，TensorFlow has already made great progress. I’ve decided to write another post to show how to install TensorFlow and Caffe with Anaconda.
Firstly set integrated video card as the main GPU in the BIOS, and connect your monitor to the output port of the integrated video card so your Nvidia GPU is completely dedicated to deep learning computation.
Afterwards, download the deb files from the download page of
CUDA. Do not install at this time. We would reboot Ubuntu and
Ctrl-Alt-F1 to login via terminal.
Execute the following command to stop
sudo service lightdm stop
According to this article, this must be done when you want to use your Nvidia GPU solely for CUDA. When this is not done, we might not be able to login to the desktop after CUDA installation.
So now we would install CUDA 8.0.
sudo dpkg -i cuda-repo-<distro>_<version>_<architecture>.deb sudo apt update sudo apt install cuda-8-0
Record which version of nvidia driver is installed and add the PATH to
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/usr/lib/nvidia-384 export CUDA_HOME=/usr/local/cuda export PATH=$PATH:/usr/local/cuda/bin
/usr/lib/nvidia-384 should point to the actual version installed.
Reboot again to confirm that we could login:
Download Python 3 version of Anaconda at the Anaconda download page, and execute the installation command:
Install Anaconda onto a directory such as
And create a new environment named
conda create -n tf anaconda
source activate tf
Execute this command and
cudatoolkit would be
conda install tensorflow-gpu
Firstly install the required packages:
sudo apt install build-essential conda install atlas boost gflags glog hdf5 leveldb lmdb openblas protobuf conda install -c menpo opencv3
Download Caffe, and create the configuration file.
git clone https://github.com/BVLC/caffe cd caffe cp Makefile.config.example Makefile.config
Makefile.config, the number in
python3.6 could be
changed to the current Python version:
5c5 < # USE_CUDNN := 1 --- > USE_CUDNN := 1 21c21 < # OPENCV_VERSION := 3 --- > OPENCV_VERSION := 3 25c25 < # CUSTOM_CXX := g++ --- > CUSTOM_CXX := /usr/bin/g++-4.9 68,69c68,69 < PYTHON_INCLUDE := /usr/include/python2.7 \ < /usr/lib/python2.7/dist-packages/numpy/core/include --- > # PYTHON_INCLUDE := /usr/include/python2.7 \ > # /usr/lib/python2.7/dist-packages/numpy/core/include 72,75c72,75 < # ANACONDA_HOME := $(HOME)/anaconda < # PYTHON_INCLUDE := $(ANACONDA_HOME)/include \ < # $(ANACONDA_HOME)/include/python2.7 \ < # $(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include --- > ANACONDA_HOME := $(HOME)/anaconda3/envs/tf > PYTHON_INCLUDE := $(ANACONDA_HOME)/include \ > $(ANACONDA_HOME)/include/python3.6m \ > $(ANACONDA_HOME)/lib/python3.6/site-packages/numpy/core/include 83,84c83,84 < PYTHON_LIB := /usr/lib < # PYTHON_LIB := $(ANACONDA_HOME)/lib --- > # PYTHON_LIB := /usr/lib > PYTHON_LIB := $(ANACONDA_HOME)/lib 94c94 < INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include --- > INCLUDE_DIRS := $(PYTHON_INCLUDE)
Caffe can now be compiled:
make all make pycaffe