Finally I understood why my friend recommended Anaconda. It's so much easier to install Anaconda, which includes all the goodies that come with it, rather than installing each component on an as-needed basis (e.g. Spyder, iPython, etc.) The only reason I didn't go with Anaconda installation of tensorflow previously was that the tensorflow official documentation did not strongly recommend it. I used Anaconda to install tensorflow in my MacBookAir, and had no issues so far. So why not use it for the GPU box as well?
1. Install Anaconda (Python 3.6 at the time of this writing)
2. Create a conda environment named tensorflow to run Python 3.6:
$ conda create -n tensorflow
3. Activate the conda environment:
$ source activate tensorflow
(tensorflow) username$ # Your prompt should change
4. Install tensorflow within the conda environment:
(tensorflow) username$ pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.0.1-cp36-cp36m-linux_x86_64.whl
# This is for Python 3.6 with GPU support
I tried pip3 at the beginning and got an error. pip works without an issue. I still don't quite understand pip3 (python3) vs. pip (python2).
5. Verify that tensorflow is installed within Anaconda
(tensorflow) username$ ls /home/username/anaconda3/envs/tensorflow/bin/
activate conda deactivate
6. Install ipython and jupyter
(tensorflow) username$ conda install ipython
(tensorflow) username$ pip3 install jupyter
7. Verify that ipython and is installed within Anaconda
(tensorflow) username$ ls /home/username/anaconda3/envs/tensorflow/bin/
2to3 easy_install-3.6 pydoc python3.6-config tclsh8.5
2to3-3.6 idle3 pydoc3 python3.6m unxz
activate idle3.6 pydoc3.6 python3.6m-config wheel
conda ipython pygmentize python3-config wish8.5
c_rehash ipython3 python pyvenv xz
deactivate openssl python3 pyvenv-3.6
easy_install pip python3.6 sqlite3
Now I can use tensorflow in ipython within Anaconda!
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