![]() ![]() ( tensorflow-venv3 ) $ export TF_BINARY_URL = https : ///tensorflow/linux/gpu/tensorflow_gpu-0.12.1-cp35-cp35m-linux_x86_64.whl # Python 2 ( tensorflow-venv2 ) $ pip install - upgrade $TF_BINARY_URL For other versions, see "Installing from sources" below. First select the correct binary to install (from this page): # Ubuntu/Linux 64-bit, GPU enabled, Python 3.5 # Requires CUDA toolkit 8.0 and CuDNN v5. Now, install TensorFlow just as you would for a regular Pip installation. Install TensorFlow in the virtualenv for python 3:.$ source ~ /tensorflow-venv3/ bin / activate # If using bash ( tensorflow-venv3 ) $ # Your prompt should change ![]() If you want isolation from the global system, do not use this flag. This can be used if you have control over the global site-packages directory, and you want to depend on the packages there. If you build with virtualenv -system-site-packages ENV, your virtual environment will inherit packages from /usr/lib/python2.7/site-packages (or wherever your global site-packages directory is). $ virtualenv -system-site-packages -p python ~/tensorflow-venv $ virtualenv - system - site - packages -p python3 ~/ tensorflow-venv3 Create a Virtualenv environment in the directory for python 3 ~/tensorflow-venv3:.$ sudo apt - get install python - pip python - dev python - virtualenv With Virtualenv the installation is as follows: See here for a detailed introduction of how virtualenv works and some basic usage. The Virtualenv installation of TensorFlow will not override pre-existing version of the Python packages needed by TensorFlow. Virtualenv is a tool to keep the dependencies required by different Python projects in separate places. I already installed GPU TensorFlow from source for Python 2 (see this post), and now I would like to also install GPU TensorFlow for Python 3 on the same machine using Virtualenv. ![]()
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