tensorflow-gpu —Current release with GPU support There are a few options to install TensorFlow on your machine:
- Use pip in virtual environment (recommended).
- Use pip in your system environment.
- Configure a docker container.
- Use pip in Anaconda.
- Install tensorflow from source.
Here i will discuss the first option:
1.) Use pip in virtual environment The Virtualenv tool creates virtual Python environments that are isolated from other Python development on the same machine. In this scenario, you install TensorFlow and its dependencies within a virtual environment that is available when activated. Virtualenv provides a reliable way to install and run TensorFlow while avoiding conflicts with the rest of the system.
1. Install Python, pip, and virtualenv. On Ubuntu, Python is automatically installed and pip is usually installed. Confirm the python and pip versions:
$ python -V # or: python3 -V
$ pip -V # or: pip3 -V
To install these packages on Ubuntu:
$ sudo apt-get install python-pip python-dev python-virtualenv # for Python 2.7
$ sudo apt-get install python3-pip python3-dev python-virtualenv # for Python 3.n
We recommend using pip version 8.1 or higher. If using a release before version 8.1, upgrade pip:
$ sudo pip install -U pip
If not using Ubuntu and setuptools is installed, use easy_install to install pip:
$ easy_install -U pip
2. Create a directory for the virtual environment and choose a Python interpreter.
$ mkdir ~/tensorflo # somewhere to work out of
$ cd ~/tensorflow
$ virtualenv –system-site-packages venv # Use python default (Python 2.7)
$ virtualenv –system-site-packages -p python3 venv # Use Python 3.n
3. Activate the Virtualenv environment.
Use one of these shell-specific commands to activate the virtual environment:
$ source ~/tensorflow/venv/bin/activate
$ source ~/tensorflow/venv/bin/activate.csh
$ . ~/tensorflow/venv/bin/activate.fish
4. Upgrade pip in the virtual environment.
Within the active virtual environment, upgrade pip:
(venv)$ pip install -U pip
You can install other Python packages within the virtual environment without affecting packages outside the virtualenv.
5. Install TensorFlow in the virtual environment.
Choose one of the available TensorFlow packages for installation:
- tensorflow —Current release for CPU
- tensorflow-gpu —Current release with GPU support
- tf-nightly —Nightly build for CPU
- tf-nightly-gpu —Nightly build with GPU support
Within an active Virtualenv environment, use pip to install the package:
$ pip install -U tensorflow
Success: TensorFlow is now installed.