Install TensorFlow with pip
TensorFlow 2 packages are available
tensorflow —Latest stable release with CPU and GPU support (Ubuntu and Windows)
tf-nightly —Preview build (unstable) . Ubuntu and Windows include GPU support .
Older versions of TensorFlow
For TensorFlow 1.x, CPU and GPU packages are separate:
tensorflow==1.15 —Release for CPU-only
tensorflow-gpu==1.15 —Release with GPU support (Ubuntu and Windows)
System requirements
Python 3.6–3.8
Python 3.8 support requires TensorFlow 2.2 or later.
pip 19.0 or later (requires manylinux2010 support)
Ubuntu 16.04 or later (64-bit)
macOS 10.12.6 (Sierra) or later (64-bit) (no GPU support)
macOS requires pip 20.3 or later
Windows 7 or later (64-bit)
Raspbian 9.0 or later
GPU support requires a CUDA®-enabled card (Ubuntu and Windows)
Note: Installing TensorFlow 2 requires a newer version of pip .
Hardware requirements
Starting with TensorFlow 1.6, binaries use AVX instructions which may not run on older CPUs.
Read the GPU support guide to set up a CUDA®-enabled GPU card on Ubuntu or Windows.
1. Install the Python development environment on your system
Check if your Python environment is already configured:
Requires Python 3.6–3.8, pip and venv >= 19.0
$ python3 --version
$ pip3 --version
If these packages are already installed, skip to the next step.
Otherwise, install Python , the pip package manager , and venv :
$ sudo apt update
$ sudo apt install python3-dev python3-pip python3-venv
Caution: Upgrading the system pip can cause problems .
If not in a virtual environment, use python3 -m pip for the commands below. This ensures that you upgrade and use the Python pip instead of the system pip .
2. Create a virtual environment (recommended)
Python virtual environments are used to isolate package installation from the system.
Create a new virtual environment by choosing a Python interpreter and making a ./venv directory to hold it:
$ python3 -m venv --system-site-packages ./venv
Activate the virtual environment using a shell-specific command:
$ source ./venv/bin/activate # sh, bash, or zsh
When the virtual environment is active, your shell prompt is prefixed with (venv) .
Install packages within a virtual environment without affecting the host system setup. Start by upgrading pip :
$ pip install --upgrade pip
$ pip list # show packages installed within the virtual environment
And to exit the virtual environment later:
3. Install the TensorFlow pip package
Choose one of the following TensorFlow packages to install from PyPI :
tensorflow —Latest stable release with CPU and GPU support (Ubuntu and Windows) .
tf-nightly —Preview build (unstable) . Ubuntu and Windows include GPU support .
tensorflow==1.15 —The final version of TensorFlow 1.x.
Package dependencies are automatically installed. These are listed in the setup.py file under REQUIRED_PACKAGES .
Virtual environment install
$ pip install --upgrade tensorflow
System Install
$ pip3 install --user --upgrade tensorflow # install in $HOME
Verify the install:
Venv $ python -c "import tensorflow as tf;print(tf.reduce_sum(tf.random.normal([1000, 1000])))"
System install
$ python3 -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([1000, 1000])))"
Success: If a tensor is returned, you've installed TensorFlow successfully. Read the tutorials to get started.
Package location
A few installation mechanisms require the URL of the TensorFlow Python package. The value you specify depends on your Python version.
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