Install packages within a virtual environment without affecting the host system When the virtual environment is active, your shell prompt is prefixed with (venv). venvĪctivate the virtual environment using a shell-specific command: Python virtual environments are used to isolate package installation from the system.Ĭreate a new virtual environment by choosing a Python interpreter and making a Create a virtual environment (recommended)

This ensures that you upgrade and use theĢ. If not in a virtual environment, use python3 -m pip for Other curl -o get-pip.py python get-pip.py Caution: Upgrading the system pip can cause Install the 64-bit Python 3 release for Windows (select pip as an optional feature). Make sure long paths are enabled on Windows.

Download and install the Microsoft Visual C++ Redistributable for Visual Studio 2015, 20 for your platform.

Scroll down the page to the Visual Studio 2015, 20 section.

Go to the Microsoft Visual C++ downloads,.

The redistributable comes with Visual Studio 2019 but can be installed separately: Starting with the TensorFlow 2.1.0 version, the msvcp140_1.dllįile is required from this package (which may not be provided from older redistributable packages). Install the Microsoft Visual C++ Redistributable for Visual Studio 2015, 2017,Īnd 2019. Install using the Homebrew package manager: /usr/bin/ruby -e '$(curl -fsSL )' export PATH='/usr/local/opt/python/libexec/bin:$PATH' # if you are on macOS 10.12 (Sierra) use `export PATH='/usr/local/bin:/usr/local/sbin:$PATH'` brew update brew install python # Python 3 Windows Ubuntu sudo apt update sudo apt install python3-dev python3-pip python3-venv macOS If these packages are already installed, skip to the next step. Requires Python 3.7–3.9, and pip >= 19.0 python3 -version pip3 -version Install the Python development environment on your systemĬheck if your Python environment is already configured:

Read the GPU support guide to set up a CUDA®-enabled GPU card on Ubuntu or Windows.ġ.

Starting with TensorFlow 1.6, binaries use AVX instructions which may not run on older CPUs.

Note: Installing TensorFlow 2 requires a newer version of pip.

GPU support requires a CUDA®-enabled card (Ubuntu and Windows).

Redistributable for Visual Studio 2015, 20

macOS 10.12.6 (Sierra) or later (64-bit) (no GPU support).

pip 19.0 or later (requires manylinux2010 support).

Python 3.8 support requires TensorFlow 2.2 or later.

Python 3.9 support requires TensorFlow 2.5 or later.

tensorflow-gpu=1.15 -Release with GPU support (Ubuntu and Windows).

Ubuntu and Windows include GPU support.įor TensorFlow 1.x, CPU and GPU packages are separate:

tensorflow -Latest stable release with CPU and GPU support (Ubuntu and Windows).

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