TensorFlow GPU

TensorFlow GPU#

This chapter is about installing TensorFlow with and without CUDA packages as well as TensorRT.

Important

TensorFlow 2.10 was the last TensorFlow release that supported GPU on native-Windows. Starting with TensorFlow 2.11, you will need to install TensorFlow in WSL2.

Installation on Windows via WSL2#

Installing TensorFlow within WSL2 is an efficient approach as it allows you to leverage the performance benefits of the Linux kernel while working in a Windows environment. The setup process includes installing a Linux distribution on Windows using WSL2, configuring a Python environment, preferably using Anaconda, and then installing TensorFlow into this environment.

graph TB; classDef green fill:#9f6,stroke:#333,stroke-width:2px; subgraph "Windows_host" subgraph "WSL2_guest" A[Anaconda] end end class WSL2_guest green

Warning

Installing TensorFlow with GPU support can be a nightmare - expect challenges.

If the installation didn’t work, starting a trial-and-error process can exacerbate the problems and mess everything up.

I highly recommend you carefully consider whether you choose option 1 or option 2. I recommend you favor Option 2 and only choose Option 1 if it is absolutely necessary and you are sure you can handle it. Option 1 is much more complex in terms of installation and maintenance.

see also, CUDA Installation


Install options#

graph TB; classDef red fill:#f96,stroke:#AAA,stroke-width:0.5px; classDef green fill:#90EE90,stroke:#AAA,stroke-width:0.5px; subgraph " Host " A[Host: Windows] A --> B[NVIDIA Driver]; end subgraph "Option 1 " B --> C[Guest: WSL2]; C --> D[CUDA Toolkit + cuDNN Libraries]; D --> E["TensorFlow package"]; end subgraph "Option 2 " B --> F[Guest: WSL2]; F --> G["TensorFlow[and-cuda] package"]; end class B,D red; class A,C,F green;

Software Installation Dependency Chart#

graph LR A[TensorFlow] -->|Option 1| B[Setuptools] C["TensorFlow[and Cuda]"] -->|Option 2| B subgraph TensorFlowRT B --> D[Nvidia-pyindex] D --> E[Nvidia-TensorRT] end


Table of content#

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