Update pip.md

[sgkouzias]

Specify additional steps to utilize GPU for Linux users

[8bitmp3]

@MarkDaoust @markmcd

[sgkouzias]

Added steps and respective instructions to install TensorFlow by running the pip install tensorflow[and-cuda] command within a virtual environment (option #1: conda, option #2: venv) and set environment variables to find/locate compatible NVIDIA libs installed with TensorFlow to effectively utilize GPUs. The solution has been successfully tested.

Reference: tensorflow/tensorflow#63362

[sgkouzias]

@haifeng-jin , @MarkDaoust, @8bitmp3 I await any suggestions or revisions if needed. Do we have any updates?

[haifeng-jin]

As I remembered, the current recommended way to install TF is to use pip. I do not have further info on this. @MarkDaoust may comment on this.

[sgkouzias]

As I remembered, the current recommended way to install TF is to use pip. I do not have further info on this. @MarkDaoust may comment on this.

@haifeng-jin it seems practically impossible for someone owning a PC with CUDA-enabled GPU to perform deep learning experiments with TensorFlow version 2.16.1 and utilize his GPU locally without manually performing some extra steps not included (until today) in the official TensorFlow documentation of the standard installation procedure of TensorFlow for Linux users with GPUs at least as a temporal fix!

It turns out that when you pip install tensorflow[and-cuda] all required NVIDIA libraries are installed as well. You just need to configure manually the environment variables as appropriate in order to utilize them and run TensorFlow with GPU.

[mihaimaruseac]

Please don't use "add file"/"update file"/"fix file"/etc. commit messages. These are hard to reason about when looking at the history of the file/repository. Instead, please write explanatory git commit messages.

The commit message is also the title of the PR if the PR has only one commit. It is thus twice important to have commit messages that are relevant, as PRs would be easier to understand and easier to analyze in search results.

For how to write good quality git commit messages, please consult https://cbea.ms/git-commit/

[mihaimaruseac]

It turns out that when you pip install tensorflow[and-cuda] all required NVIDIA libraries are installed as well. You just need to configure manually the environment variables as appropriate in order to utilize them and run TensorFlow with GPU.

Can we instead add these to the install guide?