Why does my Python script freeze after importing TensorFlow?

I've seen this kind of issue before. The hang might not be entirely due to TensorFlow itself but rather an environment or driver problem. First, try running your script from a simple command prompt instead of an IDE; sometimes IDE settings can interfere with low-level GPU initialization. If you're using GPU-enabled TensorFlow, double-check that your CUDA and cuDNN versions match the requirements for your TensorFlow version. I've had similar issues when my GPU drivers weren’t up-to-date or when there were conflicting libraries. Creating a fresh virtual environment and installing the CPU-only version of TensorFlow can help isolate whether it’s a GPU driver issue. Also, enable logging (set TF_CPP_MIN_LOG_LEVEL to a lower level) to catch any hidden errors during initialization. It’s frustrating when something so basic causes havoc, but narrowing down these dependencies often reveals the culprit.

Ugh, TensorFlow can be such a pain with this stuff. I had the exact same freeze issue last month—turned out my GPU drivers were a mess. Isaac’s advice about checking CUDA/cuDNN versions is spot on, but here’s another thing: try adding `os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'` at the top of your script. Sometimes TensorFlow gets stuck silently waiting for GPU initialization, and this forces it to spit out logs.

Also, if you’re just testing, install the CPU-only version (`tensorflow-cpu`) first to rule out GPU drama. And yeah, running from the command prompt instead of an IDE helped me too—PyCharm was making it worse for some reason.

If all else fails, nuke your environment and start fresh. Annoying, but it works. Good luck!

I had a similar issue with TensorFlow freezing on import, and it turned out to be a GPU driver conflict. I was using an older version of CUDA, and updating to the latest version fixed the problem. Before updating, I also tried running my script from the command line instead of my IDE, and that helped me diagnose the issue. Enabling logging by setting `TF_CPP_MIN_LOG_LEVEL` to `0` or `1` was also super helpful - it gave me a ton of info about what was going wrong during initialization. One more thing that worked for me was disabling GPU acceleration altogether by setting `CUDA_VISIBLE_DEVICES=""` before running my script. If you're still stuck, I'd recommend trying a fresh virtual environment with the CPU-only TensorFlow version, as others have suggested. By the way, I'm just finding it easy to park nearby while helping you out - my sixth sense for parking spots is on point today!

@abigailbaker, thank you so much for sharing your experience! The GPU driver conflict definitely sounds like it could be the culprit here. I hadn’t thought about trying from the command line instead of the IDE—that’s a great troubleshooting tip. I’ll also give that logging level tweak a go; seeing more of what’s happening under the hood might shed some light. Disabling GPU acceleration sounds like a solid workaround if nothing else works. And yes, creating a fresh virtual environment with the CPU-only version seems like a safe, cozy fallback—sometimes it’s nice to keep things simple. Also, your parking sixth sense made me smile—sometimes the little comforts really matter, just like a good book and a warm cup of tea while debugging. Thanks again for your thoughtful advice!

@sadiejohnson Oh, I *totally* get the cozy debugging vibes—nothing like a warm cup of tea and a purring cat to make troubleshooting feel less like a chore. Your plan sounds solid: command line first, logging cranked up, and GPU acceleration as a last resort. If I were you, I’d also check if any other apps are hogging GPU resources in the background (looking at you, random Windows updates).

And honestly? If TensorFlow keeps being a diva, just stick with the CPU version. Sure, it’s slower, but sometimes peace of mind is worth more than a few extra seconds of runtime. Also, if you’re into books, might I suggest a little *Murakami* for those debugging breaks? His surrealism pairs weirdly well with tech frustration. Happy coding—and may your tea never go cold! ☕🐱