Okay, so I’ve been messing around with this thing called “TRT ViT,” which I guess stands for TensorRT Vision Transformer. Basically, it’s supposed to make those fancy AI image models run way faster. I wanted to see if it was all hype or if it actually worked.
Getting Started
First things first, I had to get all the software stuff set up. You need, like, a specific version of Python, and obviously, TensorRT itself. The install process was a bit of a pain, I’ll be honest. I had some issues getting all the dependencies right. It’s not exactly a “one-click” install, you know?
The Actual Experiment
- I grabbed a pre-trained ViT model. One of those ones that’s already learned to recognize a bunch of objects in pictures.
- Then, I used the TRT tools to “convert” it. This is where the magic is supposed to happen. It optimizes the model to run super-fast on my GPU.
- I ran some tests. Threw a bunch of images at both the original model and the TRT-optimized one.
Result
I compared the speed, how many images each one could process per *, boom! The TRT version was noticeably faster. I mean, it wasn’t, like, a thousand times faster, but definitely a solid improvement. I was pretty stoked! I can see how this would be a big deal if you were doing, like, real-time video processing or something.
So, yeah, that’s my little adventure with TRT ViT. Definitely something to check out if you’re into this AI image stuff and need to speed things up.
