[models] Add VIPTR recognition model

[felixdittrich92]

🚀 The feature

Ref.: #1826

Paper: VIPTR
Implementation: https://github.com/cxfyxl/VIPTR

• PyTorch implementation
• TensorFlow implementation

Hi, 

I would like to suggest possibly introducing another state-of-the-art text recognition architecture to docTR.
[SVIPTR](https://paperswithcode.com/paper/viptr-a-vision-permutable-extractor-for-fast)
It's promising accurate results at low latency.

Notably, the SVIPTR-T (Tiny) variant delivers highly competitive accuracy on par with other lightweight models and achieves SOTA inference speeds. Meanwhile, the SVIPTR-L (Large) attains SOTA accuracy in single-encoder-type models, while maintaining a low parameter count and favorable inference speed.

Thanks for your consideration.

Inference latency should be comparable to crnn_mobilenet_v3_large and the results are hopefully comparable to parseq.
The addition is agreed.

[felixdittrich92]

If someone wants to work on this feel free to ping here. Otherwise I planned to start working on it after we have some strategy done to make docTR multilingual.