SD3 dreambooth training - caching of embeddings and vae representations

**Is your feature request related to a problem? Please describe.**
The current implementation of the dreambooth trainings for both loras and finetuning is very memory intensive.

**Describe the solution you'd like.**
I would like the option to pre-cache the VAE representations of the images and the text encoder representations so that training could be done without the text encoders being in VRAM.

**Describe alternatives you've considered.**
I don't believe there are alternatives to reducing the VRAM requirement for training.

Start by locating the SD3 DreamBooth training entry points and how they currently encode images and text during training. The requested result is optional pre-caching of VAE and text-encoder representations so training can run without the text encoders in VRAM; the issue names no specific files or tests.

索引モデルが issue の本文から書いたものです。