Comments (2)
Hi.
For the loss config, we do not train the first stage model, i.e., VQGAN, so it is fixed and the loss is set to identity. You may refer to the training process of Latent diffusion for a better understanding. In the code, you can find that this loss config does nothing during the training of the diffusion part.
For the training pipeline, you can refer to our paper for details. Your understanding is mostly correct. Only one thing: after training the diffusion part, we just generate the training data using the diffusion part. After that, the diffusion part is not involved in the training process anymore and we just use the generated data to train CFW, the same as training VQGAN.
from stablesr.
Thank you for your reply!
from stablesr.
Related Issues (20)
- SFT training problem
- SR Result is a noise image HOT 1
- About the issue of non-decreasing training loss HOT 2
- packages is strictly installed follow the procedure but still xformers install went wrong
- RuntimeError: PytorchStreamReader in demo colab StableSR_inference.ipynb HOT 1
- SD-Turbo HOT 3
- Training dataset question (whether crop small patches) HOT 4
- The effect of using display pictures is very poor HOT 4
- How to train StableSR with SD-turbo? HOT 1
- It seems to be a val_dataloader issue HOT 1
- Reporting an Issue with Google Colab Demo HOT 1
- Is there any implementation StableSR in diffusers? HOT 1
- Can I run the StableSR without CFW? HOT 3
- about size match of tensor HOT 4
- Share finding for compression experiment HOT 3
- Test output is black HOT 2
- About FID HOT 2
- ConnectionResetError:[Error 104] Connection reset by peer HOT 1
- Is time-aware guidance really important?
- Is vqgan_finetune_00011.ckpt the same as vqgan_cfw_00011.ckpt?
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from stablesr.