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Fix link (#24)

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Luca Antiga
2023-07-25 09:58:18 +02:00
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@@ -28,7 +28,7 @@ Modularity is king. This repo implements a config-driven approach where we build
### Changelog from the old `ldm` codebase ### Changelog from the old `ldm` codebase
For training, we use [pytorch-lightning](https://www.pytorchlightning.ai/index.html), but it should be easy to use other training wrappers around the base modules. The core diffusion model class (formerly `LatentDiffusion`, now `DiffusionEngine`) has been cleaned up: For training, we use [PyTorch Lightning](https://lightning.ai/docs/pytorch/stable/), but it should be easy to use other training wrappers around the base modules. The core diffusion model class (formerly `LatentDiffusion`, now `DiffusionEngine`) has been cleaned up:
- No more extensive subclassing! We now handle all types of conditioning inputs (vectors, sequences and spatial conditionings, and all combinations thereof) in a single class: `GeneralConditioner`, see `sgm/modules/encoders/modules.py`. - No more extensive subclassing! We now handle all types of conditioning inputs (vectors, sequences and spatial conditionings, and all combinations thereof) in a single class: `GeneralConditioner`, see `sgm/modules/encoders/modules.py`.
- We separate guiders (such as classifier-free guidance, see `sgm/modules/diffusionmodules/guiders.py`) from the - We separate guiders (such as classifier-free guidance, see `sgm/modules/diffusionmodules/guiders.py`) from the