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| author | Laurent Mazare <laurent.mazare@gmail.com> | 2023-08-06 18:49:43 +0200 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2023-08-06 17:49:43 +0100 |
| commit | d34039e35267b3f4de83770f8da4ea31491bcec5 (patch) | |
| tree | 6efc4796859a04223d2211303cc12b3a97321fcc /candle-examples/examples/stable-diffusion/stable_diffusion.rs | |
| parent | 93cfe5642f473889d1df62ccb8f1740f77523dd3 (diff) | |
| download | candle-d34039e35267b3f4de83770f8da4ea31491bcec5.tar.gz candle-d34039e35267b3f4de83770f8da4ea31491bcec5.tar.bz2 candle-d34039e35267b3f4de83770f8da4ea31491bcec5.zip | |
Add a stable diffusion example (#328)
* Start adding a stable-diffusion example.
* Proper computation of the causal mask.
* Add the chunk operation.
* Work in progress: port the attention module.
* Add some dummy modules for conv2d and group-norm, get the attention module to compile.
* Re-enable the 2d convolution.
* Add the embeddings module.
* Add the resnet module.
* Add the unet blocks.
* Add the unet.
* And add the variational auto-encoder.
* Use the pad function from utils.
Diffstat (limited to 'candle-examples/examples/stable-diffusion/stable_diffusion.rs')
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