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todo
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@@ -824,6 +824,7 @@ Once built, images will be saved to the same directory the command is invoked
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- [ ] become an expert with unets, cleanup unet code, make it fully configurable, port all learnings over to https://github.com/lucidrains/x-unet
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- [ ] copy the cascading ddpm code to a separate repo (perhaps https://github.com/lucidrains/denoising-diffusion-pytorch) as the main contribution of dalle2 really is just the prior network
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- [ ] transcribe code to Jax, which lowers the activation energy for distributed training, given access to TPUs
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- [ ] pull logic for training diffusion prior into a class DiffusionPriorTrainer, for eventual script based + CLI based training
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- [ ] train on a toy task, offer in colab
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- [ ] think about how best to design a declarative training config that handles preencoding for prior and training of multiple networks in decoder
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- [ ] extend diffusion head to use diffusion-gan (potentially using lightweight-gan) to speed up inference
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