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Did anyone get good CIFAR10 results? #100

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IdoZach opened this issue Sep 30, 2022 · 8 comments
Open

Did anyone get good CIFAR10 results? #100

IdoZach opened this issue Sep 30, 2022 · 8 comments

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@IdoZach
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IdoZach commented Sep 30, 2022

Hi, thanks for providing this code. I'm trying to reproduce the CIFAR10 results from the original DDPM paper. I use 3x32x32 images, all the CIFAR data (50k frames), 2000 epochs (but I check every 100 epochs how it looks like), and I get some similar results, but not as good as the paper.
This is the result that I get:
image
I'm also attaching the training results that I get (the divergent one is the validation loss):
image
My training schedule is similar to the original except that I maximize the batch size on my GPUs. I'm using image size of 32, and U-Net options dim=64, dim_mults=(1,2,4,8).

Was anyone more successful and can share their results and tips? I think that this result is far from perfect. Thanks very much, I hope you could help me find what I'm missing.

@tcapelle
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tcapelle commented Oct 4, 2022

nop, have been trying all day. MNIST works fine

@yiyixuxu
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yiyixuxu commented Oct 4, 2022

you can try p2_loss_weight_gamma = 1. , my result with cifar10 wasn't great either with the default setting but I think you can see a big difference with p2 weighting - the original paper used a reweighted loss too

@we1cao
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we1cao commented Oct 28, 2022

How do you show the loss on the tensorboard? Could you share the code maybe?

@malbergo
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malbergo commented Nov 5, 2022

does someone have example code for mnist/cifar10?

@tcapelle
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tcapelle commented Nov 5, 2022 via email

@Gregory1994
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similar problem, any solution please?
sample-69

@pimakshay
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What parameter is 'p2_loss_weight_gamma'? and where do we exactly use it? Can anyone highlight it in the denoising_diffusion_pytorch.py file?

@chengyiqiu1121
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you can try p2_loss_weight_gamma = 1. , my result with cifar10 wasn't great either with the default setting but I think you can see a big difference with p2 weighting - the original paper used a reweighted loss too

Can u tell me where is p2_loss_weight_gamma, i did not find it

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8 participants