about the pretrain_mode

[ZhouHaoWa]

i have tried three pretrain_model, all of them generative close to Gaussian noise，does anyone get the same problem as me?

[dome272]

What do you mean with "pretrain_model"? Do you mean when you train the models, all you get is noise when sampling?

[ZhouHaoWa]

sorry, i got it wrong, I confused pre-train with checkpoints. I just used three checkpoints you have shared to generative the pic, of course it doesn't work. I would like to take this opportunity to thank you for sharing the code and video explanation, as a beginner, I have learned a lot, thank you very much, I will continue to pay attention to your sharing.

[igoindown]

sorry, i got it wrong, I confused pre-train with checkpoints. I just used three checkpoints you have shared to generative the pic, of course it doesn't work. I would like to take this opportunity to thank you for sharing the code and video explanation, as a beginner, I have learned a lot, thank you very much, I will continue to pay attention to your sharing.

Hi, I'm having the same problem as you, so what should I do to generate the images correctly

[ChaunceyWang]

I trained the model following this project setting, Here is my modes, The generation images seems better than the models given, while the results can also be improved.

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@ZhouHaoWa @dome272 I have the same problem, I used the model given by the link and run the demo code. However, the results were almost Gaussian noise, is there any thing wrong? （Is the model weights given randomly initialized？）

    model = UNet().to(device)
    ckpt = torch.load("unconditional_ckpt.pt")
    model.load_state_dict(ckpt)
    diffusion = Diffusion(img_size=64, device=device)
    x = diffusion.sample(model, n=16)
    plot_images(x)