From 207d23af86c79b886a345f8851572ba8c1c50f62 Mon Sep 17 00:00:00 2001 From: wassname Date: Thu, 22 Dec 2022 10:57:30 +0800 Subject: [PATCH] Update denoising_diffusion_pytorch.py Shouldn't eta be 0 for DDIM sampling? In the DDIM paper in section 5.1 they mention the eta=0 is DDIM, and eta=1 approximates the normal DDPM. They also use [eta=0](https://github.com/openai/improved-diffusion/blob/e94489283bb876ac1477d5dd7709bbbd2d9902ce/improved_diffusion/gaussian_diffusion.py#L487) in the openai implementation of DDIM. --- denoising_diffusion_pytorch/denoising_diffusion_pytorch.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py b/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py index 708e09e..7f586f1 100644 --- a/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py +++ b/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py @@ -431,7 +431,7 @@ class GaussianDiffusion(nn.Module): beta_schedule = 'cosine', p2_loss_weight_gamma = 0., # p2 loss weight, from https://arxiv.org/abs/2204.00227 - 0 is equivalent to weight of 1 across time - 1. is recommended p2_loss_weight_k = 1, - ddim_sampling_eta = 1. + ddim_sampling_eta = 0. ): super().__init__() assert not (type(self) == GaussianDiffusion and model.channels != model.out_dim)