From 532178a6a3cc603657e4816d3a4d07f6a13b8f20 Mon Sep 17 00:00:00 2001 From: Phil Wang Date: Tue, 7 Jun 2022 16:12:44 -0700 Subject: [PATCH] assume when sampling all batch samples are at the same time, and do not noise for the last time step --- .../continuous_time_gaussian_diffusion.py | 4 ++++ setup.py | 2 +- 2 files changed, 5 insertions(+), 1 deletion(-) diff --git a/denoising_diffusion_pytorch/continuous_time_gaussian_diffusion.py b/denoising_diffusion_pytorch/continuous_time_gaussian_diffusion.py index 3a4f91a..063be8b 100644 --- a/denoising_diffusion_pytorch/continuous_time_gaussian_diffusion.py +++ b/denoising_diffusion_pytorch/continuous_time_gaussian_diffusion.py @@ -131,6 +131,10 @@ class ContinuousTimeGaussianDiffusion(nn.Module): batch, *_, device = *x.shape, x.device model_mean, model_variance = self.p_mean_variance(x = x, time = time, time_next = time_next) + + if time_next == 0: + return model_mean + noise = torch.randn_like(x) return model_mean + sqrt(model_variance) * noise diff --git a/setup.py b/setup.py index f0690f4..22fe6a8 100644 --- a/setup.py +++ b/setup.py @@ -3,7 +3,7 @@ from setuptools import setup, find_packages setup( name = 'denoising-diffusion-pytorch', packages = find_packages(), - version = '0.16.3', + version = '0.16.4', license='MIT', description = 'Denoising Diffusion Probabilistic Models - Pytorch', author = 'Phil Wang',