From 84731bb03d1830be8ab68a46a1ad7124ed01d73d Mon Sep 17 00:00:00 2001 From: Phil Wang Date: Wed, 4 May 2022 10:38:29 -0700 Subject: [PATCH] groupnorm groups should be actually configurable --- denoising_diffusion_pytorch/denoising_diffusion_pytorch.py | 4 ++-- setup.py | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py b/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py index 49688f3..a57cf76 100644 --- a/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py +++ b/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py @@ -128,8 +128,8 @@ class ResnetBlock(nn.Module): nn.Linear(time_emb_dim, dim_out) ) if exists(time_emb_dim) else None - self.block1 = Block(dim, dim_out) - self.block2 = Block(dim_out, dim_out) + self.block1 = Block(dim, dim_out, groups = groups) + self.block2 = Block(dim_out, dim_out, groups = groups) self.res_conv = nn.Conv2d(dim, dim_out, 1) if dim != dim_out else nn.Identity() def forward(self, x, time_emb = None): diff --git a/setup.py b/setup.py index 6b0f4fb..d427e3e 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 = '0.11.1', + version = '0.11.2', license='MIT', description = 'Denoising Diffusion Probabilistic Models - Pytorch', author = 'Phil Wang',