From eb6e1b508e920efd840f2fa13e80d60ce19ed2c1 Mon Sep 17 00:00:00 2001 From: Phil Wang Date: Mon, 31 Jan 2022 17:13:27 -0800 Subject: [PATCH] greater kernel size in convnext blocks --- denoising_diffusion_pytorch/denoising_diffusion_pytorch.py | 7 +++---- setup.py | 2 +- 2 files changed, 4 insertions(+), 5 deletions(-) diff --git a/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py b/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py index 5f5f8f4..5fafe76 100644 --- a/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py +++ b/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py @@ -95,7 +95,7 @@ def Upsample(dim): return nn.ConvTranspose2d(dim, dim, 4, 2, 1) def Downsample(dim): - return nn.Conv2d(dim, dim, 3, 2, 1) + return nn.Conv2d(dim, dim, 4, 2, 1) class LayerNorm(nn.Module): def __init__(self, dim, eps = 1e-5): @@ -135,10 +135,9 @@ class ConvNextBlock(nn.Module): self.net = nn.Sequential( LayerNorm(dim) if norm else nn.Identity(), - nn.Conv2d(dim, dim_out * mult, 1), + nn.Conv2d(dim, dim_out * mult, 3, padding = 1), nn.GELU(), - LayerNorm(dim_out * mult), - nn.Conv2d(dim_out * mult, dim_out, 1) + nn.Conv2d(dim_out * mult, dim_out, 3, padding = 1) ) self.res_conv = nn.Conv2d(dim, dim_out, 1) if dim != dim_out else nn.Identity() diff --git a/setup.py b/setup.py index 1b9f790..caf6439 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 = '0.7.0', + version = '0.7.1', license='MIT', description = 'Denoising Diffusion Probabilistic Models - Pytorch', author = 'Phil Wang',