From ddc31bc48909161e440e035f6b021189b8bf5834 Mon Sep 17 00:00:00 2001
From: Phil Wang <lucidrains@gmail.com>
Date: Sun, 27 Nov 2022 10:05:55 -0800
Subject: [PATCH] trust paper

---
 README.md                                              | 10 ++++++++++
 .../denoising_diffusion_pytorch.py                     |  5 ++++-
 setup.py                                               |  2 +-
 3 files changed, 15 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 1514ee1..f10a3c5 100644
--- a/README.md
+++ b/README.md
@@ -248,3 +248,13 @@ sampled_seq.shape # (4, 32, 128)
     volume  = {abs/2207.12598}
 }
 ```
+
+```bibtex
+@article{Sunkara2022NoMS,
+    title   = {No More Strided Convolutions or Pooling: A New CNN Building Block for Low-Resolution Images and Small Objects},
+    author  = {Raja Sunkara and Tie Luo},
+    journal = {ArXiv},
+    year    = {2022},
+    volume  = {abs/2208.03641}
+}
+```
diff --git a/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py b/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py
index fc6af0e..de628db 100644
--- a/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py
+++ b/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py
@@ -86,7 +86,10 @@ def Upsample(dim, dim_out = None):
     )
 
 def Downsample(dim, dim_out = None):
-    return nn.Conv2d(dim, default(dim_out, dim), 4, 2, 1)
+    return nn.Sequential(
+        Rearrange('b c (h p1) (w p2) -> b (c p1 p2) h w', p1 = 2, p2 = 2),
+        nn.Conv2d(dim * 4, default(dim_out, dim), 1)
+    )
 
 class WeightStandardizedConv2d(nn.Conv2d):
     """
diff --git a/setup.py b/setup.py
index f0969c1..1937242 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 = '0.31.1',
+  version = '0.32.0',
   license='MIT',
   description = 'Denoising Diffusion Probabilistic Models - Pytorch',
   author = 'Phil Wang',