default to ddim sampling, since not sure how to incorporate scale into logsnr yet

Author: lucidrains

README.md

@@ -42,7 +42,6 @@ model = RIN(
 diffusion = GaussianDiffusion(
     model,
     image_size = 128,
-    use_ddim = False,
     timesteps = 400,
     train_prob_self_cond = 0.9,  # how often to self condition on latents
     scale = 1.                   # this will be set to < 1. for more noising and leads to better convergence when training on higher resolution images (512, 1024) - input noised images will be auto variance normalized

rin_pytorch/rin_pytorch.py

@@ -514,7 +514,7 @@ def __init__(
         *,
         image_size,
         timesteps = 1000,
-        use_ddim = False,
+        use_ddim = True,
         noise_schedule = 'sigmoid',
         objective = 'eps',
         schedule_kwargs: dict = dict(),

setup.py

@@ -3,7 +3,7 @@
 setup(
   name = 'RIN-pytorch',
   packages = find_packages(exclude=[]),
-  version = '0.4.2',
+  version = '0.4.3',
   license='MIT',
   description = 'RIN - Recurrent Interface Network - Pytorch',
   author = 'Phil Wang',