fix ddim to use alpha_cumprod

dalle2_pytorch/dalle2_pytorch.py

@@ -2845,12 +2845,13 @@ class Decoder(nn.Module):
         inpaint_mask = None,
         inpaint_resample_times = 5
     ):
-        batch, device, total_timesteps, alphas, eta = shape[0], self.device, noise_scheduler.num_timesteps, noise_scheduler.alphas_cumprod_prev, self.ddim_sampling_eta
+        batch, device, total_timesteps, alphas, eta = shape[0], self.device, noise_scheduler.num_timesteps, noise_scheduler.alphas_cumprod, self.ddim_sampling_eta
 
         times = torch.linspace(0., total_timesteps, steps = timesteps + 2)[:-1]
 
         times = list(reversed(times.int().tolist()))
         time_pairs = list(zip(times[:-1], times[1:]))
+        time_pairs = list(filter(lambda t: t[0] > t[1], time_pairs))
 
         is_inpaint = exists(inpaint_image)
         resample_times = inpaint_resample_times if is_inpaint else 1

dalle2_pytorch/version.py

@@ -1 +1 @@
-__version__ = '1.10.1'
+__version__ = '1.10.2'