Merge branch 'main' of https://github.com/huggingface/diffusers into main

README.md

@@ -55,7 +55,7 @@ num_prediction_steps = len(noise_scheduler)
 for t in tqdm.tqdm(reversed(range(num_prediction_steps)), total=num_prediction_steps):
 	# predict noise residual
 	with torch.no_grad():
-			residual = unet(image, t)
+		residual = unet(image, t)
 
 	# predict previous mean of image x_t-1
 	pred_prev_image = noise_scheduler.compute_prev_image_step(residual, image, t)
@@ -63,8 +63,8 @@ for t in tqdm.tqdm(reversed(range(num_prediction_steps)), total=num_prediction_s
 	# optionally sample variance
 	variance = 0
 	if t > 0:
-			noise = noise_scheduler.sample_noise(image.shape, device=image.device, generator=generator)
-			variance = noise_scheduler.get_variance(t).sqrt() * noise
+		noise = noise_scheduler.sample_noise(image.shape, device=image.device, generator=generator)
+		variance = noise_scheduler.get_variance(t).sqrt() * noise
 
 	# set current image to prev_image: x_t -> x_t-1
 	image = pred_prev_image + variance