Fix when latents is None

animatediff/pipelines/pipeline_animation.py

@@ -332,8 +332,11 @@ class AnimationPipeline(DiffusionPipeline):
                 if init_latents is not None:
                     init_latents = init_latents.unsqueeze(0).repeat(batch_size, 1, 1, 1, 1)
                     for i in range(video_length):
-                        init_alpha = (video_length - float(i)) / video_length / 30
-                        latents[:, :, i, :, :] = init_latents * init_alpha + latents[:, :, i, :, :] * (1 - init_alpha)
+                        if init_latents is None:
+                            latents[:, :, i, :, :] = torch.randn(latents[:, :, i, :, :].shape, device=rand_device, dtype=dtype) * self.scheduler.init_noise_sigma
+                        else:
+                            init_alpha = (video_length - float(i)) / video_length / 30
+                            latents[:, :, i, :, :] = init_latents * init_alpha + latents[:, :, i, :, :] * (1 - init_alpha)
                 else:
                     latents = torch.randn(shape, generator=generator, device=rand_device, dtype=dtype).to(device)
 
@@ -349,6 +352,7 @@ class AnimationPipeline(DiffusionPipeline):
         return latents
 
 
+
     @torch.no_grad()
     def __call__(
         self,