fix ci

lightx2v/models/schedulers/wan/changing_resolution/scheduler.py

@@ -18,7 +18,7 @@ class WanScheduler4ChangingResolution(WanScheduler):
             device=self.device,
             generator=self.generator,
         )
-        
+
         self.noise_original_resolution = torch.randn(
             target_shape[0],
             target_shape[1],
@@ -45,21 +45,17 @@ class WanScheduler4ChangingResolution(WanScheduler):
 
         # 2. upsample clean noise to target shape
         denoised_sample_5d = denoised_sample.unsqueeze(0)  # (C,T,H,W) -> (1,C,T,H,W)
-        clean_noise = torch.nn.functional.interpolate(
-            denoised_sample_5d, 
-            size=(self.config.target_shape[1], self.config.target_shape[2], self.config.target_shape[3]), 
-            mode='trilinear'
-        )
-        clean_noise = clean_noise.squeeze(0)  # (1,C,T,H,W) -> (C,T,H,W)        
-        
+        clean_noise = torch.nn.functional.interpolate(denoised_sample_5d, size=(self.config.target_shape[1], self.config.target_shape[2], self.config.target_shape[3]), mode="trilinear")
+        clean_noise = clean_noise.squeeze(0)  # (1,C,T,H,W) -> (C,T,H,W)
+
         # 3. add noise to clean noise
         noisy_sample = self.add_noise(clean_noise, self.noise_original_resolution, self.timesteps[self.step_index + 1])
-        
+
         # 4. update latents
         self.latents = noisy_sample
-        
+
         # self.disable_corrector = [24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37] # maybe not needed
-        
+
         # 5. update timesteps using shift + 2 更激进的去噪
         self.set_timesteps(self.infer_steps, device=self.device, shift=self.sample_shift + 2)