Fix DREAM training (#8302)

Co-authored-by: Jimmy <39@🇺🇸

.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

src/diffusers/training_utils.py

@@ -157,19 +157,19 @@ def compute_dream_and_update_latents(
     with torch.no_grad():
         pred = unet(noisy_latents, timesteps, encoder_hidden_states).sample
 
-    noisy_latents, target = (None, None)
+    _noisy_latents, _target = (None, None)
     if noise_scheduler.config.prediction_type == "epsilon":
         predicted_noise = pred
         delta_noise = (noise - predicted_noise).detach()
         delta_noise.mul_(dream_lambda)
-        noisy_latents = noisy_latents.add(sqrt_one_minus_alphas_cumprod * delta_noise)
-        target = target.add(delta_noise)
+        _noisy_latents = noisy_latents.add(sqrt_one_minus_alphas_cumprod * delta_noise)
+        _target = target.add(delta_noise)
     elif noise_scheduler.config.prediction_type == "v_prediction":
         raise NotImplementedError("DREAM has not been implemented for v-prediction")
     else:
         raise ValueError(f"Unknown prediction type {noise_scheduler.config.prediction_type}")
 
-    return noisy_latents, target
+    return _noisy_latents, _target
 
 
 def unet_lora_state_dict(unet: UNet2DConditionModel) -> Dict[str, torch.Tensor]: