fix latent caching

Author: linoytsaban

examples/dreambooth/train_dreambooth_lora_sd3.py

@@ -1512,6 +1512,8 @@ def compute_text_embeddings(prompt, text_encoders, tokenizers):
                 tokens_two = torch.cat([tokens_two, class_tokens_two], dim=0)
                 tokens_three = torch.cat([tokens_three, class_tokens_three], dim=0)
 
+    vae_config_shift_factor = vae.config.shift_factor
+    vae_config_scaling_factor = vae.config.scaling_factor
     if args.cache_latents:
         latents_cache = []
         for batch in tqdm(train_dataloader, desc="Caching latents"):
@@ -1685,7 +1687,8 @@ def get_sigmas(timesteps, n_dim=4, dtype=torch.float32):
                 else:
                     pixel_values = batch["pixel_values"].to(dtype=vae.dtype)
                     model_input = vae.encode(pixel_values).latent_dist.sample()
-                model_input = (model_input - vae.config.shift_factor) * vae.config.scaling_factor
+
+                model_input = (model_input - vae_config_shift_factor) * vae_config_scaling_factor
                 model_input = model_input.to(dtype=weight_dtype)
 
                 # Sample noise that we'll add to the latents