).eval()
unet = UNet2DConditionModel.from_pretrained(args.pretrained_decoder_model_name_or_path, subfolder="unet")
```  
Next, the script includes several image transforms and a [preprocessing](https://github.com/huggingface/diffusers/blob/6e68c71503682c8693cb5b06a4da4911dfd655ee/examples/kandinsky2_2/text_to_image/train_text_to_image_decoder.py#L622) function for applying the transforms to the images and returning the pixel values:  
```py
def preprocess_train(examples):