If True, the function will preprocess and clean the provided caption before encoding.    Encodes the prompt into text encoder hidden states.  IFImg2ImgSuperResolutionPipeline  class diffusers.IFImg2ImgSuperResolutionPipeline  < source > ( tokenizer: T5Tokenizer text_encoder: T5EncoderModel unet: UNet2DConditionModel scheduler: DDPMScheduler image_noising_scheduler: DDPMScheduler safety_checker: Optional feature_extractor: Optional watermarker: Optional requires_safety_checker: bool = True  )     __call__  < source > ( image: Union original_image: Union = None strength: float = 0.8 prompt: Union = None num_inference_steps: int = 50 timesteps: List = None guidance_scale: float = 4.0 negative_prompt: Union = None num_images_per_prompt: Optional = 1 eta: float = 0.0 generator: Union = None prompt_embeds: Optional = None negative_prompt_embeds: Optional = None output_type: Optional = 'pil' return_dict: bool = True callback: Optional = None callback_steps: int = 1 cross_attention_kwargs: Optional = None noise_level: int = 250 clean_caption: bool = True  ) → ~pipelines.stable_diffusion.IFPipelineOutput or tuple  Parameters   image (torch.FloatTensor or PIL.Image.Image) —