Update custom_pipeline.py

custom_pipeline.py

@@ -64,14 +64,17 @@ EXAMPLE_DOC_STRING = """
         >>> import torch
         >>> from diffusers import StableDiffusionXLInstructPix2PixPipeline
         >>> from diffusers.utils import load_image
+
         >>> resolution = 768
         >>> image = load_image(
         ...     "https://hf.co/datasets/diffusers/diffusers-images-docs/resolve/main/mountain.png"
         ... ).resize((resolution, resolution))
         >>> edit_instruction = "Turn sky into a cloudy one"
+
         >>> pipe = StableDiffusionXLInstructPix2PixPipeline.from_pretrained(
         ...     "diffusers/sdxl-instructpix2pix-768", torch_dtype=torch.float16
         ... ).to("cuda")
+
         >>> edited_image = pipe(
         ...     prompt=edit_instruction,
         ...     image=image,
@@ -123,13 +126,16 @@ class CosStableDiffusionXLInstructPix2PixPipeline(
 ):
     r"""
     Pipeline for pixel-level image editing by following text instructions. Based on Stable Diffusion XL.
+
     This model inherits from [`DiffusionPipeline`]. Check the superclass documentation for the generic methods the
     library implements for all the pipelines (such as downloading or saving, running on a particular device, etc.)
+
     The pipeline also inherits the following loading methods:
         - [`~loaders.TextualInversionLoaderMixin.load_textual_inversion`] for loading textual inversion embeddings
         - [`~loaders.FromSingleFileMixin.from_single_file`] for loading `.ckpt` files
         - [`~loaders.StableDiffusionXLLoraLoaderMixin.load_lora_weights`] for loading LoRA weights
         - [`~loaders.StableDiffusionXLLoraLoaderMixin.save_lora_weights`] for saving LoRA weights
+
     Args:
         vae ([`AutoencoderKL`]):
             Variational Auto-Encoder (VAE) Model to encode and decode images to and from latent representations.
@@ -220,6 +226,7 @@ class CosStableDiffusionXLInstructPix2PixPipeline(
     ):
         r"""
         Encodes the prompt into text encoder hidden states.
+
         Args:
             prompt (`str` or `List[str]`, *optional*):
                 prompt to be encoded
@@ -621,6 +628,7 @@ class CosStableDiffusionXLInstructPix2PixPipeline(
     ):
         r"""
         Function invoked when calling the pipeline for generation.
+
         Args:
             prompt (`str` or `List[str]`, *optional*):
                 The prompt or prompts to guide the image generation. If not defined, one has to pass `prompt_embeds`.
@@ -731,7 +739,9 @@ class CosStableDiffusionXLInstructPix2PixPipeline(
                 Part of SDXL's micro-conditioning as explained in section 2.2 of
                 [https://huggingface.co/papers/2307.01952](https://huggingface.co/papers/2307.01952). Can be used to
                 simulate an aesthetic score of the generated image by influencing the negative text condition.
+
         Examples:
+
         Returns:
             [`~pipelines.stable_diffusion_xl.StableDiffusionXLPipelineOutput`] or `tuple`:
             [`~pipelines.stable_diffusion_xl.StableDiffusionXLPipelineOutput`] if `return_dict` is True, otherwise a