From 7323e803721ea815d6398f16fbbdaa2e063f9e01 Mon Sep 17 00:00:00 2001
From: Chong-U Lim <me@chongdashu.com>
Date: Thu, 22 Feb 2024 15:03:44 +0000
Subject: [PATCH] Fix docstring of community pipeline imagic

---
 examples/community/imagic_stable_diffusion.py | 15 ++++++---------
 1 file changed, 6 insertions(+), 9 deletions(-)

diff --git a/examples/community/imagic_stable_diffusion.py b/examples/community/imagic_stable_diffusion.py
index acd09c7e0bf4..98e06ceb21ac 100644
--- a/examples/community/imagic_stable_diffusion.py
+++ b/examples/community/imagic_stable_diffusion.py
@@ -346,8 +346,9 @@ def __call__(
         r"""
         Function invoked when calling the pipeline for generation.
         Args:
-            prompt (`str` or `List[str]`):
-                The prompt or prompts to guide the image generation.
+            alpha (`float`, *optional*, defaults to 1.2):
+                The interpolation factor between the original and optimized text embeddings. A value closer to 0
+                will resemble the original input image.
             height (`int`, *optional*, defaults to 512):
                 The height in pixels of the generated image.
             width (`int`, *optional*, defaults to 512):
@@ -361,22 +362,18 @@ def __call__(
                 Paper](https://arxiv.org/pdf/2205.11487.pdf). Guidance scale is enabled by setting `guidance_scale >
                 1`. Higher guidance scale encourages to generate images that are closely linked to the text `prompt`,
                 usually at the expense of lower image quality.
-            eta (`float`, *optional*, defaults to 0.0):
-                Corresponds to parameter eta (η) in the DDIM paper: https://arxiv.org/abs/2010.02502. Only applies to
-                [`schedulers.DDIMScheduler`], will be ignored for others.
             generator (`torch.Generator`, *optional*):
                 A [torch generator](https://pytorch.org/docs/stable/generated/torch.Generator.html) to make generation
                 deterministic.
-            latents (`torch.FloatTensor`, *optional*):
-                Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
-                generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
             output_type (`str`, *optional*, defaults to `"pil"`):
                 The output format of the generate image. Choose between
                 [PIL](https://pillow.readthedocs.io/en/stable/): `PIL.Image.Image` or `nd.array`.
             return_dict (`bool`, *optional*, defaults to `True`):
                 Whether or not to return a [`~pipelines.stable_diffusion.StableDiffusionPipelineOutput`] instead of a
                 plain tuple.
+            eta (`float`, *optional*, defaults to 0.0):
+                Corresponds to parameter eta (η) in the DDIM paper: https://arxiv.org/abs/2010.02502. Only applies to
+                [`schedulers.DDIMScheduler`], will be ignored for others.
         Returns:
             [`~pipelines.stable_diffusion.StableDiffusionPipelineOutput`] or `tuple`:
             [`~pipelines.stable_diffusion.StableDiffusionPipelineOutput`] if `return_dict` is True, otherwise a `tuple.