[Hacktoberfest]Fixing issues #5241 (#5255)

* Update pipeline_wuerstchen_prior.py

* prior_num_inference_steps updated

* height, width, num_inference_steps, and guidance_scale synced

* parameters synced

* latent_mean, latent_std, and resolution_multiple synced

* prior_num_inference_steps changed

* Formatted pipeline_wuerstchen_prior.py

* Update src/diffusers/pipelines/wuerstchen/pipeline_wuerstchen_prior.py

---------
Co-authored-by: Kashif Rasul <kashif.rasul@gmail.com>

src/diffusers/pipelines/wuerstchen/pipeline_wuerstchen.py

@@ -213,13 +213,13 @@ class WuerstchenDecoderPipeline(DiffusionPipeline):
                 Image Embeddings either extracted from an image or generated by a Prior Model.
             prompt (`str` or `List[str]`):
                 The prompt or prompts to guide the image generation.
-            num_inference_steps (`int`, *optional*, defaults to 30):
+            num_inference_steps (`int`, *optional*, defaults to 12):
                 The number of denoising steps. More denoising steps usually lead to a higher quality image at the
                 expense of slower inference.
             timesteps (`List[int]`, *optional*):
                 Custom timesteps to use for the denoising process. If not defined, equal spaced `num_inference_steps`
                 timesteps are used. Must be in descending order.
-            guidance_scale (`float`, *optional*, defaults to 4.0):
+            guidance_scale (`float`, *optional*, defaults to 0.0):
                 Guidance scale as defined in [Classifier-Free Diffusion Guidance](https://arxiv.org/abs/2207.12598).
                 `decoder_guidance_scale` is defined as `w` of equation 2. of [Imagen
                 Paper](https://arxiv.org/pdf/2205.11487.pdf). Guidance scale is enabled by setting

src/diffusers/pipelines/wuerstchen/pipeline_wuerstchen_combined.py

@@ -194,7 +194,7 @@ class WuerstchenCombinedPipeline(DiffusionPipeline):
                 Paper](https://arxiv.org/pdf/2205.11487.pdf). Guidance scale is enabled by setting
                 `prior_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.
-            prior_num_inference_steps (`Union[int, Dict[float, int]]`, *optional*, defaults to 30):
+            prior_num_inference_steps (`Union[int, Dict[float, int]]`, *optional*, defaults to 60):
                 The number of prior denoising steps. More denoising steps usually lead to a higher quality image at the
                 expense of slower inference. For more specific timestep spacing, you can pass customized
                 `prior_timesteps`

src/diffusers/pipelines/wuerstchen/pipeline_wuerstchen_prior.py

@@ -82,6 +82,12 @@ class WuerstchenPriorPipeline(DiffusionPipeline):
             [CLIPTokenizer](https://huggingface.co/docs/transformers/v4.21.0/en/model_doc/clip#transformers.CLIPTokenizer).
         scheduler ([`DDPMWuerstchenScheduler`]):
             A scheduler to be used in combination with `prior` to generate image embedding.
+        latent_mean ('float', *optional*, defaults to 42.0):
+            Mean value for latent diffusers.
+        latent_std ('float', *optional*, defaults to 1.0):
+            Standard value for latent diffusers.
+        resolution_multiple ('float', *optional*, defaults to 42.67):
+            Default resolution for multiple images generated.
     """
 
     model_cpu_offload_seq = "text_encoder->prior"
@@ -282,17 +288,17 @@ class WuerstchenPriorPipeline(DiffusionPipeline):
         Args:
             prompt (`str` or `List[str]`):
                 The prompt or prompts to guide the image generation.
-            height (`int`, *optional*, defaults to 512):
+            height (`int`, *optional*, defaults to 1024):
                 The height in pixels of the generated image.
-            width (`int`, *optional*, defaults to 512):
+            width (`int`, *optional*, defaults to 1024):
                 The width in pixels of the generated image.
-            num_inference_steps (`int`, *optional*, defaults to 30):
+            num_inference_steps (`int`, *optional*, defaults to 60):
                 The number of denoising steps. More denoising steps usually lead to a higher quality image at the
                 expense of slower inference.
             timesteps (`List[int]`, *optional*):
                 Custom timesteps to use for the denoising process. If not defined, equal spaced `num_inference_steps`
                 timesteps are used. Must be in descending order.
-            guidance_scale (`float`, *optional*, defaults to 4.0):
+            guidance_scale (`float`, *optional*, defaults to 8.0):
                 Guidance scale as defined in [Classifier-Free Diffusion Guidance](https://arxiv.org/abs/2207.12598).
                 `decoder_guidance_scale` is defined as `w` of equation 2. of [Imagen
                 Paper](https://arxiv.org/pdf/2205.11487.pdf). Guidance scale is enabled by setting