[BUG] fixed WAN docstring (#11226)

update

Author: ishan-modi

src/diffusers/pipelines/wan/pipeline_wan.py

@@ -417,7 +417,7 @@ def __call__(
             prompt_embeds (`torch.Tensor`, *optional*):
                 Pre-generated text embeddings. Can be used to easily tweak text inputs (prompt weighting). If not
                 provided, text embeddings are generated from the `prompt` input argument.
-            output_type (`str`, *optional*, defaults to `"pil"`):
+            output_type (`str`, *optional*, defaults to `"np"`):
                 The output format of the generated image. Choose between `PIL.Image` or `np.array`.
             return_dict (`bool`, *optional*, defaults to `True`):
                 Whether or not to return a [`WanPipelineOutput`] instead of a plain tuple.

src/diffusers/pipelines/wan/pipeline_wan_i2v.py

@@ -545,7 +545,7 @@ def __call__(
             image_embeds (`torch.Tensor`, *optional*):
                 Pre-generated image embeddings. Can be used to easily tweak image inputs (weighting). If not provided,
                 image embeddings are generated from the `image` input argument.
-            output_type (`str`, *optional*, defaults to `"pil"`):
+            output_type (`str`, *optional*, defaults to `"np"`):
                 The output format of the generated image. Choose between `PIL.Image` or `np.array`.
             return_dict (`bool`, *optional*, defaults to `True`):
                 Whether or not to return a [`WanPipelineOutput`] instead of a plain tuple.

src/diffusers/pipelines/wan/pipeline_wan_video2video.py

@@ -542,7 +542,7 @@ def __call__(
             prompt_embeds (`torch.Tensor`, *optional*):
                 Pre-generated text embeddings. Can be used to easily tweak text inputs (prompt weighting). If not
                 provided, text embeddings are generated from the `prompt` input argument.
-            output_type (`str`, *optional*, defaults to `"pil"`):
+            output_type (`str`, *optional*, defaults to `"np"`):
                 The output format of the generated image. Choose between `PIL.Image` or `np.array`.
             return_dict (`bool`, *optional*, defaults to `True`):
                 Whether or not to return a [`WanPipelineOutput`] instead of a plain tuple.