[Stable Diffusion Inpainting] Deprecate inpainting pipeline in favor of official one (#903)

* finish

* up

* Apply suggestions from code review

Co-authored-by: Anton Lozhkov <[email protected]>

* Update src/diffusers/pipeline_utils.py

* Finish

Co-authored-by: Anton Lozhkov <[email protected]>

Author: patrickvonplaten

src/diffusers/__init__.py

@@ -52,6 +52,7 @@
         LDMTextToImagePipeline,
         StableDiffusionImg2ImgPipeline,
         StableDiffusionInpaintPipeline,
+        StableDiffusionInpaintPipelineLegacy,
         StableDiffusionPipeline,
     )
 else:

src/diffusers/pipeline_utils.py

@@ -40,6 +40,7 @@
     ONNX_WEIGHTS_NAME,
     WEIGHTS_NAME,
     BaseOutput,
+    deprecate,
     is_transformers_available,
     logging,
 )
@@ -413,6 +414,25 @@ def from_pretrained(cls, pretrained_model_name_or_path: Optional[Union[str, os.P
             diffusers_module = importlib.import_module(cls.__module__.split(".")[0])
             pipeline_class = getattr(diffusers_module, config_dict["_class_name"])
 
+        # To be removed in 1.0.0
+        if pipeline_class.__name__ == "StableDiffusionInpaintPipeline" and version.parse(
+            version.parse(config_dict["_diffusers_version"]).base_version
+        ) <= version.parse("0.5.1"):
+            from diffusers import StableDiffusionInpaintPipeline, StableDiffusionInpaintPipelineLegacy
+
+            pipeline_class = StableDiffusionInpaintPipelineLegacy
+
+            deprecation_message = (
+                "You are using a legacy checkpoint for inpainting with Stable Diffusion, therefore we are loading the"
+                f" {StableDiffusionInpaintPipelineLegacy} class instead of {StableDiffusionInpaintPipeline}. For"
+                " better inpainting results, we strongly suggest using Stable Diffusion's official inpainting"
+                " checkpoint: https://huggingface.co/runwayml/stable-diffusion-inpainting instead or adapting your"
+                f" checkpoint {pretrained_model_name_or_path} to the format of"
+                " https://huggingface.co/runwayml/stable-diffusion-inpainting. Note that we do not actively maintain"
+                " the {StableDiffusionInpaintPipelineLegacy} class and will likely remove it in version 1.0.0."
+            )
+            deprecate("StableDiffusionInpaintPipelineLegacy", "1.0.0", deprecation_message, standard_warn=False)
+
         # some modules can be passed directly to the init
         # in this case they are already instantiated in `kwargs`
         # extract them here

src/diffusers/pipelines/__init__.py

@@ -16,6 +16,7 @@
     from .stable_diffusion import (
         StableDiffusionImg2ImgPipeline,
         StableDiffusionInpaintPipeline,
+        StableDiffusionInpaintPipelineLegacy,
         StableDiffusionPipeline,
     )
 

src/diffusers/pipelines/stable_diffusion/__init__.py

@@ -31,6 +31,7 @@ class StableDiffusionPipelineOutput(BaseOutput):
     from .pipeline_stable_diffusion import StableDiffusionPipeline
     from .pipeline_stable_diffusion_img2img import StableDiffusionImg2ImgPipeline
     from .pipeline_stable_diffusion_inpaint import StableDiffusionInpaintPipeline
+    from .pipeline_stable_diffusion_inpaint_legacy import StableDiffusionInpaintPipelineLegacy
     from .safety_checker import StableDiffusionSafetyChecker
 
 if is_transformers_available() and is_onnx_available():

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint.py

@@ -82,8 +82,6 @@ def __init__(
         feature_extractor: CLIPFeatureExtractor,
     ):
         super().__init__()
-        logger.info("`StableDiffusionInpaintPipeline` is experimental and will very likely change in the future.")
-
         if hasattr(scheduler.config, "steps_offset") and scheduler.config.steps_offset != 1:
             deprecation_message = (
                 f"The configuration file of this scheduler: {scheduler} is outdated. `steps_offset`"
@@ -223,6 +221,8 @@ def __call__(
             list of `bool`s denoting whether the corresponding generated image likely represents "not-safe-for-work"
             (nsfw) content, according to the `safety_checker`.
         """
+        # TODO(Suraj) - adapt to your use case
+
         if isinstance(prompt, str):
             batch_size = 1
         elif isinstance(prompt, list):