Release: v0.20.1

Fix torch compile for controlnete

docs/source/en/training/controlnet.md

@@ -265,7 +265,7 @@ distributed_type: DEEPSPEED
 
 See [documentation](https://huggingface.co/docs/accelerate/usage_guides/deepspeed) for more DeepSpeed configuration options.
 
-</Tip>
+<Tip>
 
 Changing the default Adam optimizer to DeepSpeed's Adam
 `deepspeed.ops.adam.DeepSpeedCPUAdam` gives a substantial speedup but
@@ -330,4 +330,4 @@ image.save("./output.png")
 
 ## Stable Diffusion XL
 
-Training with [Stable Diffusion XL](https://huggingface.co/papers/2307.01952) is also supported via the `train_controlnet_sdxl.py` script. Please refer to the docs [here](https://github.com/huggingface/diffusers/blob/main/examples/controlnet/README_sdxl.md). 
+Training with [Stable Diffusion XL](https://huggingface.co/papers/2307.01952) is also supported via the `train_controlnet_sdxl.py` script. Please refer to the docs [here](https://github.com/huggingface/diffusers/blob/main/examples/controlnet/README_sdxl.md). 

setup.py

@@ -233,7 +233,7 @@ install_requires = [
 
 setup(
     name="diffusers",
-    version="0.20.2",  # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
+    version="0.20.1",  # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
     description="Diffusers",
     long_description=open("README.md", "r", encoding="utf-8").read(),
     long_description_content_type="text/markdown",

src/diffusers/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "0.20.2"
+__version__ = "0.20.1"
 
 from .configuration_utils import ConfigMixin
 from .utils import (

src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl_inpaint.py

@@ -861,7 +861,7 @@ class StableDiffusionXLInpaintPipeline(DiffusionPipeline, LoraLoaderMixin, FromS
         mask_image: Union[torch.FloatTensor, PIL.Image.Image] = None,
         height: Optional[int] = None,
         width: Optional[int] = None,
-        strength: float = 0.9999,
+        strength: float = 1.0,
         num_inference_steps: int = 50,
         denoising_start: Optional[float] = None,
         denoising_end: Optional[float] = None,
@@ -910,7 +910,7 @@ class StableDiffusionXLInpaintPipeline(DiffusionPipeline, LoraLoaderMixin, FromS
                 The height in pixels of the generated image.
             width (`int`, *optional*, defaults to self.unet.config.sample_size * self.vae_scale_factor):
                 The width in pixels of the generated image.
-            strength (`float`, *optional*, defaults to 0.9999):
+            strength (`float`, *optional*, defaults to 1.):
                 Conceptually, indicates how much to transform the masked portion of the reference `image`. Must be
                 between 0 and 1. `image` will be used as a starting point, adding more noise to it the larger the
                 `strength`. The number of denoising steps depends on the amount of noise initially added. When