[Flax] Add Flax inpainting impl (huggingface#1966)

* [Flax] Add Flax inpainting impl

* fixed copies, add README.md

* fixed README.md

* add test

* format

* update README.md

README.md

@@ -284,6 +284,53 @@ output = pipeline(
 output_images = pipeline.numpy_to_pil(np.asarray(output.reshape((num_samples,) + output.shape[-3:])))
 ```
 
+Diffusers also has a Text-guided inpainting pipeline with Flax/Jax
+
+```python
+import jax
+import numpy as np
+from flax.jax_utils import replicate
+from flax.training.common_utils import shard
+import PIL
+import requests
+from io import BytesIO
+
+
+from diffusers import FlaxStableDiffusionInpaintPipeline
+
+def download_image(url):
+    response = requests.get(url)
+    return PIL.Image.open(BytesIO(response.content)).convert("RGB")
+img_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png"
+mask_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png"
+
+init_image = download_image(img_url).resize((512, 512))
+mask_image = download_image(mask_url).resize((512, 512))
+
+pipeline, params = FlaxStableDiffusionInpaintPipeline.from_pretrained("xvjiarui/stable-diffusion-2-inpainting")
+
+prompt = "Face of a yellow cat, high resolution, sitting on a park bench"
+prng_seed = jax.random.PRNGKey(0)
+num_inference_steps = 50
+
+num_samples = jax.device_count()
+prompt = num_samples * [prompt]
+init_image = num_samples * [init_image]
+mask_image = num_samples * [mask_image]
+prompt_ids, processed_masked_images, processed_masks = pipeline.prepare_inputs(prompt, init_image, mask_image)
+
+
+# shard inputs and rng
+params = replicate(params)
+prng_seed = jax.random.split(prng_seed, jax.device_count())
+prompt_ids = shard(prompt_ids)
+processed_masked_images = shard(processed_masked_images)
+processed_masks = shard(processed_masks)
+
+images = pipeline(prompt_ids, processed_masks, processed_masked_images, params, prng_seed, num_inference_steps, jit=True).images
+images = pipeline.numpy_to_pil(np.asarray(images.reshape((num_samples,) + images.shape[-3:])))
+```
+
 ### Image-to-Image text-guided generation with Stable Diffusion
 
 The `StableDiffusionImg2ImgPipeline` lets you pass a text prompt and an initial image to condition the generation of new images.

src/diffusers/__init__.py

@@ -182,4 +182,8 @@
 except OptionalDependencyNotAvailable:
     from .utils.dummy_flax_and_transformers_objects import *  # noqa F403
 else:
-    from .pipelines import FlaxStableDiffusionImg2ImgPipeline, FlaxStableDiffusionPipeline
+    from .pipelines import (
+        FlaxStableDiffusionImg2ImgPipeline,
+        FlaxStableDiffusionInpaintPipeline,
+        FlaxStableDiffusionPipeline,
+    )

src/diffusers/pipelines/__init__.py

@@ -108,4 +108,8 @@
 except OptionalDependencyNotAvailable:
     from ..utils.dummy_flax_and_transformers_objects import *  # noqa F403
 else:
-    from .stable_diffusion import FlaxStableDiffusionImg2ImgPipeline, FlaxStableDiffusionPipeline
+    from .stable_diffusion import (
+        FlaxStableDiffusionImg2ImgPipeline,
+        FlaxStableDiffusionInpaintPipeline,
+        FlaxStableDiffusionPipeline,
+    )

src/diffusers/pipelines/stable_diffusion/__init__.py

@@ -99,4 +99,5 @@ class FlaxStableDiffusionPipelineOutput(BaseOutput):
     from ...schedulers.scheduling_pndm_flax import PNDMSchedulerState
     from .pipeline_flax_stable_diffusion import FlaxStableDiffusionPipeline
     from .pipeline_flax_stable_diffusion_img2img import FlaxStableDiffusionImg2ImgPipeline
+    from .pipeline_flax_stable_diffusion_inpaint import FlaxStableDiffusionInpaintPipeline
     from .safety_checker_flax import FlaxStableDiffusionSafetyChecker