Feature/zimage inpaint pipeline (#13006)
* Add ZImageInpaintPipeline
Updated the pipeline structure to include ZImageInpaintPipeline
alongside ZImagePipeline and ZImageImg2ImgPipeline.
Implemented the ZImageInpaintPipeline class for inpainting
tasks, including necessary methods for encoding prompts,
preparing masked latents, and denoising.
Enhanced the auto_pipeline to map the new ZImageInpaintPipeline
for inpainting generation tasks.
Added unit tests for ZImageInpaintPipeline to ensure
functionality and performance.
Updated dummy objects to include ZImageInpaintPipeline for
testing purposes.
* Add documentation and improve test stability for ZImageInpaintPipeline
- Add torch.empty fix for x_pad_token and cap_pad_token in test
- Add # Copied from annotations for encode_prompt methods
- Add documentation with usage example and autodoc directive
* Address PR review feedback for ZImageInpaintPipeline
Add batch size validation and callback handling fixes per review,
using diffusers conventions rather than suggested code verbatim.
* Update src/diffusers/pipelines/z_image/pipeline_z_image_inpaint.py
Co-authored-by: Álvaro Somoza <asomoza@users.noreply.github.com>
* Update src/diffusers/pipelines/z_image/pipeline_z_image_inpaint.py
Co-authored-by: Álvaro Somoza <asomoza@users.noreply.github.com>
* Add input validation and fix XLA support for ZImageInpaintPipeline
- Add missing is_torch_xla_available import for TPU support
- Add xm.mark_step() in denoising loop for proper XLA execution
- Add check_inputs() method for comprehensive input validation
- Call check_inputs() at the start of __call__
Addresses PR review feedback from @asomoza.
* Cleanup
---------
Co-authored-by: Álvaro Somoza <asomoza@users.noreply.github.com>
