Fix wrong variable in multi-ControlNet check_inputs#14156
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In pipeline_controlnet_img2img.py and pipeline_controlnet_inpaint.py, the multi-ControlNet branch of check_inputs() was checking the `image` variable (the input image) where it should check `control_image` (the ControlNet conditioning image). This caused incorrect type/length validation against the wrong variable. Fix by: - Adding `control_image` as a new parameter to check_inputs() in both files - Updating the multi-ControlNet branch to use `control_image` instead of `image` - Updating the self.check_inputs() call sites to pass `image` and `control_image` as separate arguments Fixes huggingface#14057
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What does this PR fix?
Fixes #14057.
In
pipeline_controlnet_img2img.pyandpipeline_controlnet_inpaint.py, the multi-ControlNet branch ofcheck_inputs()was referencing theimagevariable (the input image) where it should referencecontrol_image(the ControlNet conditioning image). This caused type/length validation to run against the wrong variable when usingMultiControlNetModel.Changes
control_imageas a new parameter tocheck_inputs()in both files.control_imageinstead ofimage, including updating theTypeError/ValueErrormessages to name the correct parameter.self.check_inputs()call sites to passimage(the input image) andcontrol_image(the ControlNet conditioning image) as separate arguments, so each variable is checked against the right input.The single-ControlNet branch is unchanged — it continues to validate
imageas before.