OneFormer-ADE20K-SemSegPreprocessor on MPS - cannot convert a MPS Tensor to float64 dtype

[Gabled-Waters]

Trying to use the OneFormer-ADE20K-SemSegPreprocessor or COCO-Segmentor on MPS fails with

"Cannot convert a MPS Tensor to float64 dtype as the MPS framework doesn't support float64. Please use float32 instead."
I looked into this and AI suggested to pin this to CPU when running on MPS, as I did not want to mess around with the dtypes (no significant impact in overall processing time when I use CPU).

I used a very quick n dirty fix in oneformer.py. I'm not sure if this really fixes the issue as alibaba-pai/Z-Image-Turbo-Fun-Controlnet-Union-2.1 doesn't seem to understand the segmentation map which resulted after this fix, but maybe it's a starting point.

from ..utils import common_annotator_call, define_preprocessor_inputs, INPUT
import comfy.model_management as model_management

class OneFormer_COCO_SemSegPreprocessor:
    @classmethod
    def INPUT_TYPES(s):
        return define_preprocessor_inputs(resolution=INPUT.RESOLUTION())

    RETURN_TYPES = ("IMAGE",)
    FUNCTION = "semantic_segmentate"

    CATEGORY = "ControlNet Preprocessors/Semantic Segmentation"

    def semantic_segmentate(self, image, resolution=512):
        from custom_controlnet_aux.oneformer import OneformerSegmentor

        model = OneformerSegmentor.from_pretrained(filename="150_16_swin_l_oneformer_coco_100ep.pth")

##        original
#        model = model.to(model_management.get_torch_device())

        import torch
        from comfy import model_management
        model = model.to(torch.device("cpu"))

        out = common_annotator_call(model, image, resolution=resolution)
        del model
        return (out,)