AttributeError: 'Block' object has no attribute 'drop_path' about multi-subject-render HOT 4 OPEN

Having the exact same issue & haven't been able to solve it yet, would be nice if someone could chime in to tell us noobs what we're doing wrong, or if it's just broken lol

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ouch I'm not using A1111 anymore and right now I'm not sure what went wrong. I'm sorry that you guys can't use it. I will take a look into it during the upcoming month if possible!

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It does function with the Midas model, although I can not get a suitable image out of it, but the script appears to be broken with the other models.

from multi-subject-render.

Changing the lines of code at :
automatic1111\repositories\midas\midas\backbones\beit.py", line 102, in block_forward -

FROM

        x = x + self.drop_path(self.attn(self.norm1(x), resolution, shared_rel_pos_bias=shared_rel_pos_bias))
        x = x + self.drop_path(self.mlp(self.norm2(x)))
    else:
        x = x + self.drop_path(self.gamma_1 * self.attn(self.norm1(x), resolution,
                                                        shared_rel_pos_bias=shared_rel_pos_bias))
        x = x + self.drop_path(self.gamma_2 * self.mlp(self.norm2(x)))

TO:

        x = x + self.drop_path1(self.attn(self.norm1(x), resolution, shared_rel_pos_bias=shared_rel_pos_bias))
        x = x + self.drop_path2(self.mlp(self.norm2(x)))
    else:
        x = x + self.drop_path1(self.gamma_1 * self.attn(self.norm1(x), resolution,
                                                        shared_rel_pos_bias=shared_rel_pos_bias))
        x = x + self.drop_path2(self.gamma_2 * self.mlp(self.norm2(x)))

(manually adding path#s is really all.)

Seems to brute force a fix
however, it seems the brute forcing of it this way causes a memory leak as it will go from successful runs, to OOM exceptions immediately before it even renders 1 pre-image.

I honestly don't know a lot of python, just know how to follow traces and stacks while guessing syntax along the way, so no idea if the changes made are just bad, or if this is close to a solution or not.

another thought:
This is in the beit.py file, the model for midas beit, that is 512 (the big one.) perhaps changing to a different model (swin2) will resolve? thats on my todo at least if I cannot resolve beit.

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