ONNX Inferencing Error about sparseinst_tensorrt HOT 3 CLOSED

Done!!
I solved it by converting the array to double then float rather than 1e-6. Not sure why 1e-6 was mapped to double no matter what I do.
My solution:

@torch.jit.script
def rescoring_mask(scores, mask_pred, masks):
    mask_pred_ = mask_pred.float()
    factrr = mask_pred_.sum([1, 2]).double()
    factrr = factrr + 1e-6
    return scores * ((masks * mask_pred_).sum([1, 2]) / factrr.float())

from sparseinst_tensorrt.

Dear @mohamadmansourX, thank you for saying that 😉
Would you mind sharing your ONNX file with me? Such that I can check it out on netron with the verbose output.

On my ONNX, the last Add node I have a the Add_319 which is link to the "rescoring_mask" definition in the sparseinst.py, called line 229. If it is the case, you should be able to change line 21 which define mask_pred_ as a float that could possibily be converted to double.
Let's see from where your Add_398 comes from ...

from sparseinst_tensorrt.

Hello, thank you for your reply.
Yeah as you mentioned, after debugging with netron, the issue is in this line:

Adding the terms mask_pred_.sum([1, 2]) and 1e-6 is causing that issue.
Tried changing 1e-6 to torch.tensor(1e-6).float() but for some reason it's still being interpreted as a tensor(double)!

from sparseinst_tensorrt.