Is possible to make bounding boxe inference from a detectron2 model in ONNX format?

After successful converting my model detectron2 model to ONNX format I cant make predictions.

I am getting the following error:

failed: Fatal error: AliasWithName is not a registered function/op

My code:

import onnx

import onnxruntime as ort
import numpy as np
import glob 
import cv2
onnx_model = onnx.load("test.onnx")

onnx.checker.check_model(onnx_model)


im = cv2.imread('img.png')
print(im.shape)

ort_sess = ort.InferenceSession('test.onnx',providers=[ 'CPUExecutionProvider'])
outputs = ort_sess.run(None, {'input': im})
print(outputs)

I am doing something wrong? In documentation: https://detectron2.readthedocs.io/en/latest/modules/export.html#detectron2.export.Caffe2Tracer.export_onnx They say: "Export the model to ONNX format. Note that the exported model contains custom ops only available in caffe2, therefore it cannot be directly executed by another runtime (such as onnxruntime or TensorRT). Post-processing or transformation passes may be applied on the model to accommodate different runtimes, but we currently do not provide support for them."

What is that "Post-processing or transformation" that I should do?

from Is possible to make bounding boxe inference from a detectron2 model in ONNX format?