Consistency of Bilinear Upsampling Layer

It is well known among deep-learning manias that bilinear upsampling layers in TensorFlow have pixel-offset issues. This has been partly fixed by adding an'align_corner' attribute to them in TensorFlow 2.x. But the problem remains to cause inconsistent computation flow when exporting a trained model in TensorFlow into another DL framework through various versions. In my case, a neural network model with bilinear upsampling layers showed weird behavior when converting the trained model from TensorFlow 2.5 to Apple Core ML by using coremltools 3.4. After uncountable coding, trials, and delete-delete-delete, I nearly gave up the consistent results of the upsampling layer between TensorFlow and Core ML.