I have a pretrained model built by a colleague. I have an identical model (network architecure) that I built and trained myself. By identical I mean the model summaries are the same, they have exactly the same number of trainable and non-trainable variables. I can load weights interchangebly between the 2 models.
Weirdly the variables file, in their model is about 50% of the size of mine. If I load and save their model the weights file remains the same (50%).
Possibly related, the performance of my model sucks compared to the pretrained model.
Any idea how 2 identical models can have weights files of different sizes?
Turns out we used different optimizers. Optimizer state is stored with the model network and weights.