Load and save model in gluon

Newbie question. How can I save and model in gluon?
The tutorials:
https://gluon.mxnet.io/chapter03_deep-neural-networks/serialization.html


We have to separate the definition of the neural network from the params. This could cause unnecessary inconsistency between the model and the params.

Why does MXNet have to do it in such a convoluted way?

Hi @xinwang-issaquah,

I see it as different files are used to store semantically different types of data. With a single file for the architecture it’s simple and efficient to share and use visualisation tools (like https://lutzroeder.github.io/Netron/). I understand your argument for consistency though, and to ensure consistency of these two components, MXNet will give you warnings/errors if you try to load weights onto a incompatible model. So that you still have flexibility, you can disable the warnings/errors with the following two arguments of load_parameters:

  • allow_missing ( bool , default False ) – Whether to silently skip loading parameters not represents in the file.
  • ignore_extra ( bool , default False ) – Whether to silently ignore parameters from the file that are not present in this Block.