Just a question...

[vladBaciu]

Can custom models and datasets be used easily on this project ?

I am wondering if I can evaluate a custom model on a custom dataset that is not publicly available. If yes, could you give me some hints ?

[PhilippvK]

The model zoo we provide is entirely optional. There are a few ways to use your own models instead

• Just pass a relative/absolute path to the model file to the mlonmch flow ... command.
• Add your model you the user-level model directory, e.g. `~/.config/mlonmcu/models"
• Extend the model lookup paths in your environment.yml with any custom directories like this:

  paths:
  models:
  - "/work/git/mlonmcu/models"
  - "/home/ga87puy/.config/mlonmcu/models"
  - "/path/to/model/zoo"

The only limitation is that your model type has to be supported by one of mlonmcus frontends.

Regarding datasets: Since mlonmcu is only working with pre-trained models, it does not really care about datasets. The only case when the data becomes relevant is when validation the model outputs against a golden reference. This feature is supported by MLonMCU (see https://github.com/tum-ei-eda/mlonmcu/blob/main/ipynb/Examples/ValidateOutputs.ipynb) but we are currently working on a more sophisticated solution for model output verification...

I hope this answers your question!