Evaluation of the model after training

once a model is trained in Modulus, how can I evaluate the results for a range of inputs? I’m expecting to get the outputs instantaneously without running the simulations.

Hi @smraniaki

There are a couple of ways, the first “Modulus workflow” approach is using the evaluate mode built into the solver: solver.eval(). This will just run any inferencer / validators you’ve added. See the _eval function in the trainer: https://gitlab.com/nvidia/modulus/modulus/-/blob/release_22.09/modulus/trainer.py#L749

Alternatively you could look at loading the model checkpoint manually using a Modulus model. This checkpoint is saved in the outputs folder of your run. Then running inference manually in a typical PyTorch method:

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