Thanks for responding @tensoralex
Actually, I was using similar function from rossman nb as reference when it threw the mentioned error.
So, I think this is just the accuracy metric for printing and loss function is defined in StructuredLearner which is called when we use get_learner in rossman nb.
class StructuredLearner(Learner): def __init__(self, data, models, **kwargs): super().__init__(data, models, **kwargs) **self.crit = F.mse_loss**
As we see here, it is using F.mse_loss which is inbuilt functional form for mse. I couldn’t find F.myloss() for equirectangular distance (loss I need to use). So, I guess loss function should have forward and backward capability as in F.loss() and we might have to build a class for it. But I found pytorch forums confusing 