fix: Handle NaN values during weight conversion

[tgaddair]

Fixes #81.

Solution proposed by @asingh9530 .

[arnavgarg1]

Nice! LGTM, thanks for putting this together @tgaddair! Is it also worth adding special error checking if the weights have Inf (I know this is super rare and really only can happen when training without regularization measures in place)?

[asingh9530]

@tgaddair looks good but not sure if nesting conditions would be right choice as if for any reason we in future it requires to add more check it would start becoming cluttered.

[tgaddair]

@asingh9530 it's a good point. My reason for doing it this way was to save the computation cost of calling torch.any(torch.isnan)) in cases where we know the weights are not nan. Not sure how much of an impact this will have in practice. Happy to go with an alternative if you feel there's a better place for this check!

[asingh9530]

@tgaddair how about using a validatorTensor method and it takes care of validating tensors and then we can add validation conditions much neatly there. Let me know I can add in this PR as adding internal methods like validation or convert makes a huge difference in maintaining

[tgaddair]

Hey @asingh9530, that sounds good! I can go ahead and merge this PR for now and then you can create a follow-up PR, if that works.