This is really interesting! This behavior is consistent with NumPy's pad, but @saketh-are and I were surprised that np.pad did this. That is, trying to pad an integer array by 1.5 result in padding it by 1! It seems divergent from NumPy's typical type promotion.    Should we preserve this behavior or maybe throw an error if the constant value isn't representable in the tensor's datatype, @kurtamohler?    cc @rgommers to see if he has some context on pad's (lack of) type promotion