Say we have a one-to-one (total) function $f:\mathbb{N}\to\mathbb{N}$ and a Turing-machine $T_f$ that computes it. Suppose further that $T_f$ runs in polynomial time wrt. length of the input.
Are there functions $f$ that are computable in polynomial time but whose inverse is known not to be computable in polynomial time?
Does the situation change if we drop the one-to-one requirement and define the inverse as, say, min$(f^{-1})$? How about if we change the complexity class in question?