As far as I am aware, pytorch does not have this kind of “map”
function.

However, pytorch supports many different functions that act
element-wise on tensors (arithmetic, cos(), log(), etc.). If you
can rewrite your function using element-wise torch tensor
operations, your composite function will also act element-wise,
and will do what you want.

Numpy provides a way to vectorize a function. Examples for the same makes it very clear and easy to understand. I am not able to find a similar thing in PyTorch. A reference to any of the following would be really helpful:

How to use map() with PyTorch tensors?

Is there any API like np.vectorize?

PS: We want to apply a function f on each element of list of tensors.