Pytorch is easier to read and write and there are more resources for it. Tensorflow is easier to deploy and (sometimes) more performant.

Although Pytorch 2.0 is in testing and should be out soon. It makes up for whatever performance gap there is between the two apparently.

Regarding model performance it probably doesn't matter which one you choose, but looking at how your LSTM formulation of the solution is just plain wrong, Pytorch will be easier to use for more complex networks, although in practice to fully utilize resources you need to know both.