Yes, using that old issue implementation saves on the number of parameters but I am not sure is the right way as well as it is basically reshaping the input to be able to apply the module and once applied reshaping to the original shape of the input. so you might lose some temporal information in this way (?) And the purpose of the timedistributed module.
I will train two models using both versions and see which leads to better results or makes more sense