Would writing a decision tree algorithm in Pytorch or Tensorflow be faster than with Numpy?

Since these libraries can turn CPU arrays into GPU tensors, could you parallelize (and therefore accelerate) the calculations for a decision tree? I am considering making a decision tree class written in Tensorflow/Pytorch for a school project, but I want to be certain that it makes sense.