Parallel way of applying function element-wise to a Pytorch CUDA Tensor
Suppose I have a torch CUDA tensor and I want to apply some function like sin() but I have explicitly defined the function F. How can I use parallel computation to apply F in Pytorch.

I think currently, it is not possible to explicit parallelize a function on a CUDA-Tensor. A possible solution could be, you can define a Function like the for example the non-linear activation functions. So you can feed forward it through the Net and your function. 

The drawback is, it probably don't work, because you have to define a CUDA-Function and have to recompile pytorch.
