I really want to know that in Pytorch, functions such like view(), permute(), contiguous() operate the Tensor in-place or they will allocate new memory block to store the result.
Recently, I encounter that my data needs lot of memory, so I need to reduce memory usage in the forward process, and knowing the answer of the question above is of great help.
Thanks a lot