torch.Tensor.resize_
Tensor.resize_(*sizes, memory_format=torch.contiguous_format) -> Tensor
Resizes "self" tensor to the specified size. If the number of
   elements is larger than the current storage size, then the
   underlying storage is resized to fit the new number of elements. If
   the number of elements is smaller, the underlying storage is not
   changed. Existing elements are preserved but any new memory is
   uninitialized.
Warning:
 This is a low-level method. The storage is reinterpreted as
 C-contiguous, ignoring the current strides (unless the target
 size equals the current size, in which case the tensor is left
 unchanged). For most purposes, you will instead want to use
 "view()", which checks for contiguity, or "reshape()", which
 copies data if needed. To change the size in-place with custom
 strides, see "set_()".

Parameters:
      * sizes (torch.Size or int...) -- the desired size