These kinds of type reinterpretations are an important building block for implementing special functions. It’s quite common to switch from float to integer, do a few manipulations there (e.g. of the mantissa), and then switch back to floats in the end.  In the NumPy world, np.view is the operation that enables one to do that. AFAIK it’s not possible with PyTorch. There is no analog of np.view as far as I can see, and directly assigning the dtype yields an error message:
>>> t.dtype = torch.int32
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: attribute 'dtype' of 'torch._C._TensorBase' objects is not writable

Or do you have any suggestions?