class_docstr: A Tensor subclass of uint8 dtype, that represents Tensor with X-bit elements.
  The last dimension must be divisible by (8 // X).
  
  __torch_dispatch__ special handling:
  .view(dtype=torch.uint8) - returns the underlying uint8 data.
  
  .slice,.view - works in UIntX units, dimension values must be divisible by (8 // X).
  
  .detach,.clone - work as an op on underlying uint8 data.
code: def __new__(cls, N, elem):
      assert elem.dtype is torch.uint8
      # pyre-ignore
      return torch.Tensor._make_wrapper_subclass(
          cls, up_size(N, elem.shape), dtype=torch.uint8
      )
  
imports: import itertools
  from typing import List, Tuple
  import torch
  import torch._prims_common
label_desc: Use image node_id 1 for calling the UIntXTensor obj's underlying member method code with example usage: obj.__new__(cls, N, elem) and returns: torch