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 __init__(self, N: int, elem: torch.Tensor) -> None:
      self.N: int = N
      self.elem: torch.Tensor = elem
  
imports: import itertools
  from typing import List, Tuple
  import torch
  import torch._prims_common
label_desc: Use image node_id 2 to create a new UIntXTensor object from inherited base classes: torch with example: obj = UIntXTensor(N, elem)