code: def __torch_function__(cls, func, types, args=(), kwargs=None):
      if kwargs is None:
          kwargs = {}
      if func not in _PHE_TENSOR_ENCODED_HANDLED_FUNCTIONS or not all(
          issubclass(t, (torch.Tensor, PHETensorEncoded)) for t in types
      ):
          return NotImplemented
      return _PHE_TENSOR_ENCODED_HANDLED_FUNCTIONS[func](
          *args, **kwargs
      )
  
imports: import functools
  import torch
  from fate.arch.trace import auto_trace
label_desc: Use image node_id 2 for calling the PHETensorEncoded obj's underlying member method code with example usage: obj.__torch_function__(cls, func, types, args, kwargs) and returns: _PHE_TENSOR_ENCODED_HANDLED_FUNCTIONS, NotImplemented