code: def encrypt_encoded(
      self, tensor: "PHETensorEncoded", obfuscate=False
  ):
      from ._tensor import PHETensor, PHETensorEncoded
  
      if isinstance(tensor, PHETensorEncoded):
          data = self._pk.encrypt_encoded(tensor.data, obfuscate)
          return PHETensor(
              self._pk,
              self._evaluator,
              tensor.coder,
              tensor.shape,
              data,
              tensor.dtype,
              tensor.device,
          )
      elif hasattr(tensor, "encrypt_encoded"):
          return tensor.encrypt_encoded(self)
      raise NotImplementedError(f"`{tensor}` not supported")
  
imports: import typing
  import torch
label_desc: Use image node_id 2 for calling the PHETensorEncryptor obj's underlying member method code with example usage: obj.encrypt_encoded(tensor, obfuscate) and returns: PHETensor, tensor