class_docstr: A portal for a tensor.
class_docstr_tok: ["A","portal","for","a","tensor","."]
docstr: Creates a :class:`PortalOrange` which retrieves the hidden tensor
  without losing ability of backpropagation.
  
  Give a phony forked from the main lane of an autograd graph::
  
          +-- PortalOrange --+
          |                  |
      -- Fork --------- f(a, b) --
docstr_tok: ["Creates","a",":","class",":","`","PortalOrange","`","which","retrieves","the","hidden","tensor","without","losing","ability","of","backpropagation",".","Give","a","phony","forked","from","the","main","lane","of","an","autograd","graph",":",":","+","--","PortalOrange","--","+","|","|","--","Fork","--","--","--","--","-","f","(","a",",","b",")","--"]
code: def orange(self, phony: Tensor) -> Optional[Tensor]:
      """Creates a :class:`PortalOrange` which retrieves the hidden tensor
      without losing ability of backpropagation.
  
      Give a phony forked from the main lane of an autograd graph::
  
              +-- PortalOrange --+
              |                  |
          -- Fork --------- f(a, b) --
  
      """
      self.check_tensor_life()
  
      if self.tensor is None:
          return self.use_tensor()
  
      return PortalOrange.apply(self, phony)
  
imports: from typing import Any, List, Optional, Tuple
  import torch
  from torch import Tensor
  from .None import Namespace
  from ..copy import Context
  from ..copy import Copy
  from ..phony import get_phony
  from ..stream import AbstractStream, get_device
label_desc: Use image node_id 4 for calling the Portal obj's underlying member method code with example usage: obj.orange(phony) and returns: PortalOrange, self