code: def forward(self, tensor_list: NestedTensor):
      xs = self[0](tensor_list)
      out: List[NestedTensor] = []
      pos = []
      for name, x in xs.items():
          out.append(x)
          # position encoding
          pos.append(self[1](x).to(x.tensors.dtype))
  
      return out, pos
  
imports: from collections import OrderedDict
  import torch
  import torch.nn.functional
  import torchvision
  from torch import nn
  from torchvision.models._utils import IntermediateLayerGetter
  from typing import Dict, List
  from util.misc import NestedTensor, is_main_process
  from .position_encoding import build_position_encoding
label_desc: Use image node_id 2 for calling the Joiner obj's underlying member method code with example usage: obj.forward(tensor_list) and returns: out,  pos