code: def forward(self, tensor_list: NestedTensor):
      xs = self.body(tensor_list.tensors)
      out: Dict[str, NestedTensor] = {}
      for name, x in xs.items():
          m = tensor_list.mask
          assert m is not None
          mask = F.interpolate(m[None].float(), size=x.shape[-2:]).to(
              torch.bool
          )[0]
          out[name] = NestedTensor(x, mask)
      return out
  
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 BackboneBase obj's underlying member method code with example usage: obj.forward(tensor_list) and returns: out