code: def forward(self, tensor_list: NestedTensor):
      xs = self.body(tensor_list.tensors)
      out = OrderedDict()
      for name, x in xs.items():
          mask = F.interpolate(
              tensor_list.mask[None].float(), size=x.shape[-2:]
          ).bool()[0]
          out[name] = NestedTensor(x, mask)
      return out
  
imports: import math
  from collections import OrderedDict
  import torch
  import torch.nn.functional
  import torchvision
  from mmf.models.unit.misc import NestedTensor
  from torch import nn
  from torchvision.models._utils import IntermediateLayerGetter
  from torchvision.ops.misc import FrozenBatchNorm2d
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