code: def forward(self, x):
      x = self.feature_extractor(x)
  
      detection_feed = [x]
      for l in self.additional_blocks:
          x = l(x)
          detection_feed.append(x)
  
      # Feature Map 38x38x4, 19x19x6, 10x10x6, 5x5x6, 3x3x4, 1x1x4
      locs, confs = self.bbox_view(detection_feed, self.loc, self.conf)
  
      # For SSD 300, shall return nbatch x 8732 x {nlabels, nlocs} results
      return locs, confs
  
imports: import torch
  import torch.nn
  from torchvision.models.resnet import resnet18, resnet34, resnet50, resnet101, resnet152
  from torch.nn.parallel import DistributedDataParallel
label_desc: Use image node_id 5 for calling the SSD300 obj's underlying member method code with example usage: obj.forward(x) and returns: locs,  confs