code: def forward(self, x, mask_features=None):
      with ExitStack() as stack:
          if self.inference_mode:
              stack.enter_context(torch.no_grad())
  
          c1, _, c3, c4 = self.backbone(x, mask_features)
          c1 = self.skip_project(c1)
  
          x = self.aspp(c4)
          x = F.interpolate(
              x, c1.size()[2:], mode="bilinear", align_corners=True
          )
          x = torch.cat((x, c1), dim=1)
          x = self.head(x)
  
      return (x,)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from contextlib import ExitStack
  from .resnet import ResNetBackbone
  from .basic_blocks import select_activation_function
  from .basic_blocks import SeparableConv2d
label_desc: Use image node_id 4 for calling the DeepLabV3Plus obj's underlying member method code with example usage: obj.forward(x, mask_features) and returns: x