code: def forward(self, features: List[Tensor]):  # skipcq: PYL-W0221
      layers = []
      dst_size = features[0].size()[
          2:
      ]  # Skip B, C, and use rest (This works for 1D, 2D, 3D and ND..)
  
      for f in features:
          layers.append(
              F.interpolate(
                  f,
                  size=dst_size,
                  mode=self.mode,
                  align_corners=self.align_corners,
              )
          )
  
      return torch.cat(layers, dim=1)
  
imports: from __future__ import absolute_import
  from typing import List
  import torch
  from torch import nn, Tensor
  from torch.nn import functional
  from ..modules.activations import ABN
label_desc: Use image node_id 2 for calling the FPNFuse obj's underlying member method code with example usage: obj.forward(features) and returns: torch