code: def test_dilated_encoder():
      in_channels = 16
      out_channels = 32
      out_shape = 34
      dilated_encoder = DilatedEncoder(
          in_channels, out_channels, 16, 2, [2, 4, 6, 8]
      )
      feat = [torch.rand(1, in_channels, 34, 34)]
      out_feat = dilated_encoder(feat)[0]
      assert out_feat.shape == (1, out_channels, out_shape, out_shape)
  
file_path: mmdetection/tests/test_models/test_necks/test_necks.py
imports: import pytest
  import torch
  from torch.nn.modules.batchnorm import _BatchNorm
  from mmdet.models.necks import FPG, FPN, FPN_CARAFE, NASFCOS_FPN, NASFPN, SSH, YOLOXPAFPN, ChannelMapper, DilatedEncoder, DyHead, SSDNeck, YOLOV3Neck
label_desc: Use image node_id 3 for calling a global function with example usage: test_dilated_encoder() without return types