code: def __init__(self, in_channels, out_channels, norm_layer, **kwargs):
      super(_GlobalAvgPooling, self).__init__()
      self.gap = nn.Sequential(
          nn.AdaptiveAvgPool2d(1),
          nn.Conv2d(in_channels, out_channels, 1, bias=False),
          norm_layer(out_channels),
          nn.ReLU(True),
      )
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from pywick.models.segmentation.da_basenets.resnet import resnet18
label_desc: Use image node_id 1 to create a new _GlobalAvgPooling object from inherited base classes: nn with example: obj = _GlobalAvgPooling(in_channels, out_channels, norm_layer)