code: def __init__(self, channel, reduction=16):
      super(ChannelAttentionGate, self).__init__()
      self.avg_pool = nn.AdaptiveAvgPool2d(1)
      self.fc = nn.Sequential(
          nn.Linear(channel, channel // reduction),
          nn.ReLU(inplace=True),
          nn.Linear(channel // reduction, channel),
          nn.Sigmoid(),
      )
  
imports: from torch import nn
  from torch.nn import functional
  import torch
  from torchvision import models
  from torchvision.models import resnet34, resnet101, resnet50, resnet152
  import torchvision
label_desc: Use image node_id 1 to create a new ChannelAttentionGate object from inherited base classes: nn with example: obj = ChannelAttentionGate(channel, reduction)