class_docstr: Channel Squeeze module
code: def __init__(self, channels):
      super().__init__()
      self.squeeze = nn.Conv2d(channels, 1, kernel_size=1, padding=0)
  
imports: from torch import nn, Tensor
  from torch.nn import functional
label_desc: Use image node_id 1 to create a new ChannelGate2d object from inherited base classes: nn with example: obj = ChannelGate2d(channels)