class_docstr: Dual attention module.
  
  Args:
      in_channels (int): The number of input channels.
      out_channels (int): The number of output channels.
class_docstr_tok: ["Dual","attention","module",".","Args",":","in_channels","(","int",")",":","The","number","of","input","channels",".","out_channels","(","int",")",":","The","number","of","output","channels","."]
code: def forward(self, feats):
      channel_feats = self.channel_conv(feats)
      channel_feats = self.cam(channel_feats)
      channel_feats = self.conv1(channel_feats)
  
      position_feats = self.position_conv(feats)
      position_feats = self.pam(position_feats)
      position_feats = self.conv2(position_feats)
  
      feats_sum = position_feats + channel_feats
      out = self.conv3(feats_sum)
      return out
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.models import layers
label_desc: Use image node_id 2 for calling the DualAttentionModule obj's underlying member method code with example usage: obj.forward(feats) and returns: out