code: def __init__(self, in_chan, out_chan):
      super(AttentionRefinementModule, self).__init__()
      self.conv = layers.ConvBNReLU(
          in_chan, out_chan, kernel_size=3, stride=1, padding=1
      )
      self.conv_atten = nn.Conv2D(
          out_chan, out_chan, kernel_size=1, bias_attr=None
      )
      self.bn_atten = nn.BatchNorm2D(out_chan)
      self.sigmoid_atten = nn.Sigmoid()
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg import utils
  from paddleseg.models import layers
  from paddleseg.cvlibs import manager
  from paddleseg.utils import utils
label_desc: Use image node_id 1 to create a new AttentionRefinementModule object from inherited base classes: nn with example: obj = AttentionRefinementModule(in_chan, out_chan)