class_docstr: Down sampler.
  Args:
      in_channels (int): Number of input channels.
      out_channels (int): Number of output channels.
class_docstr_tok: ["Down","sampler",".","Args",":","in_channels","(","int",")",":","Number","of","input","channels",".","out_channels","(","int",")",":","Number","of","output","channels","."]
code: def forward(self, x):
      x = self.conv1(x)
      d1 = self.d_conv1(x)
      d2 = self.d_conv2(x)
      d4 = self.d_conv4(x)
      d8 = self.d_conv8(x)
      d16 = self.d_conv16(x)
  
      feat1 = d2
      feat2 = feat1 + d4
      feat3 = feat2 + d8
      feat4 = feat3 + d16
  
      feat = paddle.concat([d1, feat1, feat2, feat3, feat4], axis=1)
      out = self.bn(feat)
      out = self.act(out)
      return out
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.models import layers
  from paddleseg.cvlibs import manager
  from paddleseg.utils import utils
label_desc: Use image node_id 2 for calling the DownSampler obj's underlying member method code with example usage: obj.forward(x) and returns: out