code: def forward(self, inputs):
      x, x_m, y = inputs
      out = self.conv1(x)
      out = F.relu(out)
      out = F.max_pool2d(out, 2, ceil_mode=True)
      out = self.dense1(out)
      out = self.trans1(out)
      out = self.dense2(out)
      out = self.trans2(out)
      out = self.dense3(out)
      return out, x_m, y
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import paddle
  import paddle.nn
  import paddle.nn.functional
label_desc: Use image node_id 3 for calling the DenseNet obj's underlying member method code with example usage: obj.forward(inputs) and returns: out,  x_m,  y