code: def forward(self, x):
      res2, res3, res4, res5 = x
  
      mla_p5_1x1 = self.mla_p5_1x1(res5)
      mla_p4_1x1 = self.mla_p4_1x1(res4)
      mla_p3_1x1 = self.mla_p3_1x1(res3)
      mla_p2_1x1 = self.mla_p2_1x1(res2)
  
      mla_p4_plus = mla_p5_1x1 + mla_p4_1x1
      mla_p3_plus = mla_p4_plus + mla_p3_1x1
      mla_p2_plus = mla_p3_plus + mla_p2_1x1
  
      mla_p5 = self.mla_p5(mla_p5_1x1)
      mla_p4 = self.mla_p4(mla_p4_plus)
      mla_p3 = self.mla_p3(mla_p3_plus)
      mla_p2 = self.mla_p2(mla_p2_plus)
  
      return [mla_p2, mla_p3, mla_p4, mla_p5]
  
imports: import paddle.nn
  import paddle.nn.functional
  import paddle
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.models import layers
  from paddleseg.utils import utils
label_desc: Use image node_id 2 for calling the ConvMLA obj's underlying member method code with example usage: obj.forward(x) and returns: list