code: def __init__(self, in_channels, mla_channels):
      super().__init__()
  
      self.mla_p2_1x1 = layers.ConvBNReLU(
          in_channels=in_channels,
          out_channels=mla_channels,
          kernel_size=1,
      )
  
      self.mla_p3_1x1 = layers.ConvBNReLU(
          in_channels=in_channels,
          out_channels=mla_channels,
          kernel_size=1,
      )
  
      self.mla_p4_1x1 = layers.ConvBNReLU(
          in_channels=in_channels,
          out_channels=mla_channels,
          kernel_size=1,
      )
  
      self.mla_p5_1x1 = layers.ConvBNReLU(
          in_channels=in_channels,
          out_channels=mla_channels,
          kernel_size=1,
      )
  
      self.mla_p2 = layers.ConvBNReLU(
          in_channels=mla_channels,
          out_channels=mla_channels,
          kernel_size=3,
          padding=1,
      )
  
      self.mla_p3 = layers.ConvBNReLU(
          in_channels=mla_channels,
          out_channels=mla_channels,
          kernel_size=3,
          padding=1,
      )
  
      self.mla_p4 = layers.ConvBNReLU(
          in_channels=mla_channels,
          out_channels=mla_channels,
          kernel_size=3,
          padding=1,
      )
  
      self.mla_p5 = layers.ConvBNReLU(
          in_channels=mla_channels,
          out_channels=mla_channels,
          kernel_size=3,
          padding=1,
      )
  
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 1 to create a new ConvMLA object from inherited base classes: nn with example: obj = ConvMLA(in_channels, mla_channels)