class_docstr: The auxiliary layer implementation for auxiliary loss.
  
  Args:
      in_channels (int): The number of input channels.
      inter_channels (int): The intermediate channels.
      out_channels (int): The number of output channels, and usually it is num_classes.
      dropout_prob (float, optional): The drop rate. Default: 0.1.
code: def __init__(
      self,
      in_channels: int,
      inter_channels: int,
      out_channels: int,
      dropout_prob: float = 0.1,
      **kwargs,
  ):
      super().__init__()
  
      self.conv_bn_relu = ConvBNReLU(
          in_channels=in_channels,
          out_channels=inter_channels,
          kernel_size=3,
          padding=1,
          **kwargs,
      )
  
      self.dropout = nn.Dropout(p=dropout_prob)
  
      self.conv = nn.Conv2D(
          in_channels=inter_channels,
          out_channels=out_channels,
          kernel_size=1,
      )
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle.nn.layer import activation
  from paddle.nn import Conv2D, AvgPool2D
label_desc: Use image node_id 1 to create a new AuxLayer object from inherited base classes: nn with example: obj = AuxLayer(in_channels, inter_channels, out_channels, dropout_prob)