code: def __init__(
      self, in_channels, inter_channels, out_channels, lr_mult
  ):
      super().__init__()
      self.bn1 = bn2d(in_channels, lr_mult=lr_mult)
      self.conv1 = conv2d(
          in_channels,
          inter_channels,
          kernel_size=3,
          padding=1,
          lr_mult=lr_mult,
      )
      self.bn2 = bn2d(inter_channels, lr_mult=lr_mult)
      self.relu = nn.ReLU()
      self.conv2 = conv2d(
          inter_channels,
          out_channels,
          kernel_size=1,
          padding=0,
          bias_attr=True,
          lr_mult=lr_mult,
      )
  
imports: from functools import partial
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.models import layers
  from paddleseg.utils import utils
  from paddleseg.models.backbones.transformer_utils import DropPath, Identity
  from paddleseg.cvlibs.param_init import constant_init, kaiming_normal_init, trunc_normal_init
label_desc: Use image node_id 1 to create a new SegHead object from inherited base classes: nn with example: obj = SegHead(in_channels, inter_channels, out_channels, lr_mult)