code: def __init__(self, in_channels, out_channels):
      super(SEB, self).__init__()
      self.conv = nn.Conv2d(
          in_channels, out_channels, kernel_size=3, stride=1, padding=1
      )
      self.upsample = nn.Upsample(scale_factor=2, mode="bilinear")
  
file_path: pywick/pywick/models/segmentation/testnets/lg_kernel_exfuse/large_kernel_exfuse.py
imports: import torch
  from torch import nn
  from .deeplab_resnet import ModelBuilder
  from .large_kernel import _GlobalConvModule
label_desc: Use image node_id 1 to create a new SEB object from inherited base classes: nn with example: obj = SEB(in_channels, out_channels)