code: def __init__(self, channels, reduction):
      super(SEModule, self).__init__()
      self.fc1 = nn.Conv2d(
          channels, channels // reduction, kernel_size=1
      )
      self.relu = nn.ReLU(inplace=True)
      self.fc2 = nn.Conv2d(
          channels // reduction, channels, kernel_size=1
      )
      self.sigmoid = nn.Sigmoid()
  
imports: import math
  from collections import OrderedDict
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import create_classifier
  from ._builder import build_model_with_cfg
  from ._registry import register_model, generate_default_cfgs
label_desc: Use image node_id 1 to create a new SEModule object from inherited base classes: nn with example: obj = SEModule(channels, reduction)