code: def forward_features(self, x):
      x = self.layer0(x)
      x = self.pool0(x)
      x = self.layer1(x)
      x = self.layer2(x)
      x = self.layer3(x)
      x = self.layer4(x)
      return x
  
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 7 for calling the SENet obj's underlying member method code with example usage: obj.forward_features(x) and returns: x