code: def forward_features(self, x):
      x = self.base_layer(x)
      x = self.level0(x)
      x = self.level1(x)
      x = self.level2(x)
      x = self.level3(x)
      x = self.level4(x)
      x = self.level5(x)
      return x
  
imports: import math
  from typing import List, Optional
  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 DLA obj's underlying member method code with example usage: obj.forward_features(x) and returns: x