code: def forward(self, x):
      # initial convolutional block:
      out = self.initial_block(x)
  
      # evaluate all residual blocks:
      # TODO: (kaizh) T43794289 exit early if there is no block that has heads
      out = self.blocks(out)
  
      return out
  
imports: import copy
  import math
  import re
  import warnings
  from collections import OrderedDict
  from typing import Any, Dict, Optional, Sequence
  import torch.nn
  from classy_vision.generic.util import is_pos_int, is_pos_int_tuple
  from .None import register_model
  from .classy_model import ClassyModel
  from .squeeze_and_excitation_layer import SqueezeAndExcitationLayer
label_desc: Use image node_id 6 for calling the ResNeXt obj's underlying member method code with example usage: obj.forward(x) and returns: out