code: def _forward(self, x):
      branch1x1 = self.branch1x1(x)
  
      branch7x7 = self.branch7x7_1(x)
      branch7x7 = self.branch7x7_2(branch7x7)
      branch7x7 = self.branch7x7_3(branch7x7)
  
      branch7x7dbl = self.branch7x7dbl_1(x)
      branch7x7dbl = self.branch7x7dbl_2(branch7x7dbl)
      branch7x7dbl = self.branch7x7dbl_3(branch7x7dbl)
      branch7x7dbl = self.branch7x7dbl_4(branch7x7dbl)
      branch7x7dbl = self.branch7x7dbl_5(branch7x7dbl)
  
      branch_pool = F.avg_pool2d(x, kernel_size=3, stride=1, padding=1)
      branch_pool = self.branch_pool(branch_pool)
  
      outputs = [branch1x1, branch7x7, branch7x7dbl, branch_pool]
      return outputs
  
imports: from functools import partial
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.data import IMAGENET_DEFAULT_STD, IMAGENET_DEFAULT_MEAN, IMAGENET_INCEPTION_MEAN, IMAGENET_INCEPTION_STD
  from timm.layers import trunc_normal_, create_classifier, Linear, ConvNormAct
  from ._builder import build_model_with_cfg
  from ._builder import resolve_pretrained_cfg
  from ._manipulate import flatten_modules
  from ._registry import register_model, generate_default_cfgs, register_model_deprecations
label_desc: Use image node_id 2 for calling the InceptionC obj's underlying member method code with example usage: obj._forward(x) and returns: outputs