code: def forward(self, x):
      outputs = self._forward(x)
      return torch.cat(outputs, 1)
  
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 3 for calling the InceptionE obj's underlying member method code with example usage: obj.forward(x) and returns: torch