code: def forward(self, x: Tensor) -> GoogLeNetOutputs:
      x = self._transform_input(x)
      x, aux1, aux2 = self._forward(x)
      aux_defined = self.training and self.aux_logits
      if torch.jit.is_scripting():
          if not aux_defined:
              warnings.warn(
                  "Scripted GoogleNet always returns GoogleNetOutputs Tuple"
              )
          return GoogLeNetOutputs(x, aux2, aux1)
      else:
          return self.eager_outputs(x, aux2, aux1)
  
imports: import warnings
  from collections import namedtuple
  from functools import partial
  from typing import Any, Callable, List, Optional, Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from torch import Tensor
  from ..transforms._presets import ImageClassification
  from ..utils import _log_api_usage_once
  from ._api import register_model, Weights, WeightsEnum
  from ._meta import _IMAGENET_CATEGORIES
  from ._utils import _ovewrite_named_param, handle_legacy_interface
label_desc: Use image node_id 5 for calling the GoogLeNet obj's underlying member method code with example usage: obj.forward(x) and returns: GoogLeNetOutputs, self