code: def eager_outputs(
      self, x: Tensor, aux2: Tensor, aux1: Optional[Tensor]
  ) -> GoogLeNetOutputs:
      if self.training and self.aux_logits:
          return _GoogLeNetOutputs(x, aux2, aux1)
      else:
          return x
  
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 4 for calling the GoogLeNet obj's underlying member method code with example usage: obj.eager_outputs(x, aux2, aux1) and returns: _GoogLeNetOutputs, x