code: def _forward(self, x: Tensor) -> List[Tensor]:
      branch3x3 = self.branch3x3(x)
  
      branch3x3dbl = self.branch3x3dbl_1(x)
      branch3x3dbl = self.branch3x3dbl_2(branch3x3dbl)
      branch3x3dbl = self.branch3x3dbl_3(branch3x3dbl)
  
      branch_pool = F.max_pool2d(x, kernel_size=3, stride=2)
  
      outputs = [branch3x3, branch3x3dbl, branch_pool]
      return outputs
  
imports: import warnings
  from collections import namedtuple
  from functools import partial
  from typing import Any, Callable, List, Optional, Tuple
  import torch
  import torch.nn.functional
  from torch import nn, 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 2 for calling the InceptionB obj's underlying member method code with example usage: obj._forward(x) and returns: outputs