code: def _forward(self, x: Tensor) -> Tuple[Tensor, Optional[Tensor]]:
      # N x 3 x 299 x 299
      x = self.Conv2d_1a_3x3(x)
      # N x 32 x 149 x 149
      x = self.Conv2d_2a_3x3(x)
      # N x 32 x 147 x 147
      x = self.Conv2d_2b_3x3(x)
      # N x 64 x 147 x 147
      x = self.maxpool1(x)
      # N x 64 x 73 x 73
      x = self.Conv2d_3b_1x1(x)
      # N x 80 x 73 x 73
      x = self.Conv2d_4a_3x3(x)
      # N x 192 x 71 x 71
      x = self.maxpool2(x)
      # N x 192 x 35 x 35
      x = self.Mixed_5b(x)
      # N x 256 x 35 x 35
      x = self.Mixed_5c(x)
      # N x 288 x 35 x 35
      x = self.Mixed_5d(x)
      # N x 288 x 35 x 35
      x = self.Mixed_6a(x)
      # N x 768 x 17 x 17
      x = self.Mixed_6b(x)
      # N x 768 x 17 x 17
      x = self.Mixed_6c(x)
      # N x 768 x 17 x 17
      x = self.Mixed_6d(x)
      # N x 768 x 17 x 17
      x = self.Mixed_6e(x)
      # N x 768 x 17 x 17
      aux: Optional[Tensor] = None
      if self.AuxLogits is not None:
          if self.training:
              aux = self.AuxLogits(x)
      # N x 768 x 17 x 17
      x = self.Mixed_7a(x)
      # N x 1280 x 8 x 8
      x = self.Mixed_7b(x)
      # N x 2048 x 8 x 8
      x = self.Mixed_7c(x)
      # N x 2048 x 8 x 8
      # Adaptive average pooling
      x = self.avgpool(x)
      # N x 2048 x 1 x 1
      x = self.dropout(x)
      # N x 2048 x 1 x 1
      x = torch.flatten(x, 1)
      # N x 2048
      x = self.fc(x)
      # N x 1000 (num_classes)
      return x, aux
  
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 3 for calling the Inception3 obj's underlying member method code with example usage: obj._forward(x) and returns: x,  aux