code: def __init__(
      self,
      in_channels: int,
      num_classes: int,
      conv_block: Optional[Callable[..., nn.Module]] = None,
      dropout: float = 0.7,
  ) -> None:
      super().__init__()
      if conv_block is None:
          conv_block = BasicConv2d
      self.conv = conv_block(in_channels, 128, kernel_size=1)
  
      self.fc1 = nn.Linear(2048, 1024)
      self.fc2 = nn.Linear(1024, num_classes)
      self.dropout = nn.Dropout(p=dropout)
  
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 1 to create a new InceptionAux object from inherited base classes: nn with example: obj = InceptionAux(in_channels, num_classes, conv_block, dropout)