code: def __init__(
      self,
      in_channels: int,
      pool_features: int,
      conv_block: Optional[Callable[..., nn.Module]] = None,
  ) -> None:
      super().__init__()
      if conv_block is None:
          conv_block = BasicConv2d
      self.branch1x1 = conv_block(in_channels, 64, kernel_size=1)
  
      self.branch5x5_1 = conv_block(in_channels, 48, kernel_size=1)
      self.branch5x5_2 = conv_block(48, 64, kernel_size=5, padding=2)
  
      self.branch3x3dbl_1 = conv_block(in_channels, 64, kernel_size=1)
      self.branch3x3dbl_2 = conv_block(64, 96, kernel_size=3, padding=1)
      self.branch3x3dbl_3 = conv_block(96, 96, kernel_size=3, padding=1)
  
      self.branch_pool = conv_block(
          in_channels, pool_features, kernel_size=1
      )
  
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 1 to create a new InceptionA object from inherited base classes: nn with example: obj = InceptionA(in_channels, pool_features, conv_block)