code: def __init__(self, *args: Any, **kwargs: Any) -> None:
      super().__init__(*args, conv_block=QuantizableBasicConv2d, **kwargs)  # type: ignore[misc]
      self.cat = nn.quantized.FloatFunctional()
  
imports: import warnings
  from functools import partial
  from typing import Any, Optional, Union
  import torch
  import torch.nn
  from torch import Tensor
  from torch.nn import functional
  from ...transforms._presets import ImageClassification
  from .._api import register_model, Weights, WeightsEnum
  from .._meta import _IMAGENET_CATEGORIES
  from .._utils import _ovewrite_named_param, handle_legacy_interface
  from ..googlenet import BasicConv2d, GoogLeNet, GoogLeNet_Weights, GoogLeNetOutputs, Inception, InceptionAux
  from .utils import _fuse_modules, _replace_relu, quantize_model
label_desc: Use image node_id 1 to create a new QuantizableInception object from inherited base classes: Inception with example: obj = QuantizableInception()