code: def __init__(self, *args: Any, **kwargs: Any) -> None:
      super().__init__(*args, conv_block=QuantizableBasicConv2d, **kwargs)  # type: ignore[misc]
      self.myop1 = nn.quantized.FloatFunctional()
      self.myop2 = nn.quantized.FloatFunctional()
      self.myop3 = nn.quantized.FloatFunctional()
  
imports: import warnings
  from functools import partial
  from typing import Any, List, Optional, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from torch import Tensor
  from torchvision.models import inception
  from torchvision.models.inception import Inception_V3_Weights, InceptionOutputs
  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 .utils import _fuse_modules, _replace_relu, quantize_model
label_desc: Use image node_id 1 to create a new QuantizableInceptionE object from inherited base classes: inception_module with example: obj = QuantizableInceptionE()