code: def forward(self, x: Tensor) -> Tensor:
      x = self.quant(x)
      x = self._forward_impl(x)
      x = self.dequant(x)
      return x
  
imports: from functools import partial
  from typing import Any, List, Optional, Union
  import torch
  from torch import nn, Tensor
  from torch.ao.quantization import DeQuantStub, QuantStub
  from ...ops.misc import Conv2dNormActivation, SqueezeExcitation
  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 ..mobilenetv3 import _mobilenet_v3_conf, InvertedResidual, InvertedResidualConfig, MobileNet_V3_Large_Weights, MobileNetV3
  from .utils import _fuse_modules, _replace_relu
label_desc: Use image node_id 2 for calling the QuantizableMobileNetV3 obj's underlying member method code with example usage: obj.forward(x) and returns: x