code: def forward(self, x: Tensor) -> Tensor:
      if self.use_res_connect:
          return self.skip_add.add(x, self.conv(x))
      else:
          return self.conv(x)
  
imports: from functools import partial
  from typing import Any, Optional, Union
  from torch import nn, Tensor
  from torch.ao.quantization import DeQuantStub, QuantStub
  from torchvision.models.mobilenetv2 import InvertedResidual, MobileNet_V2_Weights, MobileNetV2
  from ...ops.misc import Conv2dNormActivation
  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 2 for calling the QuantizableInvertedResidual obj's underlying member method code with example usage: obj.forward(x) and returns: self, self