Thanks but, that was the initial attempt which results in the mentioned error as well.
Traceback (most recent call last):
  File "d:\Codes\org\python\Quantization\quantizer.py", line 265, in <module>
    features = model(img.unsqueeze(0))
  File "C:\Users\User\Anaconda3\Lib\site-packages\torch\nn\modules\module.py", line 550, in __call__
    result = self.forward(*input, **kwargs)
  File "d:\codes\org\python\FV\quantized_models.py", line 418, in forward
    x = self.bn3(x)
  File "C:\Users\User\Anaconda3\Lib\site-packages\torch\nn\modules\module.py", line 550, in __call__
    result = self.forward(*input, **kwargs)
  File "C:\Users\User\Anaconda3\Lib\site-packages\torch\nn\modules\batchnorm.py", line 106, in forward
    exponential_average_factor, self.eps)
  File "C:\Users\User\Anaconda3\Lib\site-packages\torch\nn\functional.py", line 1923, in batch_norm
    training, momentum, eps, torch.backends.cudnn.enabled
RuntimeError: Could not run 'aten::native_batch_norm' with arguments from the 'QuantizedCPUTensorId' backend. 'aten::native_batch_norm' is only available for these backends: [CPUTensorId, MkldnnCPUTensorId, VariableTensorId].