code: def __init__(self, model, thread_num=None):
      super().__init__(model.model)
      self.quantized = model
      self.thread_num = thread_num
      self._nano_context_manager = generate_context_manager(
          accelerator=None, precision="int8", thread_num=thread_num
      )
  
file_path: BigDL/python/nano/src/bigdl/nano/deps/neural_compressor/pytorch/quantized_model.py
imports: from pathlib import Path
  import yaml
  import os
  import operator
  import torch
  from bigdl.nano.pytorch.model import AcceleratedLightningModule
  from ..core import version
  from neural_compressor.utils.pytorch import load
  from neural_compressor.model.model import PyTorchModel
  from bigdl.nano.utils.common import invalidInputError
  from bigdl.nano.pytorch.context_manager import generate_context_manager
  from bigdl.nano.pytorch.lightning import LightningModule
  from bigdl.nano.utils.common import compare_version
label_desc: Use image node_id 1 to create a new PytorchQuantizedModel object from inherited base classes: AcceleratedLightningModule with example: obj = PytorchQuantizedModel(model, thread_num)