code: def _quantize_model(
      model_topology: str,
      model_weights: str,
      input_data: List[Tuple[np.ndarray, ...]],
      input_names: List[str],
  ) -> Tuple[str, str]:
      return quantize_openvino(
          model_topology, model_weights, input_data, input_names
      )
  
file_path: nebuly/optimization/nebullvm/nebullvm/operations/optimizations/compilers/openvino.py
imports: import subprocess
  from pathlib import Path
  from typing import Tuple, List, Union
  import numpy
  from nebullvm.config import QUANTIZATION_DATA_NUM
  from nebullvm.core.models import QuantizationType, ModelParams
  from nebullvm.operations.optimizations.compilers.base import Compiler
  from nebullvm.operations.optimizations.compilers.quantizations.openvino import quantize_openvino
  from nebullvm.operations.optimizations.compilers.quantizations.utils import check_quantization
  from nebullvm.optional_modules.openvino import Core, CompiledModel
  from nebullvm.tools.data import DataManager
  from nebullvm.tools.onnx import get_input_names
  from nebullvm.tools.transformations import MultiStageTransformation
label_desc: Use image node_id 4 for calling the OpenVINOCompiler obj's underlying member method code with example usage: obj._quantize_model(model_topology, model_weights, input_data, input_names) and returns: quantize_openvino