code: def _mixed_precision(
      model: Module, input_tfms: MultiStageTransformation
  ) -> GraphModule:
      with TemporaryDirectory() as tmp_dir:
          config_file_qt = _prepare_mixed_precision_config(
              model, tmp_dir
          )
          converter = MixedPrecision(str(config_file_qt))
          converter.model = model
          compressed_model = converter()
  
      input_tfms.append(HalfPrecisionTransformation())
  
      return compressed_model
  
file_path: nebuly/optimization/nebullvm/nebullvm/operations/optimizations/compilers/quantizations/intel_neural_compressor.py
imports: from pathlib import Path
  from tempfile import TemporaryDirectory
  from typing import Any
  import yaml
  from nebullvm.core.models import QuantizationType
  from nebullvm.optional_modules.neural_compressor import MixedPrecision, Quantization
  from nebullvm.optional_modules.torch import DataLoader, Module, GraphModule
  from nebullvm.tools.data import DataManager, PytorchDataset
  from nebullvm.tools.transformations import MultiStageTransformation, HalfPrecisionTransformation
label_desc: Use image node_id 6 for calling a global function with example usage: _mixed_precision(model, input_tfms) and returns: compressed_model