code: def _prepare_mixed_precision_config(model: Any, tmp_dir: str):
      config = {
          "model": {
              "name": model.__class__.__name__,
              "framework": "pytorch_fx",
          },
          "mixed_precision": {"precisions": "bf16"},
          "evaluation": {"accuracy": {"metric": {"topk": 1}}},
          "tuning": {
              "accuracy_criterion": {"relative": 0.01},
          },
      }
  
      path_file = Path(tmp_dir) / "temp_mp.yaml"
      with open(path_file, "w") as f:
          yaml.dump(config, f)
  
      return path_file
  
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 2 for calling a global function with example usage: _prepare_mixed_precision_config(model, tmp_dir) and returns: path_file