code: def test_set_signature_to_saved_model(tmp_path):
      model_path = str(tmp_path)
      mlflow.sklearn.save_model(
          RandomForestRegressor(),
          model_path,
          serialization_format=mlflow.sklearn.SERIALIZATION_FORMAT_CLOUDPICKLE,
      )
      signature = infer_signature(np.array([1]))
      set_signature(model_path, signature)
      assert Model.load(model_path).signature == signature
  
imports: import json
  import numpy
  import pandas
  import pyspark
  import pytest
  from sklearn.ensemble import RandomForestRegressor
  import mlflow
  from mlflow.exceptions import MlflowException
  from mlflow.models import Model, ModelSignature, infer_signature, set_signature
  from mlflow.models.model import get_model_info
  from mlflow.types import DataType
  from mlflow.types.schema import Array, ColSpec, ParamSchema, ParamSpec, Schema, TensorSpec
label_desc: Use image node_id 9 for calling a global function with example usage: test_set_signature_to_saved_model(tmp_path) without return types