code: def test_set_signature_overwrite():
      artifact_path = "regr-model"
      with mlflow.start_run() as run:
          mlflow.sklearn.log_model(
              sk_model=RandomForestRegressor(),
              artifact_path=artifact_path,
              signature=infer_signature(np.array([1])),
          )
      new_signature = infer_signature(np.array([1]), np.array([1]))
      run_id = run.info.run_id
      model_uri = f"runs:/{run_id}/{artifact_path}"
      set_signature(model_uri, new_signature)
      model_info = get_model_info(model_uri)
      assert model_info.signature == new_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 10 for calling a global function with example usage: test_set_signature_overwrite() without return types