code: def list_all_artifacts(
      tracking_uri: str, run_id: str, path: Optional[str] = None
  ) -> Generator[str, None, None]:
      artifacts = mlflow.tracking.MlflowClient(
          tracking_uri
      ).list_artifacts(run_id, path)
      for artifact in artifacts:
          if artifact.is_dir:
              yield from list_all_artifacts(
                  tracking_uri, run_id, artifact.path
              )
          else:
              yield artifact.path
  
imports: import os
  import random
  import shutil
  import string
  from contextlib import contextmanager
  from pathlib import Path
  from typing import Generator, Optional
  from sklearn.datasets import load_diabetes, load_iris
  from sklearn.dummy import DummyClassifier, DummyRegressor
  from sklearn.linear_model import LinearRegression, LogisticRegression
  import mlflow
  from mlflow.recipes.step import BaseStep
  from mlflow.recipes.steps.split import _OUTPUT_TEST_FILE_NAME, _OUTPUT_VALIDATION_FILE_NAME
label_desc: Use image node_id 7 for calling a global function with example usage: list_all_artifacts(tracking_uri, run_id, path) without return types