code: def setup_model_and_evaluate(tmp_recipe_exec_path: Path):
      split_step_output_dir = tmp_recipe_exec_path.joinpath(
          "steps", "split", "outputs"
      )
      split_step_output_dir.mkdir(parents=True)
      X, y = load_diabetes(as_frame=True, return_X_y=True)
      validation_df = X.assign(y=y).sample(n=50, random_state=9)
      validation_df.to_parquet(
          split_step_output_dir.joinpath(_OUTPUT_VALIDATION_FILE_NAME)
      )
      test_df = X.assign(y=y).sample(n=100, random_state=42)
      test_df.to_parquet(
          split_step_output_dir.joinpath(_OUTPUT_TEST_FILE_NAME)
      )
  
      run_id, model = train_and_log_model()
      train_step_output_dir = tmp_recipe_exec_path.joinpath(
          "steps", "train", "outputs"
      )
      train_step_output_dir.mkdir(parents=True)
      train_step_output_dir.joinpath("run_id").write_text(run_id)
      output_model_path = train_step_output_dir.joinpath("sk_model")
      if os.path.exists(output_model_path) and os.path.isdir(
          output_model_path
      ):
          shutil.rmtree(output_model_path)
      mlflow.sklearn.save_model(model, output_model_path)
  
      evaluate_step_output_dir = tmp_recipe_exec_path.joinpath(
          "steps", "evaluate", "outputs"
      )
      evaluate_step_output_dir.mkdir(parents=True)
  
      register_step_output_dir = tmp_recipe_exec_path.joinpath(
          "steps", "register", "outputs"
      )
      register_step_output_dir.mkdir(parents=True)
      return evaluate_step_output_dir, register_step_output_dir
  
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 2 for calling a global function with example usage: setup_model_and_evaluate(tmp_recipe_exec_path) and returns: evaluate_step_output_dir,  register_step_output_dir