code: def sklearn_model():
      X, y = load_iris(return_X_y=True, as_frame=True)
      model = LogisticRegression().fit(X, y)
      X_pred = X.sample(frac=0.1, random_state=0)
      y_pred = model.predict(X_pred)
      return namedtuple("Model", ["model", "X_pred", "y_pred"])(
          model, X_pred, y_pred
      )
  
imports: import os
  import sys
  from collections import namedtuple
  from io import BytesIO
  from pathlib import Path
  from stat import S_IRGRP, S_IROTH, S_IRUSR, S_IXGRP, S_IXOTH, S_IXUSR
  import numpy
  import pandas
  import pytest
  import sklearn
  from sklearn.datasets import load_iris
  from sklearn.linear_model import LogisticRegression
  import mlflow
  from mlflow.environment_variables import MLFLOW_ENV_ROOT
  from mlflow.pyfunc.scoring_server import CONTENT_TYPE_JSON
  from mlflow.utils.environment import _PYTHON_ENV_FILE_NAME, _REQUIREMENTS_FILE_NAME
  from mlflow.utils.virtualenv import _is_pyenv_available, _is_virtualenv_available
  from tests.helper_functions import pyfunc_serve_and_score_model
label_desc: Use image node_id 1 for calling a global function with example usage: sklearn_model() and returns: namedtuple