code: def sklearn_knn_model():
      iris = datasets.load_iris()
      X = iris.data[:, :2]  # we only take the first two features.
      y = iris.target
      knn_model = knn.KNeighborsClassifier()
      knn_model.fit(X, y)
      return ModelWithData(model=knn_model, inference_data=X)
  
imports: import random
  from collections import namedtuple
  from unittest import mock
  import numpy
  import pytest
  import sklearn.neighbors
  from sklearn import datasets
  import mlflow
  from mlflow import MlflowClient
  from mlflow.entities.model_registry import ModelVersion
  from mlflow.exceptions import MlflowException
  from mlflow.models import add_libraries_to_model
  from mlflow.models.utils import _enforce_array, _enforce_datatype, _enforce_object, _enforce_property, get_model_version_from_model_uri
  from mlflow.types import DataType
  from mlflow.types.schema import Array, Object, Property
label_desc: Use image node_id 1 for calling a global function with example usage: sklearn_knn_model() and returns: ModelWithData