code: def test_infer_signature_with_input_example(
      input_is_tabular, output_shape, expected_signature
  ):
      model = DummySklearnModel(output_shape=output_shape)
      artifact_path = "model"
      example = (
          pd.DataFrame({"feature": ["value"]})
          if input_is_tabular
          else np.array([[1]])
      )
  
      with mlflow.start_run():
          mlflow.sklearn.log_model(
              model, artifact_path=artifact_path, input_example=example
          )
          model_uri = mlflow.get_artifact_uri(artifact_path)
  
      mlflow_model = Model.load(model_uri)
      assert mlflow_model.signature == expected_signature
  
imports: import json
  import math
  from unittest import mock
  import numpy
  import pandas
  import pytest
  import sklearn.neighbors
  from scipy.sparse import csc_matrix, csr_matrix
  from sklearn import datasets
  from sklearn.base import BaseEstimator, ClassifierMixin
  import mlflow
  from mlflow.models import Model
  from mlflow.models.signature import ModelSignature, infer_signature
  from mlflow.models.utils import _Example, _read_sparse_matrix_from_json, _read_tensor_input_from_json
  from mlflow.types import DataType
  from mlflow.types.schema import ColSpec, Schema, TensorSpec
  from mlflow.types.utils import TensorsNotSupportedException
  from mlflow.utils.file_utils import TempDir
  from mlflow.utils.proto_json_utils import dataframe_from_raw_json
  from tests.helper_functions import AnyStringWith
label_desc: Use image node_id 11 for calling a global function with example usage: test_infer_signature_with_input_example(input_is_tabular, output_shape, expected_signature) without return types