code: def test_digest_property_has_expected_value():
      source_uri = "test:/my/test/uri"
      source = TestDatasetSource._resolve(source_uri)
      features = np.array([1, 2, 3])
      targets = np.array([4, 5, 6])
      dataset_with_features = NumpyDataset(
          features=features, source=source, name="testname"
      )
      assert (
          dataset_with_features.digest
          == dataset_with_features._compute_digest()
      )
      assert dataset_with_features.digest == "fdf1765f"
      dataset_with_features_and_targets = NumpyDataset(
          features=features,
          targets=targets,
          source=source,
          name="testname",
      )
      assert (
          dataset_with_features_and_targets.digest
          == dataset_with_features_and_targets._compute_digest()
      )
      assert dataset_with_features_and_targets.digest == "1387de76"
  
imports: import json
  import numpy
  import pandas
  import pytest
  import mlflow.data
  from mlflow.data.code_dataset_source import CodeDatasetSource
  from mlflow.data.filesystem_dataset_source import FileSystemDatasetSource
  from mlflow.data.numpy_dataset import NumpyDataset
  from mlflow.data.pyfunc_dataset_mixin import PyFuncInputsOutputs
  from mlflow.data.schema import TensorDatasetSchema
  from mlflow.models.evaluation.base import EvaluationDataset
  from mlflow.types.utils import _infer_schema
  from tests.resources.data.dataset_source import TestDatasetSource
label_desc: Use image node_id 4 for calling a global function with example usage: test_digest_property_has_expected_value() without return types