code: def dict_of_ndarrays():
      return {
          "1D": np.arange(0, 12, 0.5),
          "2D": np.arange(0, 12, 0.5).reshape(3, 8),
          "3D": np.arange(0, 12, 0.5).reshape(2, 3, 4),
          "4D": np.arange(0, 12, 0.5).reshape(3, 2, 2, 2),
      }
  
imports: import datetime
  import json
  import math
  import re
  import numpy
  import pandas
  import pyspark
  import pyspark.sql.types
  import pytest
  from scipy.sparse import csc_matrix, csr_matrix
  from mlflow.exceptions import MlflowException
  from mlflow.models.utils import _enforce_tensor_spec
  from mlflow.pyfunc import _parse_spark_datatype
  from mlflow.types import DataType
  from mlflow.types.schema import Array, ColSpec, Object, ParamSchema, ParamSpec, Property, Schema, TensorSpec
  from mlflow.types.utils import _get_tensor_shape, _infer_colspec_type, _infer_param_schema, _infer_schema, _validate_input_dictionary_contains_only_strings_and_lists_of_strings
label_desc: Use image node_id 5 for calling a global function with example usage: dict_of_ndarrays() and returns: dict