code: def _read_example(mlflow_model: Model, path: str):
      """
      Read example from a model directory. Returns None if there is no example metadata (i.e. the
      model was saved without example). Raises FileNotFoundError if there is model metadata but the
      example file is missing.
  
      :param mlflow_model: Model metadata.
      :param path: Path to the model directory.
      :return: Input example data or None if the model has no example.
      """
      input_example = _get_mlflow_model_input_example_dict(
          mlflow_model, path
      )
      if input_example is None:
          return None
  
      example_type = mlflow_model.saved_input_example_info["type"]
      input_schema = (
          mlflow_model.signature.inputs
          if mlflow_model.signature is not None
          else None
      )
      if mlflow_model.saved_input_example_info.get(
          EXAMPLE_PARAMS_KEY, None
      ):
          input_example = input_example[EXAMPLE_DATA_KEY]
      if example_type == "json_object":
          return input_example
      if example_type == "ndarray":
          return _read_tensor_input_from_json(
              input_example, schema=input_schema
          )
      if example_type in ["sparse_matrix_csc", "sparse_matrix_csr"]:
          return _read_sparse_matrix_from_json(
              input_example, example_type
          )
      return dataframe_from_parsed_json(
          input_example, pandas_orient="split", schema=input_schema
      )
  
imports: import datetime
  import decimal
  import json
  import logging
  import os
  from copy import deepcopy
  from typing import Any, Dict, List, Optional, Union
  import numpy
  import pandas
  from mlflow.exceptions import INVALID_PARAMETER_VALUE, MlflowException
  from mlflow.models import Model
  from mlflow.store.artifact.utils.models import get_model_name_and_version
  from mlflow.types import DataType, ParamSchema, ParamSpec, Schema, TensorSpec
  from mlflow.types.schema import Array, Object, Property
  from mlflow.types.utils import TensorsNotSupportedException, _infer_param_schema, clean_tensor_type
  from mlflow.utils.annotations import experimental
  from mlflow.utils.proto_json_utils import NumpyEncoder, dataframe_from_parsed_json, parse_tf_serving_input
  from mlflow.utils.uri import get_databricks_profile_uri_from_artifact_uri
label_desc: Use image node_id 4 for calling a global function with example usage: _read_example(mlflow_model, path) and returns: dataframe_from_parsed_json, None, input_example, _read_tensor_input_from_json, _read_sparse_matrix_from_json