code: def _read_example_params(mlflow_model: Model, path: str):
      """
      Read params of input_example from a model directory. Returns None if there is no params
      in the input_example or the model was saved without example.
      """
      if (
          mlflow_model.saved_input_example_info is None
          or mlflow_model.saved_input_example_info.get(
              EXAMPLE_PARAMS_KEY, None
          )
          is None
      ):
          return None
      input_example_dict = _get_mlflow_model_input_example_dict(
          mlflow_model, path
      )
      return input_example_dict[EXAMPLE_PARAMS_KEY]
  
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 5 for calling a global function with example usage: _read_example_params(mlflow_model, path) and returns: input_example_dict, None